Experiment overview:

Experiment parameters:

Number of evaluations

Result names and types

Last progressbar status

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trial_index,arm_name,trial_status,generation_method,generation_node,RESULT,epochs,lr,bsz,da,db
0,0_0,COMPLETED,Sobol,SOBOL,0.300000000000000044408920985006,72,0.002159496855735779010515562604,5,10,43
1,1_0,COMPLETED,Sobol,SOBOL,0.247368421052631570766777713288,152,0.008417613819148392351188192606,20,76,63
2,2_0,COMPLETED,Sobol,SOBOL,0.273684210526315752076698117889,187,0.004052058681845665741305673180,11,39,88
3,3_0,COMPLETED,Sobol,SOBOL,0.621052631578947300639015338675,12,0.005219838040601462378353936344,25,93,16
4,4_0,COMPLETED,Sobol,SOBOL,0.305263157894736791853063095914,53,0.003484899180196225632055728738,22,82,25
5,5_0,COMPLETED,Sobol,SOBOL,0.236842105263157853833888566442,169,0.007131449778471143224889416956,8,50,92
6,6_0,COMPLETED,Sobol,SOBOL,0.415789473684210486581491750258,110,0.000292149827815592290271989873,31,65,70
7,7_0,COMPLETED,Sobol,SOBOL,0.268421052631578893610253544466,90,0.009019060893822461108526589157,16,21,44
8,8_0,COMPLETED,Sobol,SOBOL,0.363157894736842123961650941055,104,0.004684118163399399181745508258,31,47,59
9,9_0,COMPLETED,Sobol,SOBOL,0.294736842105263185942476411583,119,0.005856737259868532823048337121,17,85,33
10,10_0,COMPLETED,Sobol,SOBOL,0.289473684210526327476031838160,155,0.001568516799993813215507998393,25,30,14
11,11_0,COMPLETED,Sobol,SOBOL,0.294736842105263185942476411583,45,0.007821812945324928614820869655,10,56,80
12,12_0,COMPLETED,Sobol,SOBOL,0.405263157894736880670905065926,27,0.000885487682744860770192585342,14,67,99
13,13_0,COMPLETED,Sobol,SOBOL,0.268421052631578893610253544466,197,0.009617262384947389622369406936,29,18,27
14,14_0,COMPLETED,Sobol,SOBOL,0.357894736842105265495206367632,137,0.002855278081446886283972785847,6,96,54
15,15_0,COMPLETED,Sobol,SOBOL,0.278947368421052610543142691313,62,0.006497021691780537760996239172,20,36,74
16,16_0,COMPLETED,Sobol,SOBOL,0.347368421052631548562317220785,67,0.003181572284922003657908762264,17,63,20
17,17_0,COMPLETED,Sobol,SOBOL,0.305263157894736791853063095914,130,0.006828149437066168350729533643,32,25,86
18,18_0,COMPLETED,Sobol,SOBOL,0.357894736842105265495206367632,189,0.001216615944355726314229926288,10,80,64
19,19_0,COMPLETED,Sobol,SOBOL,0.336842105263157942651730536454,31,0.009943555924575776805429683236,24,54,38
20,20_0,COMPLETED,Sobol,SOBOL,0.431578947368421061980825470528,36,0.001856138612143695557424316611,27,43,48
21,21_0,COMPLETED,Sobol,SOBOL,0.294736842105263185942476411583,159,0.008114269184414296676166600264,13,92,69
22,22_0,COMPLETED,Sobol,SOBOL,0.331578947368421084185285963031,124,0.004976573886163533806670233872,21,14,93
23,23_0,COMPLETED,Sobol,SOBOL,0.247368421052631570766777713288,97,0.006144359735865146873723396936,6,75,21
24,24_0,COMPLETED,Sobol,SOBOL,0.410526315789473739137349639350,81,0.000579772082529962239257070866,18,100,82
25,25_0,COMPLETED,Sobol,SOBOL,0.363157894736842123961650941055,114,0.009311516690347344110678662332,4,34,10
26,26_0,COMPLETED,Sobol,SOBOL,0.331578947368421084185285963031,175,0.003777355640567839258764371024,27,71,37
27,27_0,COMPLETED,Sobol,SOBOL,0.342105263157894690095872647362,46,0.007419071516860276972737953116,12,17,58
28,28_0,COMPLETED,Sobol,SOBOL,0.315789473684210508785952242761,16,0.004378352442756295453962778197,8,28,76
29,29_0,COMPLETED,Sobol,SOBOL,0.300000000000000044408920985006,181,0.005550966228451580629366102215,23,60,50
30,30_0,COMPLETED,Sobol,SOBOL,0.363157894736842123961650941055,145,0.002490624342858791580995747594,15,46,31
31,31_0,COMPLETED,Sobol,SOBOL,0.278947368421052610543142691313,75,0.008743908096384256367628040607,29,89,98
32,32_0,COMPLETED,Sobol,SOBOL,0.405263157894736880670905065926,80,0.003919512849114836598729549877,25,73,46
33,33_0,COMPLETED,Sobol,SOBOL,0.310526315789473650319507669337,143,0.005072050877008587969896336034,10,13,71
34,34_0,COMPLETED,Sobol,SOBOL,0.342105263157894690095872647362,179,0.002022226462699473151923834635,32,89,89
35,35_0,COMPLETED,Sobol,SOBOL,0.352631578947368407028761794209,20,0.008293810995388775295089622830,16,42,25
36,36_0,COMPLETED,Sobol,SOBOL,0.463157894736842101757190448552,50,0.000100348113849759110476241031,6,53,18
37,37_0,COMPLETED,Sobol,SOBOL,0.268421052631578893610253544466,173,0.008853110256697983154738906819,21,78,88
38,38_0,COMPLETED,Sobol,SOBOL,0.352631578947368407028761794209,114,0.003327125069499015704715949582,14,25,61
39,39_0,COMPLETED,Sobol,SOBOL,0.321052631578947367252396816184,87,0.006950882416497917125342009825,28,61,42
40,40_0,COMPLETED,Sobol,SOBOL,0.478947368421052677156524168822,95,0.001378132767602801428408199058,11,87,72
41,41_0,COMPLETED,Sobol,SOBOL,0.326315789473684225718841389607,128,0.007654519567545503902494807846,26,44,53
42,42_0,COMPLETED,Sobol,SOBOL,0.263157894736842146166111433558,165,0.004527379948645830938513956454,5,58,29
43,43_0,COMPLETED,Sobol,SOBOL,0.284210526315789469009587264736,36,0.005675059061031789524320867457,19,28,99
44,44_0,COMPLETED,Sobol,SOBOL,0.352631578947368407028761794209,30,0.002721653866581618622794147555,30,17,78
45,45_0,COMPLETED,Sobol,SOBOL,0.363157894736842123961650941055,194,0.006350236789230257958283054620,16,70,13
46,46_0,COMPLETED,Sobol,SOBOL,0.410526315789473739137349639350,134,0.000746917662210762616122050606,22,33,35
47,47_0,COMPLETED,Sobol,SOBOL,0.363157894736842123961650941055,65,0.009494835346657782421120330696,7,98,60
48,48_0,COMPLETED,Sobol,SOBOL,0.368421052631578982428095514479,58,0.001034539474360644849618151575,26,23,23
49,49_0,COMPLETED,Sobol,SOBOL,0.226315789473684247923301882111,139,0.009787291585747152217189537282,12,66,93
50,50_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.310526315789473650319507669337,114,0.009191625632155343839091443670,26,49,75
51,51_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.210526315789473672523968161840,122,0.008973844702663847164303412285,8,48,92
52,52_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.273684210526315752076698117889,151,0.009665452023960833041749118877,20,56,96
53,53_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,126,0.008561401127126512175524730708,4,56,100
54,54_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,126,0.010000000000000000208166817117,4,45,98
55,55_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.263157894736842146166111433558,172,0.006149551698917648211162312322,13,19,50
56,56_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,119,0.010000000000000000208166817117,11,97,27
57,57_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,179,0.010000000000000000208166817117,4,33,100
58,58_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.278947368421052610543142691313,196,0.007391579804199998812719307750,18,64,97
59,59_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.284210526315789469009587264736,180,0.008285225795562229170188039973,32,10,100
60,60_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.263157894736842146166111433558,178,0.010000000000000000208166817117,32,46,100
61,61_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.205263157894736814057523588417,172,0.010000000000000000208166817117,4,38,45
62,62_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,200,0.007519436911065424493372244541,4,10,100
63,63_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.352631578947368407028761794209,56,0.010000000000000000208166817117,4,10,100
64,64_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.231578947368421106389746455534,200,0.010000000000000000208166817117,4,60,63
65,65_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.257894736842105287699666860135,168,0.009319292839995364785554698983,32,41,22
66,66_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.199999999999999955591079014994,169,0.010000000000000000208166817117,4,11,14
67,67_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.284210526315789469009587264736,175,0.010000000000000000208166817117,4,55,62
68,68_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,200,0.010000000000000000208166817117,4,21,32
69,69_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,181,0.010000000000000000208166817117,4,31,17
70,70_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.321052631578947367252396816184,170,0.007276118271745541689343728109,4,10,10
71,71_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.336842105263157942651730536454,200,0.010000000000000000208166817117,32,94,100
72,72_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.284210526315789469009587264736,200,0.010000000000000000208166817117,4,89,100
73,73_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.278947368421052610543142691313,200,0.010000000000000000208166817117,32,50,61
74,74_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.342105263157894690095872647362,141,0.009347902986113378401289430997,32,10,30
75,75_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.352631578947368407028761794209,200,0.007619937421204864627655162224,4,57,77
76,76_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.231578947368421106389746455534,200,0.007741583027187160306881175131,32,41,67
77,77_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,200,0.010000000000000000208166817117,4,94,10
78,78_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.205263157894736814057523588417,154,0.010000000000000000208166817117,32,68,99
79,79_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.294736842105263185942476411583,149,0.010000000000000000208166817117,32,38,74
80,80_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.273684210526315752076698117889,200,0.010000000000000000208166817117,32,61,100
81,81_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.310526315789473650319507669337,124,0.010000000000000000208166817117,32,56,100
82,82_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,163,0.008221007450340026348478694729,32,43,99
83,83_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.268421052631578893610253544466,180,0.005539100989525490119358419605,32,12,12
84,84_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.315789473684210508785952242761,200,0.008217068266138187124236758052,32,62,77
85,85_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.321052631578947367252396816184,200,0.006635305364903319562397410181,32,49,14
86,86_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.289473684210526327476031838160,188,0.002849797684903414632384688332,16,10,10
87,87_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.357894736842105265495206367632,129,0.010000000000000000208166817117,4,86,100
88,88_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,200,0.010000000000000000208166817117,32,13,86
89,89_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.210526315789473672523968161840,200,0.005718411287274551002557387847,32,37,93
90,90_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.215789473684210530990412735264,200,0.005890238504006059007400697425,4,28,20
91,91_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.221052631578947389456857308687,198,0.007473330891646649994097817427,10,47,100
92,92_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.263157894736842146166111433558,195,0.006947588586385951281432227233,32,57,96
93,93_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.257894736842105287699666860135,200,0.006999312336574543130796044466,4,47,55
94,94_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,200,0.003862484221283773652699800039,9,12,76
95,95_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.273684210526315752076698117889,148,0.007496572519135360525288636069,32,60,100
96,96_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.252631578947368429233222286712,200,0.006388692916692817642954071999,4,39,83
97,97_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.300000000000000044408920985006,200,0.004015615504888952851103578467,31,13,10
98,98_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,197,0.008814566263303845114474022182,4,48,87
99,99_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,198,0.006395623121673584855761962586,32,19,81
100,100_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.336842105263157942651730536454,199,0.000100000000000000004792173602,6,14,99
101,101_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.336842105263157942651730536454,200,0.003832715794613859080358642117,32,14,100
102,102_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,200,0.005647053488861257866671117256,4,39,100
103,103_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.278947368421052610543142691313,132,0.006992551159871015359348334073,4,44,100
104,104_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.336842105263157942651730536454,197,0.006650613252558020167815033830,31,47,59
105,105_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,178,0.005200489102998382372200492085,4,10,10
106,106_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.273684210526315752076698117889,125,0.006618492573964776005956966998,4,11,68
107,107_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.315789473684210508785952242761,200,0.003405501770698202753523409214,4,10,10
108,108_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.257894736842105287699666860135,198,0.006353666458654739189471083449,16,10,10
109,109_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,200,0.007411690616140210324802595210,8,29,36
110,110_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.357894736842105265495206367632,171,0.007444835264396485081939136563,4,28,58
111,111_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.284210526315789469009587264736,113,0.007303532469567609354543780142,6,10,10
112,112_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.263157894736842146166111433558,185,0.006379777375644118779518532136,12,100,99
113,113_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,131,0.010000000000000000208166817117,32,41,99
114,114_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.405263157894736880670905065926,13,0.009639939004401116770526236621,32,12,100
115,115_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.226315789473684247923301882111,196,0.006964278907844177399222296287,6,79,100
116,116_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,137,0.007201578440295736648069091501,32,10,10
117,117_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.331578947368421084185285963031,196,0.007269895243506473841987869378,32,97,100
118,118_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.205263157894736814057523588417,176,0.007715661976693974355434590962,5,68,100
119,119_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.284210526315789469009587264736,182,0.007126128842221518891464349110,32,13,36
120,120_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,150,0.005608510325837110475910574081,4,37,10
121,121_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,199,0.010000000000000000208166817117,4,58,100
122,122_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,176,0.007544040089995325548688498429,4,54,100
123,123_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.268421052631578893610253544466,200,0.006587876248689402726432806645,24,74,98
124,124_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,200,0.007245983778395012619988335700,32,35,10
125,125_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,199,0.007716978661716038072337919829,32,53,100
126,126_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.215789473684210530990412735264,200,0.010000000000000000208166817117,11,100,28
127,127_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.321052631578947367252396816184,164,0.008732151751778332790521197637,4,61,100
128,128_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.263157894736842146166111433558,200,0.007955268831545597718601925408,4,100,100
129,129_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.331578947368421084185285963031,171,0.010000000000000000208166817117,32,65,36
130,130_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.273684210526315752076698117889,146,0.010000000000000000208166817117,32,96,85
131,131_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,200,0.009247274038975425089481596785,32,100,10
132,132_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.305263157894736791853063095914,170,0.010000000000000000208166817117,15,100,100
133,133_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,139,0.010000000000000000208166817117,4,10,62
134,134_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.305263157894736791853063095914,200,0.005300411505429713371340127992,22,10,60
135,135_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,200,0.009147550775024406582991431947,32,100,100
136,136_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.252631578947368429233222286712,200,0.006276218137709642375110519197,4,14,10
137,137_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.226315789473684247923301882111,200,0.008090331956127596452210681832,4,100,72
138,138_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.215789473684210530990412735264,170,0.008065431311046046200519121783,32,65,100
139,139_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.236842105263157853833888566442,200,0.010000000000000000208166817117,25,72,81
140,140_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.221052631578947389456857308687,200,0.006818927987493387209150252914,4,67,74
141,141_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.215789473684210530990412735264,181,0.009807948852069751921600726519,18,71,100
142,142_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.278947368421052610543142691313,192,0.008778703904754868794779731900,10,78,86
143,143_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.284210526315789469009587264736,200,0.008723836780966809020809726860,20,72,100
144,144_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.357894736842105265495206367632,200,0.010000000000000000208166817117,21,82,100
145,145_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,200,0.008205562673371776319375392461,4,83,97
146,146_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.315789473684210508785952242761,200,0.008188855513530147317569074517,32,71,100
147,147_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.300000000000000044408920985006,194,0.005240123944012948717374733576,32,10,29
148,148_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,149,0.008456781280274027964849459238,4,82,94
149,149_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.278947368421052610543142691313,107,0.010000000000000000208166817117,32,88,100
150,150_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,200,0.009220205928450166121823627918,13,93,100
151,151_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.231578947368421106389746455534,200,0.006636325520254724059932005531,4,53,14
152,152_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.236842105263157853833888566442,16,0.009224157563270178952774536185,4,72,100
153,153_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,131,0.009055002469130544670572469101,4,42,19
154,154_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.226315789473684247923301882111,200,0.005210675979331394307159097679,4,10,35
155,155_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,194,0.006440283186455347461119025354,30,10,94
156,156_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.342105263157894690095872647362,64,0.010000000000000000208166817117,32,66,96
157,157_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.294736842105263185942476411583,200,0.006366795333871817959281447230,32,10,47
158,158_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.263157894736842146166111433558,187,0.006161156915159203724396963509,6,22,60
159,159_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.352631578947368407028761794209,200,0.006093395887556598243539607296,4,10,62
160,160_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.321052631578947367252396816184,200,0.008410195902360365766137206833,19,55,77
161,161_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.421052631578947345047936323681,200,0.000100000000000000004792173602,4,10,10
162,162_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.352631578947368407028761794209,11,0.009195792340030112949067486738,17,63,98
163,163_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.221052631578947389456857308687,200,0.006861979032168725838036760223,4,61,100
164,164_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.321052631578947367252396816184,79,0.004305893255039590014621175840,4,10,97
165,165_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.310526315789473650319507669337,197,0.006910819569921325747352547353,32,81,79
166,166_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.294736842105263185942476411583,200,0.005523384869178977162051946692,13,64,100
167,167_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.205263157894736814057523588417,199,0.007296484055514660359287315572,32,17,100
168,168_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.226315789473684247923301882111,200,0.010000000000000000208166817117,4,100,100
169,169_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.257894736842105287699666860135,146,0.005685671836950514750064211711,25,10,98
170,170_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,200,0.006732117230026759061023433617,32,46,100
171,171_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.226315789473684247923301882111,169,0.005610212921339534884734856490,4,10,91
172,172_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.221052631578947389456857308687,200,0.007191064665225875736365157564,16,34,100
173,173_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.321052631578947367252396816184,200,0.005883680150030681961503820077,14,17,100
174,174_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,194,0.006791375637041745412514348601,5,27,100
175,175_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,151,0.007240478928850010639783896238,4,14,100
176,176_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.236842105263157853833888566442,160,0.007236919143649459158773584733,32,21,100
177,177_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.405263157894736880670905065926,29,0.007337152006347317199919100261,32,10,16
178,178_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.342105263157894690095872647362,11,0.005664558821845147584816970721,4,10,23
179,179_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.321052631578947367252396816184,200,0.007048677748485666395839022158,20,55,95
180,180_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.273684210526315752076698117889,101,0.008653011502511638586288000852,4,100,100
181,181_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,200,0.007186284729407227574171646012,19,21,64
182,182_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.252631578947368429233222286712,194,0.008167460065066396365796030921,25,44,98
183,183_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.352631578947368407028761794209,200,0.005884680410065626192384069526,4,93,97
184,184_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.278947368421052610543142691313,186,0.008263050788502663418499949444,23,98,100
185,185_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.273684210526315752076698117889,199,0.007572659872840815063754771330,14,57,68
186,186_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.210526315789473672523968161840,200,0.010000000000000000208166817117,32,28,100
187,187_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.315789473684210508785952242761,137,0.006198461673078726162644525033,32,10,100
188,188_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.268421052631578893610253544466,162,0.007151458931079012794340687975,28,10,99
189,189_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,200,0.008358907818288859037370031047,32,10,63
190,190_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.278947368421052610543142691313,162,0.008362397414184550084592650876,21,57,99
191,191_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.205263157894736814057523588417,200,0.008014716077195765259189030871,4,73,24
192,192_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,100,0.008622640024968035443730940415,19,95,100
193,193_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,200,0.009279379162970363692508612985,4,71,44
194,194_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,150,0.007395487117138771840374467104,4,98,37
195,195_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.300000000000000044408920985006,161,0.009788062287147382412033636001,27,15,100
196,196_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.294736842105263185942476411583,136,0.007633403568166305212805422542,16,48,96
197,197_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.352631578947368407028761794209,10,0.010000000000000000208166817117,21,97,96
198,198_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.352631578947368407028761794209,200,0.005019583766906519396722163862,32,10,100
199,199_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.294736842105263185942476411583,200,0.010000000000000000208166817117,24,54,100
200,200_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.352631578947368407028761794209,150,0.008452201967786758182721307264,28,91,100
201,201_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.310526315789473650319507669337,200,0.007682419943136787644777374595,27,53,100
202,202_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.257894736842105287699666860135,200,0.007060821289075202254748031550,26,40,81
203,203_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.284210526315789469009587264736,200,0.005675232543736551983626359430,17,41,67
204,204_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,197,0.009080733342261820134622141154,7,46,10
205,205_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.347368421052631548562317220785,143,0.007393377912453571489115322635,32,36,100
206,206_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,200,0.006901989778956893646644221718,4,97,32
207,207_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,200,0.010000000000000000208166817117,4,98,70
208,208_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,132,0.006962284509711036406542916666,4,72,100
209,209_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.205263157894736814057523588417,200,0.006647987949018534063749807927,8,33,10
210,210_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.252631578947368429233222286712,200,0.008494435748330803406802580469,32,45,82
211,211_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.268421052631578893610253544466,200,0.007109808041845007073322726399,32,10,10
212,212_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.215789473684210530990412735264,116,0.009037189097683407529304489003,32,14,100
213,213_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,200,0.007050754517434964889488480111,5,17,47
214,214_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.263157894736842146166111433558,200,0.010000000000000000208166817117,31,11,10
215,215_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.347368421052631548562317220785,200,0.007079465356634386148659832116,20,12,10
216,216_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,200,0.010000000000000000208166817117,20,48,56
217,217_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.226315789473684247923301882111,200,0.010000000000000000208166817117,19,18,100
218,218_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.357894736842105265495206367632,22,0.009551570578135821013021633519,4,100,100
219,219_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,200,0.008540657780068185503385969071,22,35,94
220,220_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,200,0.008090921997057680392639866795,18,47,100
221,221_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.226315789473684247923301882111,200,0.009203202713349602215320288678,14,55,100
222,222_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,38,0.010000000000000000208166817117,4,15,10
223,223_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.257894736842105287699666860135,200,0.010000000000000000208166817117,18,100,100
224,224_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,200,0.010000000000000000208166817117,4,10,31
225,225_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,188,0.008323822847507558742030653320,23,10,88
226,226_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.189473684210526349680492330663,183,0.009432517781791624131293438893,25,42,100
227,227_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.284210526315789469009587264736,200,0.008795069051441036303562448495,32,50,100
228,228_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.215789473684210530990412735264,173,0.010000000000000000208166817117,20,55,100
229,229_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.357894736842105265495206367632,110,0.010000000000000000208166817117,32,10,100
230,230_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.236842105263157853833888566442,197,0.010000000000000000208166817117,18,69,100
231,231_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.199999999999999955591079014994,198,0.010000000000000000208166817117,16,40,76
232,232_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.215789473684210530990412735264,200,0.010000000000000000208166817117,15,67,97
233,233_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.210526315789473672523968161840,200,0.008722545113936927552167333033,18,60,100
234,234_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.263157894736842146166111433558,196,0.008447888951106666266532840837,24,37,15
235,235_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.305263157894736791853063095914,200,0.010000000000000000208166817117,19,55,89
236,236_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,200,0.010000000000000000208166817117,32,40,10
237,237_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.289473684210526327476031838160,200,0.008373797244966077468752985169,21,46,92
238,238_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.226315789473684247923301882111,200,0.007788979215599343627896011810,14,62,99
239,239_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.215789473684210530990412735264,187,0.008986995637389359400937216549,22,56,100
240,240_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.273684210526315752076698117889,200,0.005372494801945831149891930067,12,46,25
241,241_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,194,0.007619482658711060861500552477,21,52,100
242,242_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.205263157894736814057523588417,199,0.010000000000000000208166817117,18,67,71
243,243_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.252631578947368429233222286712,200,0.008635857604643880358619156823,24,54,100
244,244_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.221052631578947389456857308687,195,0.008350780281565614929228935637,4,82,51
245,245_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.331578947368421084185285963031,200,0.010000000000000000208166817117,32,46,100
246,246_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,200,0.010000000000000000208166817117,22,44,100
247,247_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.315789473684210508785952242761,199,0.006859634022091961810807525524,24,27,98
248,248_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,200,0.007954020966480139856469300241,17,40,66
249,249_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.336842105263157942651730536454,158,0.007967435937925010369653477937,22,39,100
250,250_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,200,0.008107368603441198265380229770,20,46,61
251,251_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.231578947368421106389746455534,200,0.009415320977673490368542452700,21,66,63
252,252_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,200,0.010000000000000000208166817117,17,89,71
253,253_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.221052631578947389456857308687,135,0.005907636888546158489277093651,19,11,69
254,254_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,200,0.010000000000000000208166817117,12,78,78
255,255_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.205263157894736814057523588417,200,0.010000000000000000208166817117,16,83,100
256,256_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.326315789473684225718841389607,200,0.006027159327444729999823103128,16,32,49
257,257_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,186,0.010000000000000000208166817117,23,10,43
258,258_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,200,0.008689520534490792827431171474,15,57,67
259,259_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.310526315789473650319507669337,200,0.010000000000000000208166817117,19,47,100
260,260_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.331578947368421084185285963031,200,0.008771778642056216393485534866,26,92,100
261,261_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.268421052631578893610253544466,200,0.008346937921320464817687145853,21,67,76
262,262_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,200,0.010000000000000000208166817117,22,67,100
263,263_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.305263157894736791853063095914,200,0.004996106853106147514809176613,19,17,11
264,264_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,200,0.004639546748404329429282810793,4,84,29
265,265_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.331578947368421084185285963031,193,0.003534065841138753129996308289,15,22,10
266,266_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,200,0.008197525385286773616511091234,14,54,39
267,267_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.321052631578947367252396816184,200,0.010000000000000000208166817117,9,72,100
268,268_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.310526315789473650319507669337,200,0.004345771156575503439689622809,24,10,11
269,269_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.252631578947368429233222286712,196,0.008952552377585501833245906766,18,68,84
270,270_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.236842105263157853833888566442,200,0.008273051645066689316343477856,16,68,66
271,271_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.278947368421052610543142691313,191,0.006917195431729271370979716949,19,52,71
272,272_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.210526315789473672523968161840,179,0.007081260330705821046115566730,23,11,98
273,273_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,198,0.010000000000000000208166817117,16,61,16
274,274_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.210526315789473672523968161840,200,0.007717568091060600203590080781,21,22,100
275,275_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.294736842105263185942476411583,182,0.010000000000000000208166817117,23,65,100
276,276_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.236842105263157853833888566442,200,0.008112877661988497982048507140,12,66,75
277,277_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.273684210526315752076698117889,200,0.007488419040197006812387137131,17,46,68
278,278_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.278947368421052610543142691313,191,0.006817054391210549540991436857,20,12,21
279,279_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,200,0.010000000000000000208166817117,26,100,15
280,280_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.215789473684210530990412735264,200,0.008613244195159505678383027316,11,100,78
281,281_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.273684210526315752076698117889,200,0.008070014064729146008314586425,15,79,84
282,282_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.273684210526315752076698117889,200,0.009141647815845721850025462629,11,71,99
283,283_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.215789473684210530990412735264,200,0.008694277327384819162303664086,32,10,93
284,284_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.294736842105263185942476411583,200,0.009200077393416050686170137851,20,47,66
285,285_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,200,0.007507689057276314449629328607,4,94,10
286,286_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.215789473684210530990412735264,200,0.010000000000000000208166817117,32,10,100
287,287_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.300000000000000044408920985006,199,0.008517063318861985490859645154,28,32,96
288,288_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,126,0.008564522668471838406922813647,13,90,99
289,289_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,181,0.009585620321582308950292272698,14,63,80
290,290_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,167,0.006740503075796551446519089268,25,13,48
291,291_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.289473684210526327476031838160,200,0.007712873278365775173148755073,17,46,82
292,292_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.226315789473684247923301882111,199,0.010000000000000000208166817117,24,54,81
293,293_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.231578947368421106389746455534,85,0.008950620350548381398692043831,4,96,100
294,294_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.215789473684210530990412735264,200,0.008800850862490603929155774665,23,19,74
295,295_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,200,0.010000000000000000208166817117,18,95,75
296,296_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.263157894736842146166111433558,199,0.009118120316465956262663716814,21,45,100
297,297_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.289473684210526327476031838160,196,0.007625751617686566015408278219,23,21,69
298,298_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,200,0.007916451674653920966839848461,25,10,80
299,299_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.268421052631578893610253544466,155,0.010000000000000000208166817117,16,73,100
300,300_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.226315789473684247923301882111,138,0.006630719446577613626625513632,4,69,100
301,301_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,177,0.008422487308230952249288314704,15,86,100
302,302_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,200,0.010000000000000000208166817117,4,78,77
303,303_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.321052631578947367252396816184,174,0.004049985575069868330710942672,20,15,100
304,304_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.278947368421052610543142691313,182,0.010000000000000000208166817117,23,69,63
305,305_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.215789473684210530990412735264,200,0.008897920981321699382404766254,19,66,86
306,306_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.263157894736842146166111433558,186,0.008114307449238265801394476284,18,59,86
307,307_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,82,0.010000000000000000208166817117,4,98,89
308,308_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.284210526315789469009587264736,199,0.005081986995639385315537417398,4,37,27
309,309_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,200,0.009084563763158011104326128304,23,54,89
310,310_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.263157894736842146166111433558,167,0.006773720335596076537465481948,4,100,88
311,311_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,193,0.007938052137517170522840181945,4,67,46
312,312_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.305263157894736791853063095914,177,0.007651243603322510286601776386,21,66,100
313,313_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,174,0.009228559003721730283342772339,10,87,62
314,314_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.336842105263157942651730536454,169,0.009020851526925589836114482978,30,11,45
315,315_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,178,0.008754222440827873208402110095,17,53,100
316,316_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.210526315789473672523968161840,200,0.007018616354017095243511548119,11,99,100
317,317_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.300000000000000044408920985006,200,0.008668048713510448019525789221,17,54,87
318,318_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.236842105263157853833888566442,197,0.006927245078039013029269632682,21,10,51
319,319_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.221052631578947389456857308687,126,0.006899321816495437159622028389,6,93,98
320,320_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.278947368421052610543142691313,149,0.006446219156362736554810588530,20,25,39
321,321_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.273684210526315752076698117889,200,0.009065353316835807542806158210,17,71,100
322,322_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.289473684210526327476031838160,134,0.009213101923850481808631052161,22,100,100
323,323_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.263157894736842146166111433558,200,0.008215123645444806499416046108,13,94,100
324,324_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.221052631578947389456857308687,200,0.007765890716633994453332867636,16,73,100
325,325_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.300000000000000044408920985006,111,0.008653153456307179774986693133,32,16,99
326,326_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.273684210526315752076698117889,134,0.008338424920946161875145996589,19,56,100
327,327_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.268421052631578893610253544466,190,0.008665603428693383764036539674,24,11,23
328,328_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.168421052631578915814714036969,196,0.010000000000000000208166817117,23,14,100
329,329_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.326315789473684225718841389607,165,0.008283471963658842543432037075,28,10,100
330,330_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.357894736842105265495206367632,200,0.010000000000000000208166817117,26,13,100
331,331_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.252631578947368429233222286712,163,0.007138298909025157616692336404,14,68,98
332,332_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,142,0.010000000000000000208166817117,8,95,61
333,333_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.236842105263157853833888566442,90,0.006958279122684180896529770877,8,91,100
334,334_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,200,0.007004839123860503134755273180,16,81,100
335,335_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.289473684210526327476031838160,200,0.008926864613218772268043998963,18,87,100
336,336_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.300000000000000044408920985006,148,0.005325037396815215581802327449,23,10,10
337,337_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.257894736842105287699666860135,162,0.008485487525987250173598042124,18,73,100
338,338_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.263157894736842146166111433558,179,0.006686999131018937780890354361,18,30,79
339,339_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.278947368421052610543142691313,116,0.008837301459464990890935176537,14,94,97
340,340_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.294736842105263185942476411583,102,0.006074442441503001034741604514,21,14,98
341,341_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,200,0.010000000000000000208166817117,12,15,10
342,342_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.263157894736842146166111433558,200,0.006605195460404012994248823532,7,100,99
343,343_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.194736842105263208146936904086,199,0.005157929654024255225475137365,11,10,25
344,344_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.268421052631578893610253544466,200,0.005593363859429216662644268609,13,52,55
345,345_0,RUNNING,BoTorch,BOTORCH_MODULAR,,189,0.003232736700506971816437840062,19,15,96

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Download »job_infos.csv« as file

start_time,end_time,run_time,program_string,epochs,lr,bsz,da,db,RESULT,exit_code,signal,hostname,OO_Info_SLURM_JOB_ID
1746613856,1746613881,25,bash /data/horse/ws/pwinkler-oopt/run.sh 72 0.002159496855735779 5 10 43,72,0.002159496855735779,5,10,43,0.30000000000000004,0,None,n1719,16915845
1746613889,1746613907,18,bash /data/horse/ws/pwinkler-oopt/run.sh 152 0.008417613819148392 20 76 63,152,0.008417613819148392,20,76,63,0.24736842105263157,0,None,n1719,16915847
1746613889,1746613907,18,bash /data/horse/ws/pwinkler-oopt/run.sh 187 0.004052058681845666 11 39 88,187,0.004052058681845666,11,39,88,0.27368421052631575,0,None,n1719,16915848
1746613921,1746613939,18,bash /data/horse/ws/pwinkler-oopt/run.sh 12 0.005219838040601462 25 93 16,12,0.005219838040601462,25,93,16,0.6210526315789473,0,None,n1719,16915850
1746613921,1746613939,18,bash /data/horse/ws/pwinkler-oopt/run.sh 53 0.0034848991801962256 22 82 25,53,0.0034848991801962256,22,82,25,0.3052631578947368,0,None,n1719,16915855
1746613953,1746613978,25,bash /data/horse/ws/pwinkler-oopt/run.sh 169 0.007131449778471143 8 50 92,169,0.007131449778471143,8,50,92,0.23684210526315785,0,None,n1719,16915859
1746613985,1746614003,18,bash /data/horse/ws/pwinkler-oopt/run.sh 110 0.0002921498278155923 31 65 70,110,0.0002921498278155923,31,65,70,0.4157894736842105,0,None,n1719,16915863
1746614018,1746614043,25,bash /data/horse/ws/pwinkler-oopt/run.sh 90 0.009019060893822461 16 21 44,90,0.009019060893822461,16,21,44,0.2684210526315789,0,None,n1719,16915876
1746614050,1746614068,18,bash /data/horse/ws/pwinkler-oopt/run.sh 104 0.004684118163399399 31 47 59,104,0.004684118163399399,31,47,59,0.3631578947368421,0,None,n1719,16915879
1746614082,1746614101,19,bash /data/horse/ws/pwinkler-oopt/run.sh 119 0.005856737259868533 17 85 33,119,0.005856737259868533,17,85,33,0.2947368421052632,0,None,n1719,16915881
1746614120,1746614132,12,bash /data/horse/ws/pwinkler-oopt/run.sh 45 0.007821812945324929 10 56 80,45,0.007821812945324929,10,56,80,0.2947368421052632,0,None,n1719,16915884
1746614115,1746614133,18,bash /data/horse/ws/pwinkler-oopt/run.sh 155 0.0015685167999938132 25 30 14,155,0.0015685167999938132,25,30,14,0.2894736842105263,0,None,n1719,16915882
1746614147,1746614166,19,bash /data/horse/ws/pwinkler-oopt/run.sh 27 0.0008854876827448608 14 67 99,27,0.0008854876827448608,14,67,99,0.4052631578947369,0,None,n1719,16915885
1746614180,1746614199,19,bash /data/horse/ws/pwinkler-oopt/run.sh 197 0.00961726238494739 29 18 27,197,0.00961726238494739,29,18,27,0.2684210526315789,0,None,n1719,16915888
1746614212,1746614237,25,bash /data/horse/ws/pwinkler-oopt/run.sh 137 0.0028552780814468863 6 96 54,137,0.0028552780814468863,6,96,54,0.35789473684210527,0,None,n1719,16915890
1746614245,1746614257,12,bash /data/horse/ws/pwinkler-oopt/run.sh 62 0.006497021691780538 20 36 74,62,0.006497021691780538,20,36,74,0.2789473684210526,0,None,n1719,16915893
1746614278,1746614290,12,bash /data/horse/ws/pwinkler-oopt/run.sh 67 0.0031815722849220037 17 63 20,67,0.0031815722849220037,17,63,20,0.34736842105263155,0,None,n1719,16915894
1746614310,1746614328,18,bash /data/horse/ws/pwinkler-oopt/run.sh 130 0.006828149437066168 32 25 86,130,0.006828149437066168,32,25,86,0.3052631578947368,0,None,n1719,16915896
1746614315,1746614333,18,bash /data/horse/ws/pwinkler-oopt/run.sh 189 0.0012166159443557263 10 80 64,189,0.0012166159443557263,10,80,64,0.35789473684210527,0,None,n1719,16915899
1746614342,1746614354,12,bash /data/horse/ws/pwinkler-oopt/run.sh 31 0.009943555924575777 24 54 38,31,0.009943555924575777,24,54,38,0.33684210526315794,0,None,n1719,16915902
1746614374,1746614386,12,bash /data/horse/ws/pwinkler-oopt/run.sh 36 0.0018561386121436956 27 43 48,36,0.0018561386121436956,27,43,48,0.43157894736842106,0,None,n1719,16915903
1746614407,1746614425,18,bash /data/horse/ws/pwinkler-oopt/run.sh 159 0.008114269184414297 13 92 69,159,0.008114269184414297,13,92,69,0.2947368421052632,0,None,n1719,16915906
1746614437,1746614450,13,bash /data/horse/ws/pwinkler-oopt/run.sh 124 0.004976573886163534 21 14 93,124,0.004976573886163534,21,14,93,0.3315789473684211,0,None,n1719,16915907
1746614470,1746614482,12,bash /data/horse/ws/pwinkler-oopt/run.sh 81 0.0005797720825299622 18 100 82,81,0.0005797720825299622,18,100,82,0.41052631578947374,0,None,n1719,16915912
1746614470,1746614488,18,bash /data/horse/ws/pwinkler-oopt/run.sh 97 0.006144359735865147 6 75 21,97,0.006144359735865147,6,75,21,0.24736842105263157,0,None,n1719,16915910
1746614501,1746614526,25,bash /data/horse/ws/pwinkler-oopt/run.sh 114 0.009311516690347344 4 34 10,114,0.009311516690347344,4,34,10,0.3631578947368421,0,None,n1719,16915914
1746614534,1746614546,12,bash /data/horse/ws/pwinkler-oopt/run.sh 175 0.0037773556405678393 27 71 37,175,0.0037773556405678393,27,71,37,0.3315789473684211,0,None,n1719,16915916
1746614565,1746614577,12,bash /data/horse/ws/pwinkler-oopt/run.sh 46 0.007419071516860277 12 17 58,46,0.007419071516860277,12,17,58,0.3421052631578947,0,None,n1719,16915920
1746614598,1746614616,18,bash /data/horse/ws/pwinkler-oopt/run.sh 16 0.0043783524427562955 8 28 76,16,0.0043783524427562955,8,28,76,0.3157894736842105,0,None,n1719,16915922
1746614632,1746614699,67,bash /data/horse/ws/pwinkler-oopt/run.sh 181 0.005550966228451581 23 60 50,181,0.005550966228451581,23,60,50,0.30000000000000004,0,None,n1719,16915925
1746614697,1746614740,43,bash /data/horse/ws/pwinkler-oopt/run.sh 145 0.0024906243428587916 15 46 31,145,0.0024906243428587916,15,46,31,0.3631578947368421,0,None,n1719,16915983
1746614762,1746614811,49,bash /data/horse/ws/pwinkler-oopt/run.sh 75 0.008743908096384256 29 89 98,75,0.008743908096384256,29,89,98,0.2789473684210526,0,None,n1719,16915986
1746614826,1746614862,36,bash /data/horse/ws/pwinkler-oopt/run.sh 80 0.003919512849114837 25 73 46,80,0.003919512849114837,25,73,46,0.4052631578947369,0,None,n1719,16915988
1746614857,1746614937,80,bash /data/horse/ws/pwinkler-oopt/run.sh 143 0.005072050877008588 10 13 71,143,0.005072050877008588,10,13,71,0.31052631578947365,0,None,n1719,16915996
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1746646290,1746646339,49,bash /data/horse/ws/pwinkler-oopt/run.sh 134 0.009213101923850482 22 100 100,134,0.009213101923850482,22,100,100,0.2894736842105263,0,None,n1720,16923180
1746646445,1746646500,55,bash /data/horse/ws/pwinkler-oopt/run.sh 200 0.008215123645444806 13 94 100,200,0.008215123645444806,13,94,100,0.26315789473684215,0,None,n1720,16923184
1746646609,1746646665,56,bash /data/horse/ws/pwinkler-oopt/run.sh 200 0.0077658907166339945 16 73 100,200,0.0077658907166339945,16,73,100,0.2210526315789474,0,None,n1720,16923188
1746646771,1746646820,49,bash /data/horse/ws/pwinkler-oopt/run.sh 111 0.00865315345630718 32 16 99,111,0.00865315345630718,32,16,99,0.30000000000000004,0,None,n1720,16923193
1746646899,1746646935,36,bash /data/horse/ws/pwinkler-oopt/run.sh 134 0.008338424920946162 19 56 100,134,0.008338424920946162,19,56,100,0.27368421052631575,0,None,n1720,16923198
1746647028,1746647059,31,bash /data/horse/ws/pwinkler-oopt/run.sh 190 0.008665603428693384 24 11 23,190,0.008665603428693384,24,11,23,0.2684210526315789,0,None,n1720,16923201
1746647225,1746647268,43,bash /data/horse/ws/pwinkler-oopt/run.sh 196 0.01 23 14 100,196,0.01,23,14,100,0.16842105263157892,0,None,n1720,16923205
1746647322,1746647359,37,bash /data/horse/ws/pwinkler-oopt/run.sh 165 0.008283471963658843 28 10 100,165,0.008283471963658843,28,10,100,0.3263157894736842,0,None,n1720,16923209
1746647550,1746647593,43,bash /data/horse/ws/pwinkler-oopt/run.sh 200 0.01 26 13 100,200,0.01,26,13,100,0.35789473684210527,0,None,n1720,16923215
1746647648,1746647691,43,bash /data/horse/ws/pwinkler-oopt/run.sh 163 0.007138298909025158 14 68 98,163,0.007138298909025158,14,68,98,0.25263157894736843,0,None,n1720,16923218
1746647779,1746647822,43,bash /data/horse/ws/pwinkler-oopt/run.sh 142 0.01 8 95 61,142,0.01,8,95,61,0.3631578947368421,0,None,n1720,16923221
1746647907,1746647944,37,bash /data/horse/ws/pwinkler-oopt/run.sh 90 0.006958279122684181 8 91 100,90,0.006958279122684181,8,91,100,0.23684210526315785,0,None,n1720,16923225
1746648132,1746648169,37,bash /data/horse/ws/pwinkler-oopt/run.sh 200 0.007004839123860503 16 81 100,200,0.007004839123860503,16,81,100,0.3631578947368421,0,None,n1720,16923229
1746648228,1746648258,30,bash /data/horse/ws/pwinkler-oopt/run.sh 200 0.008926864613218772 18 87 100,200,0.008926864613218772,18,87,100,0.2894736842105263,0,None,n1720,16923233
1746648357,1746648394,37,bash /data/horse/ws/pwinkler-oopt/run.sh 148 0.005325037396815216 23 10 10,148,0.005325037396815216,23,10,10,0.30000000000000004,0,None,n1720,16923236
1746648486,1746648516,30,bash /data/horse/ws/pwinkler-oopt/run.sh 162 0.00848548752598725 18 73 100,162,0.00848548752598725,18,73,100,0.2578947368421053,0,None,n1720,16923239
1746648676,1746648719,43,bash /data/horse/ws/pwinkler-oopt/run.sh 179 0.006686999131018938 18 30 79,179,0.006686999131018938,18,30,79,0.26315789473684215,0,None,n1720,16923243
1746648800,1746648843,43,bash /data/horse/ws/pwinkler-oopt/run.sh 116 0.008837301459464991 14 94 97,116,0.008837301459464991,14,94,97,0.2789473684210526,0,None,n1720,16923245
1746649016,1746649059,43,bash /data/horse/ws/pwinkler-oopt/run.sh 102 0.006074442441503001 21 14 98,102,0.006074442441503001,21,14,98,0.2947368421052632,0,None,n1720,16923249
1746649142,1746649185,43,bash /data/horse/ws/pwinkler-oopt/run.sh 200 0.01 12 15 10,200,0.01,12,15,10,0.3631578947368421,0,None,n1720,16923252
1746649360,1746649409,49,bash /data/horse/ws/pwinkler-oopt/run.sh 200 0.006605195460404013 7 100 99,200,0.006605195460404013,7,100,99,0.26315789473684215,0,None,n1720,16923257
1746649450,1746649493,43,bash /data/horse/ws/pwinkler-oopt/run.sh 199 0.005157929654024255 11 10 25,199,0.005157929654024255,11,10,25,0.1947368421052632,0,None,n1720,16923259
1746649670,1746649719,49,bash /data/horse/ws/pwinkler-oopt/run.sh 200 0.005593363859429217 13 52 55,200,0.005593363859429217,13,52,55,0.2684210526315789,0,None,n1720,16923265

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To cancel, press CTRL c, then run 'scancel 16915841'
⠧ Loading base modules...
⠋ Loading rich_argparse...
⠋ Loading torch...
⠋ Loading numpy...
⠧ Loading ax...
⠋ Loading botorch...
⠋ Loading submitit...
⠋ Loading ax logger...
Run-UUID: 20f1ba46-7391-4e5a-b557-17a921c65e25
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⠋ Checking if has random steps...
⠋ Writing worker creation log...
omniopt --partition=barnard --experiment_name=vergl_botorch --mem_gb=10 --time=600 --worker_timeout=30 --max_eval=2000 --num_parallel_jobs=50 --gpus=0 --num_random_steps=50 --follow --live_share --send_anonymized_usage_stats --checkout_to_latest_tested_version --result_names RESULT=min --run_program=YmFzaCAvZGF0YS9ob3JzZS93cy9wd2lua2xlci1vb3B0L3J1bi5zaCAlKGVwb2NocykgJShscikgJShic3opICUoZGEpICUoZGIp --cpus_per_task=1 --nodes_per_job=1 --revert_to_random_when_seemingly_exhausted --model=BOTORCH_MODULAR --n_estimators_randomforest=100 --run_mode=local --decimalrounding=4 --occ_type=euclid --main_process_gb=8 --max_nr_of_zero_results=50 --pareto_front_confidence=1 --slurm_signal_delay_s=0 --max_failed_jobs=0 --parameter epochs range 10 200 int false --parameter lr range 0.0001 0.01 float false --parameter bsz range 4 32 int false --parameter da range 10 100 int false --parameter db range 10 100 int false --ui_url 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
⠋ Saving state files...
Run-folder: runs/vergl_botorch/5
⠋ Parsing parameters...
⠋ Disabling logging...
⠋ Initializing ax_client...
⠋ Getting experiment parameters...
⠋ Setting orchestrator...
You have 2 CPUs available for the main process. No CUDA devices found. Generation strategy: SOBOL for 50 steps and then BOTORCH_MODULAR for 1950 steps.
Run-Program: bash /data/horse/ws/pwinkler-oopt/run.sh %(epochs) %(lr) %(bsz) %(da) %(db)
                      Experiment parameters:                       
┏━━━━━━━━┳━━━━━━━┳━━━━━━━━━━━━━┳━━━━━━━━━━━━━┳━━━━━━━┳━━━━━━━━━━━━┓
┃ Name   ┃ Type  ┃ Lower bound ┃ Upper bound ┃ Type  ┃ Log Scale? ┃
┡━━━━━━━━╇━━━━━━━╇━━━━━━━━━━━━━╇━━━━━━━━━━━━━╇━━━━━━━╇━━━━━━━━━━━━┩
│ epochs │ range │ 10          │ 200         │ int   │ No         │
│ lr     │ range │ 0.0001      │ 0.01        │ float │ No         │
│ bsz    │ range │ 4           │ 32          │ int   │ No         │
│ da     │ range │ 10          │ 100         │ int   │ No         │
│ db     │ range │ 10          │ 100         │ int   │ No         │
└────────┴───────┴─────────────┴─────────────┴───────┴────────────┘
        Result-Names:        
┏━━━━━━━━━━━━━┳━━━━━━━━━━━━━┓
┃ Result-Name ┃ Min or max? ┃
┡━━━━━━━━━━━━━╇━━━━━━━━━━━━━┩
│ RESULT      │         min │
└─────────────┴─────────────┘
See https://imageseg.scads.de/omniax/share?user_id=pwinkler&experiment_name=vergl_botorch&run_nr=1 for live-results.

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BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          :   4%|░░░░░░░░░░| 88/2000 1:14:44<45:10:09, 85.05s/it]

Runtime (end): 1 hours 17 minutes and 30 seconds, PID: 3681959
Exit-Code 1, this means: There was an error regarding the python-syntax. Is your python-version too old? If you are on a slurm-system, this may mean that the job cannot be started. Check stdout. May also happen when the job was cancelled due to CTRL-c, or when your virtual environment is outdated. Try deleting it, especially when you are running on a tested version. It usually is in ~/.omniax_...
BoTorchModel, best RESULT: 0.16842105263157892, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    :  17%|█▒░░░░░░░░| 345/2000 9:59:57<82:10:30, 178.75s/it]

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2025-05-07 12:30:21: SOBOL, Started OmniOpt2 run...
2025-05-07 12:30:27: SOBOL, getting new HP set     
2025-05-07 12:30:31: Sobol, eval start             
2025-05-07 12:30:35: Sobol, starting new job       
2025-05-07 12:30:38: Sobol, unknown 1∑1 (2%/50), started new job
2025-05-07 12:30:43: Sobol, unknown 1∑1 (2%/50), getting new HP set
2025-05-07 12:30:46: Sobol, pending 1∑1 (2%/50), eval start        
2025-05-07 12:30:49: Sobol, pending 1∑1 (2%/50), starting new job  
2025-05-07 12:30:54: Sobol, running/unknown 1/1∑2 (4%/50), started new job
2025-05-07 12:31:00: Sobol, running/unknown 1/1∑2 (4%/50), getting new HP set
2025-05-07 12:31:03: Sobol, running/pending 1/1∑2 (4%/50), eval start        
2025-05-07 12:31:06: Sobol, running/pending 1/1∑2 (4%/50), starting new job  
2025-05-07 12:31:11: Sobol, running/pending/unknown 1/1/1∑3 (6%/50), started new job
2025-05-07 12:31:17: Sobol, running/pending 1/2∑3 (6%/50), getting new HP set       
2025-05-07 12:31:20: Sobol, running/pending 1/2∑3 (6%/50), eval start               
2025-05-07 12:31:23: Sobol, running/pending 1/2∑3 (6%/50), starting new job         
2025-05-07 12:31:27: Sobol, completed/running/unknown 1/2/1∑4 (8%/50), started new job
2025-05-07 12:31:31: Sobol, completed/running/pending 1/2/1∑4 (8%/50), new result: 0.30000000000000004
2025-05-07 12:31:38: Sobol, best RESULT: 0.30000000000000004, running/pending 2/1∑3 (6%/50), finishing jobs (_get_next_trials), finished 1 job
2025-05-07 12:31:41: Sobol, best RESULT: 0.30000000000000004, running/pending 2/1∑3 (6%/50), getting new HP set                               
2025-05-07 12:31:44: Sobol, best RESULT: 0.30000000000000004, running/pending 2/1∑3 (6%/50), eval start                                       
2025-05-07 12:31:48: Sobol, best RESULT: 0.30000000000000004, running/pending 2/1∑3 (6%/50), starting new job                                 
2025-05-07 12:31:53: Sobol, best RESULT: 0.30000000000000004, completed/pending/unknown 2/1/1∑4 (8%/50), started new job                      
2025-05-07 12:31:57: Sobol, best RESULT: 0.30000000000000004, completed/running/unknown 2/1/1∑4 (8%/50), new result: 0.24736842105263157      
2025-05-07 12:32:05: Sobol, best RESULT: 0.24736842105263157, completed/running 1/2∑3 (6%/50), new result: 0.27368421052631575                
2025-05-07 12:32:11: Sobol, best RESULT: 0.24736842105263157, running 2∑2 (4%/50), finishing jobs (_get_next_trials), finished 2 jobs         
2025-05-07 12:32:14: Sobol, best RESULT: 0.24736842105263157, running 2∑2 (4%/50), getting new HP set                                         
2025-05-07 12:32:18: Sobol, best RESULT: 0.24736842105263157, running 2∑2 (4%/50), eval start                                                 
2025-05-07 12:32:21: Sobol, best RESULT: 0.24736842105263157, running 2∑2 (4%/50), starting new job                                           
2025-05-07 12:32:25: Sobol, best RESULT: 0.24736842105263157, completed/unknown 2/1∑3 (6%/50), started new job                                
2025-05-07 12:32:29: Sobol, best RESULT: 0.24736842105263157, completed/unknown 2/1∑3 (6%/50), new result: 0.6210526315789473                 
2025-05-07 12:32:37: Sobol, best RESULT: 0.24736842105263157, completed/running 1/1∑2 (4%/50), new result: 0.3052631578947368                 
2025-05-07 12:32:43: Sobol, best RESULT: 0.24736842105263157, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 2 jobs         
2025-05-07 12:32:46: Sobol, best RESULT: 0.24736842105263157, running 1∑1 (2%/50), getting new HP set                                         
2025-05-07 12:32:48: Sobol, best RESULT: 0.24736842105263157, running 1∑1 (2%/50), eval start                                                 
2025-05-07 12:32:52: Sobol, best RESULT: 0.24736842105263157, running 1∑1 (2%/50), starting new job                                           
2025-05-07 12:32:56: Sobol, best RESULT: 0.24736842105263157, running/unknown 1/1∑2 (4%/50), started new job                                  
2025-05-07 12:33:00: Sobol, best RESULT: 0.24736842105263157, completed/unknown 1/1∑2 (4%/50), new result: 0.23684210526315785                
2025-05-07 12:33:06: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job          
2025-05-07 12:33:09: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), getting new HP set                                         
2025-05-07 12:33:13: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), eval start                                                 
2025-05-07 12:33:17: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), starting new job                                           
2025-05-07 12:33:23: Sobol, best RESULT: 0.23684210526315785, running/unknown 1/1∑2 (4%/50), started new job                                  
2025-05-07 12:33:27: Sobol, best RESULT: 0.23684210526315785, completed/unknown 1/1∑2 (4%/50), new result: 0.4157894736842105                 
2025-05-07 12:33:34: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job          
2025-05-07 12:33:39: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), getting new HP set                                         
2025-05-07 12:33:46: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), eval start                                                 
2025-05-07 12:33:50: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), starting new job                                           
2025-05-07 12:33:55: Sobol, best RESULT: 0.23684210526315785, running/unknown 1/1∑2 (4%/50), started new job                                  
2025-05-07 12:34:04: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1∑2 (4%/50), getting new HP set                               
2025-05-07 12:34:07: Sobol, best RESULT: 0.23684210526315785, completed/running 1/1∑2 (4%/50), eval start                                     
2025-05-07 12:34:11: Sobol, best RESULT: 0.23684210526315785, completed/running 1/1∑2 (4%/50), starting new job                               
2025-05-07 12:34:16: Sobol, best RESULT: 0.23684210526315785, completed/running/unknown 1/1/1∑3 (6%/50), started new job                      
2025-05-07 12:34:20: Sobol, best RESULT: 0.23684210526315785, completed/running/pending 1/1/1∑3 (6%/50), new result: 0.2684210526315789       
2025-05-07 12:34:26: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1∑2 (4%/50), finishing jobs (_get_next_trials), finished 1 job
2025-05-07 12:34:29: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1∑2 (4%/50), getting new HP set                               
2025-05-07 12:34:33: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1∑2 (4%/50), eval start                                       
2025-05-07 12:34:36: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1∑2 (4%/50), starting new job                                 
2025-05-07 12:34:41: Sobol, best RESULT: 0.23684210526315785, completed/running/unknown 1/1/1∑3 (6%/50), started new job                      
2025-05-07 12:34:45: Sobol, best RESULT: 0.23684210526315785, completed/running/unknown 1/1/1∑3 (6%/50), new result: 0.3631578947368421       
2025-05-07 12:34:52: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1∑2 (4%/50), finishing jobs (_get_next_trials), finished 1 job
2025-05-07 12:34:56: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1∑2 (4%/50), getting new HP set                               
2025-05-07 12:35:00: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1∑2 (4%/50), eval start                                       
2025-05-07 12:35:04: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1∑2 (4%/50), starting new job                                 
2025-05-07 12:35:08: Sobol, best RESULT: 0.23684210526315785, completed/pending/unknown 1/1/1∑3 (6%/50), started new job                      
2025-05-07 12:35:11: Sobol, best RESULT: 0.23684210526315785, completed/running 1/2∑3 (6%/50), new result: 0.2947368421052632                 
2025-05-07 12:35:19: Sobol, best RESULT: 0.23684210526315785, running 2∑2 (4%/50), finishing jobs (_get_next_trials), finished 1 job          
2025-05-07 12:35:22: Sobol, best RESULT: 0.23684210526315785, running 2∑2 (4%/50), getting new HP set                                         
2025-05-07 12:35:26: Sobol, best RESULT: 0.23684210526315785, running 2∑2 (4%/50), eval start                                                 
2025-05-07 12:35:30: Sobol, best RESULT: 0.23684210526315785, running 2∑2 (4%/50), starting new job                                           
2025-05-07 12:35:35: Sobol, best RESULT: 0.23684210526315785, running/completed/unknown 1/1/1∑3 (6%/50), started new job                      
2025-05-07 12:35:38: Sobol, best RESULT: 0.23684210526315785, completed/pending 2/1∑3 (6%/50), new result: 0.2894736842105263                 
2025-05-07 12:35:46: Sobol, best RESULT: 0.23684210526315785, completed/running 1/1∑2 (4%/50), new result: 0.2947368421052632                 
2025-05-07 12:35:55: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 2 jobs         
2025-05-07 12:35:58: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), getting new HP set                                         
2025-05-07 12:36:02: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), eval start                                                 
2025-05-07 12:36:06: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), starting new job                                           
2025-05-07 12:36:10: Sobol, best RESULT: 0.23684210526315785, completed/unknown 1/1∑2 (4%/50), started new job                                
2025-05-07 12:36:15: Sobol, best RESULT: 0.23684210526315785, completed/unknown 1/1∑2 (4%/50), new result: 0.4052631578947369                 
2025-05-07 12:36:24: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job          
2025-05-07 12:36:27: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), getting new HP set                                         
2025-05-07 12:36:30: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), eval start                                                 
2025-05-07 12:36:33: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), starting new job                                           
2025-05-07 12:36:38: Sobol, best RESULT: 0.23684210526315785, running/unknown 1/1∑2 (4%/50), started new job                                  
2025-05-07 12:36:42: Sobol, best RESULT: 0.23684210526315785, completed/pending 1/1∑2 (4%/50), new result: 0.2684210526315789                 
2025-05-07 12:36:48: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job          
2025-05-07 12:36:51: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), getting new HP set                                         
2025-05-07 12:36:54: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), eval start                                                 
2025-05-07 12:36:58: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), starting new job                                           
2025-05-07 12:37:04: Sobol, best RESULT: 0.23684210526315785, running/unknown 1/1∑2 (4%/50), started new job                                  
2025-05-07 12:37:11: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1∑2 (4%/50), getting new HP set                               
2025-05-07 12:37:14: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1∑2 (4%/50), eval start                                       
2025-05-07 12:37:17: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1∑2 (4%/50), starting new job                                 
2025-05-07 12:37:22: Sobol, best RESULT: 0.23684210526315785, completed/running/unknown 1/1/1∑3 (6%/50), started new job                      
2025-05-07 12:37:27: Sobol, best RESULT: 0.23684210526315785, completed/running/unknown 1/1/1∑3 (6%/50), new result: 0.35789473684210527      
2025-05-07 12:37:34: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1∑2 (4%/50), finishing jobs (_get_next_trials), finished 1 job
2025-05-07 12:37:37: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1∑2 (4%/50), getting new HP set                               
2025-05-07 12:37:41: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1∑2 (4%/50), eval start                                       
2025-05-07 12:37:49: Sobol, best RESULT: 0.23684210526315785, completed/pending 1/1∑2 (4%/50), starting new job                               
2025-05-07 12:37:55: Sobol, best RESULT: 0.23684210526315785, completed/running/unknown 1/1/1∑3 (6%/50), started new job                      
2025-05-07 12:37:59: Sobol, best RESULT: 0.23684210526315785, completed/running/pending 1/1/1∑3 (6%/50), new result: 0.2789473684210526       
2025-05-07 12:38:07: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1∑2 (4%/50), finishing jobs (_get_next_trials), finished 1 job
2025-05-07 12:38:10: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1∑2 (4%/50), getting new HP set                               
2025-05-07 12:38:13: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1∑2 (4%/50), eval start                                       
2025-05-07 12:38:16: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1∑2 (4%/50), starting new job                                 
2025-05-07 12:38:20: Sobol, best RESULT: 0.23684210526315785, completed/pending/unknown 1/1/1∑3 (6%/50), started new job                      
2025-05-07 12:38:24: Sobol, best RESULT: 0.23684210526315785, completed/pending 1/2∑3 (6%/50), new result: 0.34736842105263155                
2025-05-07 12:38:32: Sobol, best RESULT: 0.23684210526315785, running 2∑2 (4%/50), finishing jobs (_get_next_trials), finished 1 job          
2025-05-07 12:38:35: Sobol, best RESULT: 0.23684210526315785, running 2∑2 (4%/50), getting new HP set                                         
2025-05-07 12:38:39: Sobol, best RESULT: 0.23684210526315785, running 2∑2 (4%/50), eval start                                                 
2025-05-07 12:38:42: Sobol, best RESULT: 0.23684210526315785, running 2∑2 (4%/50), starting new job                                           
2025-05-07 12:38:47: Sobol, best RESULT: 0.23684210526315785, running/unknown 2/1∑3 (6%/50), started new job                                  
2025-05-07 12:38:50: Sobol, best RESULT: 0.23684210526315785, running/pending 2/1∑3 (6%/50), new result: 0.3052631578947368                   
2025-05-07 12:38:57: Sobol, best RESULT: 0.23684210526315785, completed/pending 1/1∑2 (4%/50), new result: 0.35789473684210527                
2025-05-07 12:39:04: Sobol, best RESULT: 0.23684210526315785, pending 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 2 jobs         
2025-05-07 12:39:08: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), getting new HP set                                         
2025-05-07 12:39:12: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), eval start                                                 
2025-05-07 12:39:15: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), starting new job                                           
2025-05-07 12:39:21: Sobol, best RESULT: 0.23684210526315785, completed/unknown 1/1∑2 (4%/50), started new job                                
2025-05-07 12:39:25: Sobol, best RESULT: 0.23684210526315785, completed/pending 1/1∑2 (4%/50), new result: 0.33684210526315794                
2025-05-07 12:39:31: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job          
2025-05-07 12:39:35: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), getting new HP set                                         
2025-05-07 12:39:39: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), eval start                                                 
2025-05-07 12:39:42: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), starting new job                                           
2025-05-07 12:39:47: Sobol, best RESULT: 0.23684210526315785, running/unknown 1/1∑2 (4%/50), started new job                                  
2025-05-07 12:39:51: Sobol, best RESULT: 0.23684210526315785, completed/unknown 1/1∑2 (4%/50), new result: 0.43157894736842106                
2025-05-07 12:39:57: Sobol, best RESULT: 0.23684210526315785, pending 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job          
2025-05-07 12:40:01: Sobol, best RESULT: 0.23684210526315785, pending 1∑1 (2%/50), getting new HP set                                         
2025-05-07 12:40:06: Sobol, best RESULT: 0.23684210526315785, pending 1∑1 (2%/50), eval start                                                 
2025-05-07 12:40:11: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), starting new job                                           
2025-05-07 12:40:17: Sobol, best RESULT: 0.23684210526315785, running/unknown 1/1∑2 (4%/50), started new job                                  
2025-05-07 12:40:23: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1∑2 (4%/50), getting new HP set                               
2025-05-07 12:40:27: Sobol, best RESULT: 0.23684210526315785, completed/pending 1/1∑2 (4%/50), eval start                                     
2025-05-07 12:40:30: Sobol, best RESULT: 0.23684210526315785, completed/pending 1/1∑2 (4%/50), starting new job                               
2025-05-07 12:40:35: Sobol, best RESULT: 0.23684210526315785, completed/running/unknown 1/1/1∑3 (6%/50), started new job                      
2025-05-07 12:40:39: Sobol, best RESULT: 0.23684210526315785, completed/running/unknown 1/1/1∑3 (6%/50), new result: 0.2947368421052632       
2025-05-07 12:40:47: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1∑2 (4%/50), finishing jobs (_get_next_trials), finished 1 job
2025-05-07 12:40:50: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1∑2 (4%/50), getting new HP set                               
2025-05-07 12:40:54: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1∑2 (4%/50), eval start                                       
2025-05-07 12:40:57: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1∑2 (4%/50), starting new job                                 
2025-05-07 12:41:01: Sobol, best RESULT: 0.23684210526315785, completed/pending/unknown 1/1/1∑3 (6%/50), started new job                      
2025-05-07 12:41:06: Sobol, best RESULT: 0.23684210526315785, completed/pending/unknown 1/1/1∑3 (6%/50), new result: 0.3315789473684211       
2025-05-07 12:41:14: Sobol, best RESULT: 0.23684210526315785, running 2∑2 (4%/50), finishing jobs (_get_next_trials), finished 1 job          
2025-05-07 12:41:18: Sobol, best RESULT: 0.23684210526315785, running 2∑2 (4%/50), getting new HP set                                         
2025-05-07 12:41:22: Sobol, best RESULT: 0.23684210526315785, running 2∑2 (4%/50), eval start                                                 
2025-05-07 12:41:25: Sobol, best RESULT: 0.23684210526315785, running 2∑2 (4%/50), starting new job                                           
2025-05-07 12:41:30: Sobol, best RESULT: 0.23684210526315785, running/completed/unknown 1/1/1∑3 (6%/50), started new job                      
2025-05-07 12:41:34: Sobol, best RESULT: 0.23684210526315785, completed/pending 2/1∑3 (6%/50), new result: 0.24736842105263157                
2025-05-07 12:41:43: Sobol, best RESULT: 0.23684210526315785, completed/running 1/1∑2 (4%/50), new result: 0.41052631578947374                
2025-05-07 12:41:50: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 2 jobs         
2025-05-07 12:41:53: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), getting new HP set                                         
2025-05-07 12:41:57: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), eval start                                                 
2025-05-07 12:42:00: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), starting new job                                           
2025-05-07 12:42:05: Sobol, best RESULT: 0.23684210526315785, running/unknown 1/1∑2 (4%/50), started new job                                  
2025-05-07 12:42:10: Sobol, best RESULT: 0.23684210526315785, completed/unknown 1/1∑2 (4%/50), new result: 0.3631578947368421                 
2025-05-07 12:42:19: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job          
2025-05-07 12:42:23: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), getting new HP set                                         
2025-05-07 12:42:27: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), eval start                                                 
2025-05-07 12:42:30: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), starting new job                                           
2025-05-07 12:42:35: Sobol, best RESULT: 0.23684210526315785, completed/unknown 1/1∑2 (4%/50), started new job                                
2025-05-07 12:42:39: Sobol, best RESULT: 0.23684210526315785, completed/pending 1/1∑2 (4%/50), new result: 0.3315789473684211                 
2025-05-07 12:42:47: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job          
2025-05-07 12:42:50: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), getting new HP set                                         
2025-05-07 12:42:54: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), eval start                                                 
2025-05-07 12:42:58: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), starting new job                                           
2025-05-07 12:43:02: Sobol, best RESULT: 0.23684210526315785, completed/unknown 1/1∑2 (4%/50), started new job                                
2025-05-07 12:43:07: Sobol, best RESULT: 0.23684210526315785, completed/pending 1/1∑2 (4%/50), new result: 0.3421052631578947                 
2025-05-07 12:43:14: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job          
2025-05-07 12:43:18: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), getting new HP set                                         
2025-05-07 12:43:23: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), eval start                                                 
2025-05-07 12:43:28: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), starting new job                                           
2025-05-07 12:43:35: Sobol, best RESULT: 0.23684210526315785, running/unknown 1/1∑2 (4%/50), started new job                                  
2025-05-07 12:43:40: Sobol, best RESULT: 0.23684210526315785, completed/pending 1/1∑2 (4%/50), new result: 0.3157894736842105                 
2025-05-07 12:44:00: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job          
2025-05-07 12:44:10: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), getting new HP set                                         
2025-05-07 12:44:21: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), eval start                                                 
2025-05-07 12:44:29: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), starting new job                                           
2025-05-07 12:44:40: Sobol, best RESULT: 0.23684210526315785, running/unknown 1/1∑2 (4%/50), started new job                                  
2025-05-07 12:44:59: Sobol, best RESULT: 0.23684210526315785, running 2∑2 (4%/50), getting new HP set                                         
2025-05-07 12:45:07: Sobol, best RESULT: 0.23684210526315785, completed/running 1/1∑2 (4%/50), eval start                                     
2025-05-07 12:45:15: Sobol, best RESULT: 0.23684210526315785, completed/running 1/1∑2 (4%/50), starting new job                               
2025-05-07 12:45:24: Sobol, best RESULT: 0.23684210526315785, completed/running/unknown 1/1/1∑3 (6%/50), started new job                      
2025-05-07 12:45:35: Sobol, best RESULT: 0.23684210526315785, completed/running/pending 1/1/1∑3 (6%/50), new result: 0.30000000000000004      
2025-05-07 12:45:50: Sobol, best RESULT: 0.23684210526315785, completed/pending 1/1∑2 (4%/50), new result: 0.3631578947368421                 
2025-05-07 12:46:04: Sobol, best RESULT: 0.23684210526315785, pending 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 2 jobs         
2025-05-07 12:46:12: Sobol, best RESULT: 0.23684210526315785, pending 1∑1 (2%/50), getting new HP set                                         
2025-05-07 12:46:21: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), eval start                                                 
2025-05-07 12:46:28: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), starting new job                                           
2025-05-07 12:46:39: Sobol, best RESULT: 0.23684210526315785, running/unknown 1/1∑2 (4%/50), started new job                                  
2025-05-07 12:46:52: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1∑2 (4%/50), getting new HP set                               
2025-05-07 12:47:00: Sobol, best RESULT: 0.23684210526315785, completed/running 1/1∑2 (4%/50), eval start                                     
2025-05-07 12:47:06: Sobol, best RESULT: 0.23684210526315785, completed/running 1/1∑2 (4%/50), starting new job                               
2025-05-07 12:47:13: Sobol, best RESULT: 0.23684210526315785, completed/running/unknown 1/1/1∑3 (6%/50), started new job                      
2025-05-07 12:47:20: Sobol, best RESULT: 0.23684210526315785, completed/running/pending 1/1/1∑3 (6%/50), new result: 0.2789473684210526       
2025-05-07 12:47:32: Sobol, best RESULT: 0.23684210526315785, running 2∑2 (4%/50), finishing jobs (_get_next_trials), finished 1 job          
2025-05-07 12:47:41: Sobol, best RESULT: 0.23684210526315785, running 2∑2 (4%/50), getting new HP set                                         
2025-05-07 12:47:47: Sobol, best RESULT: 0.23684210526315785, running 2∑2 (4%/50), eval start                                                 
2025-05-07 12:47:54: Sobol, best RESULT: 0.23684210526315785, completed/running 1/1∑2 (4%/50), starting new job                               
2025-05-07 12:48:09: Sobol, best RESULT: 0.23684210526315785, completed/running/unknown 1/1/1∑3 (6%/50), started new job                      
2025-05-07 12:48:24: Sobol, best RESULT: 0.23684210526315785, completed/running/pending 1/1/1∑3 (6%/50), new result: 0.4052631578947369       
2025-05-07 12:48:57: Sobol, best RESULT: 0.23684210526315785, running 2∑2 (4%/50), finishing jobs (_get_next_trials), finished 1 job          
2025-05-07 12:49:09: Sobol, best RESULT: 0.23684210526315785, running 2∑2 (4%/50), getting new HP set                                         
2025-05-07 12:49:15: Sobol, best RESULT: 0.23684210526315785, running 2∑2 (4%/50), eval start                                                 
2025-05-07 12:49:22: Sobol, best RESULT: 0.23684210526315785, running 2∑2 (4%/50), starting new job                                           
2025-05-07 12:49:45: Sobol, best RESULT: 0.23684210526315785, completed/running/unknown 1/1/1∑3 (6%/50), started new job                      
2025-05-07 12:50:06: Sobol, best RESULT: 0.23684210526315785, completed/running/pending 1/1/1∑3 (6%/50), new result: 0.31052631578947365      
2025-05-07 12:50:44: Sobol, best RESULT: 0.23684210526315785, running 2∑2 (4%/50), finishing jobs (_get_next_trials), finished 1 job          
2025-05-07 12:50:52: Sobol, best RESULT: 0.23684210526315785, running 2∑2 (4%/50), getting new HP set                                         
2025-05-07 12:50:58: Sobol, best RESULT: 0.23684210526315785, running 2∑2 (4%/50), eval start                                                 
2025-05-07 12:51:04: Sobol, best RESULT: 0.23684210526315785, running 2∑2 (4%/50), starting new job                                           
2025-05-07 12:51:12: Sobol, best RESULT: 0.23684210526315785, completed/running/unknown 1/1/1∑3 (6%/50), started new job                      
2025-05-07 12:51:18: Sobol, best RESULT: 0.23684210526315785, completed/pending 2/1∑3 (6%/50), new result: 0.3421052631578947                 
2025-05-07 12:51:32: Sobol, best RESULT: 0.23684210526315785, completed/running 1/1∑2 (4%/50), new result: 0.3526315789473684                 
2025-05-07 12:51:46: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 2 jobs         
2025-05-07 12:51:51: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), getting new HP set                                         
2025-05-07 12:51:58: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), eval start                                                 
2025-05-07 12:52:04: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), starting new job                                           
2025-05-07 12:52:11: Sobol, best RESULT: 0.23684210526315785, completed/unknown 1/1∑2 (4%/50), started new job                                
2025-05-07 12:52:18: Sobol, best RESULT: 0.23684210526315785, completed/pending 1/1∑2 (4%/50), new result: 0.4631578947368421                 
2025-05-07 12:52:32: Sobol, best RESULT: 0.23684210526315785, pending 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job          
2025-05-07 12:52:38: Sobol, best RESULT: 0.23684210526315785, pending 1∑1 (2%/50), getting new HP set                                         
2025-05-07 12:52:45: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), eval start                                                 
2025-05-07 12:52:51: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), starting new job                                           
2025-05-07 12:52:58: Sobol, best RESULT: 0.23684210526315785, running/unknown 1/1∑2 (4%/50), started new job                                  
2025-05-07 12:53:11: Sobol, best RESULT: 0.23684210526315785, running 2∑2 (4%/50), getting new HP set                                         
2025-05-07 12:53:17: Sobol, best RESULT: 0.23684210526315785, completed/running 1/1∑2 (4%/50), eval start                                     
2025-05-07 12:53:23: Sobol, best RESULT: 0.23684210526315785, completed/running 1/1∑2 (4%/50), starting new job                               
2025-05-07 12:53:31: Sobol, best RESULT: 0.23684210526315785, completed/running/unknown 1/1/1∑3 (6%/50), started new job                      
2025-05-07 12:53:38: Sobol, best RESULT: 0.23684210526315785, completed/running 2/1∑3 (6%/50), new result: 0.2684210526315789                 
2025-05-07 12:53:52: Sobol, best RESULT: 0.23684210526315785, completed/running 1/1∑2 (4%/50), new result: 0.3526315789473684                 
2025-05-07 12:54:05: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 2 jobs         
2025-05-07 12:54:11: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), getting new HP set                                         
2025-05-07 12:54:18: Sobol, best RESULT: 0.23684210526315785, completed 1∑1 (2%/50), eval start                                               
2025-05-07 12:54:24: Sobol, best RESULT: 0.23684210526315785, completed 1∑1 (2%/50), starting new job                                         
2025-05-07 12:54:33: Sobol, best RESULT: 0.23684210526315785, completed/unknown 1/1∑2 (4%/50), started new job                                
2025-05-07 12:54:40: Sobol, best RESULT: 0.23684210526315785, completed/running 1/1∑2 (4%/50), new result: 0.32105263157894737                
2025-05-07 12:54:52: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job          
2025-05-07 12:54:58: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), getting new HP set                                         
2025-05-07 12:55:04: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), eval start                                                 
2025-05-07 12:55:11: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), starting new job                                           
2025-05-07 12:55:18: Sobol, best RESULT: 0.23684210526315785, running/unknown 1/1∑2 (4%/50), started new job                                  
2025-05-07 12:55:31: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1∑2 (4%/50), getting new HP set                               
2025-05-07 12:55:37: Sobol, best RESULT: 0.23684210526315785, completed/pending 1/1∑2 (4%/50), eval start                                     
2025-05-07 12:55:44: Sobol, best RESULT: 0.23684210526315785, completed/pending 1/1∑2 (4%/50), starting new job                               
2025-05-07 12:55:51: Sobol, best RESULT: 0.23684210526315785, completed/running/unknown 1/1/1∑3 (6%/50), started new job                      
2025-05-07 12:55:58: Sobol, best RESULT: 0.23684210526315785, completed/running/pending 1/1/1∑3 (6%/50), new result: 0.4789473684210527       
2025-05-07 12:56:11: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1∑2 (4%/50), finishing jobs (_get_next_trials), finished 1 job
2025-05-07 12:56:18: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1∑2 (4%/50), getting new HP set                               
2025-05-07 12:56:25: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1∑2 (4%/50), eval start                                       
2025-05-07 12:56:31: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1∑2 (4%/50), starting new job                                 
2025-05-07 12:56:39: Sobol, best RESULT: 0.23684210526315785, completed/running/unknown 1/1/1∑3 (6%/50), started new job                      
2025-05-07 12:56:45: Sobol, best RESULT: 0.23684210526315785, completed/running/pending 1/1/1∑3 (6%/50), new result: 0.3263157894736842       
2025-05-07 12:57:31: Sobol, best RESULT: 0.23684210526315785, completed 2∑2 (4%/50), new result: 0.26315789473684215                          
2025-05-07 12:57:41: Sobol, best RESULT: 0.23684210526315785, completed 1∑1 (2%/50), new result: 0.28421052631578947                          
2025-05-07 12:57:51: Sobol, best RESULT: 0.23684210526315785, finishing jobs (_get_next_trials), finished 3 jobs                              
2025-05-07 12:57:55: Sobol, best RESULT: 0.23684210526315785, getting new HP set                                                              
2025-05-07 12:58:00: Sobol, best RESULT: 0.23684210526315785, eval start                                                                      
2025-05-07 12:58:04: Sobol, best RESULT: 0.23684210526315785, starting new job                                                                
2025-05-07 12:58:10: Sobol, best RESULT: 0.23684210526315785, unknown 1∑1 (2%/50), started new job                                            
2025-05-07 12:58:20: Sobol, best RESULT: 0.23684210526315785, pending 1∑1 (2%/50), getting new HP set                                         
2025-05-07 12:58:25: Sobol, best RESULT: 0.23684210526315785, pending 1∑1 (2%/50), eval start                                                 
2025-05-07 12:58:30: Sobol, best RESULT: 0.23684210526315785, pending 1∑1 (2%/50), starting new job                                           
2025-05-07 12:58:36: Sobol, best RESULT: 0.23684210526315785, running/unknown 1/1∑2 (4%/50), started new job                                  
2025-05-07 12:58:46: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1∑2 (4%/50), getting new HP set                               
2025-05-07 12:58:50: Sobol, best RESULT: 0.23684210526315785, completed/pending 1/1∑2 (4%/50), eval start                                     
2025-05-07 12:58:54: Sobol, best RESULT: 0.23684210526315785, completed/pending 1/1∑2 (4%/50), starting new job                               
2025-05-07 12:59:00: Sobol, best RESULT: 0.23684210526315785, completed/running/unknown 1/1/1∑3 (6%/50), started new job                      
2025-05-07 12:59:05: Sobol, best RESULT: 0.23684210526315785, completed/running/pending 1/1/1∑3 (6%/50), new result: 0.3526315789473684       
2025-05-07 12:59:14: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1∑2 (4%/50), finishing jobs (_get_next_trials), finished 1 job
2025-05-07 12:59:18: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1∑2 (4%/50), getting new HP set                               
2025-05-07 12:59:22: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1∑2 (4%/50), eval start                                       
2025-05-07 12:59:26: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1∑2 (4%/50), starting new job                                 
2025-05-07 12:59:31: Sobol, best RESULT: 0.23684210526315785, completed/running/unknown 1/1/1∑3 (6%/50), started new job                      
2025-05-07 12:59:36: Sobol, best RESULT: 0.23684210526315785, completed/running/pending 1/1/1∑3 (6%/50), new result: 0.3631578947368421       
2025-05-07 12:59:46: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1∑2 (4%/50), finishing jobs (_get_next_trials), finished 1 job
2025-05-07 12:59:50: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1∑2 (4%/50), getting new HP set                               
2025-05-07 12:59:54: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1∑2 (4%/50), eval start                                       
2025-05-07 12:59:58: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1∑2 (4%/50), starting new job                                 
2025-05-07 13:00:03: Sobol, best RESULT: 0.23684210526315785, completed/pending/unknown 1/1/1∑3 (6%/50), started new job                      
2025-05-07 13:00:08: Sobol, best RESULT: 0.23684210526315785, completed/running 1/2∑3 (6%/50), new result: 0.41052631578947374                
2025-05-07 13:00:18: Sobol, best RESULT: 0.23684210526315785, running 2∑2 (4%/50), finishing jobs (_get_next_trials), finished 1 job          
2025-05-07 13:00:21: Sobol, best RESULT: 0.23684210526315785, running 2∑2 (4%/50), getting new HP set                                         
2025-05-07 13:00:26: Sobol, best RESULT: 0.23684210526315785, running 2∑2 (4%/50), eval start                                                 
2025-05-07 13:00:30: Sobol, best RESULT: 0.23684210526315785, running 2∑2 (4%/50), starting new job                                           
2025-05-07 13:00:35: Sobol, best RESULT: 0.23684210526315785, completed/unknown 2/1∑3 (6%/50), started new job                                
2025-05-07 13:00:40: Sobol, best RESULT: 0.23684210526315785, completed/running 2/1∑3 (6%/50), new result: 0.3631578947368421                 
2025-05-07 13:00:49: Sobol, best RESULT: 0.23684210526315785, completed/running 1/1∑2 (4%/50), new result: 0.368421052631579                  
2025-05-07 13:00:58: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), finishing jobs, finished 2 jobs                            
2025-05-07 13:01:02: Sobol, best RESULT: 0.23684210526315785, running 1∑1 (2%/50), new result: 0.22631578947368425                            
2025-05-07 13:01:10: Sobol, best RESULT: 0.22631578947368425, finishing previous jobs (1), finished 1 job                                     
2025-05-07 13:01:15: Sobol, best RESULT: 0.22631578947368425, getting new HP set                                                              
2025-05-07 13:01:22: BoTorchModel, best RESULT: 0.22631578947368425, eval start                                                               
2025-05-07 13:01:26: BoTorchModel, best RESULT: 0.22631578947368425, starting new job                                                         
2025-05-07 13:01:31: BoTorchModel, best RESULT: 0.22631578947368425, unknown 1∑1 (2%/50), started new job                                     
2025-05-07 13:01:41: BoTorchModel, best RESULT: 0.22631578947368425, pending 1∑1 (2%/50), getting new HP set                                  
2025-05-07 13:01:47: BoTorchModel, best RESULT: 0.22631578947368425, running 1∑1 (2%/50), eval start                                          
2025-05-07 13:01:52: BoTorchModel, best RESULT: 0.22631578947368425, running 1∑1 (2%/50), starting new job                                    
2025-05-07 13:01:58: BoTorchModel, best RESULT: 0.22631578947368425, running/unknown 1/1∑2 (4%/50), started new job                           
2025-05-07 13:02:03: BoTorchModel, best RESULT: 0.22631578947368425, completed/pending 1/1∑2 (4%/50), new result: 0.31052631578947365         
2025-05-07 13:02:12: BoTorchModel, best RESULT: 0.22631578947368425, pending 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:02:16: BoTorchModel, best RESULT: 0.22631578947368425, pending 1∑1 (2%/50), getting new HP set                                  
2025-05-07 13:02:35: BoTorchModel, best RESULT: 0.22631578947368425, running 1∑1 (2%/50), eval start                                          
2025-05-07 13:02:40: BoTorchModel, best RESULT: 0.22631578947368425, running 1∑1 (2%/50), starting new job                                    
2025-05-07 13:02:46: BoTorchModel, best RESULT: 0.22631578947368425, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 13:02:52: BoTorchModel, best RESULT: 0.22631578947368425, completed/running 1/1∑2 (4%/50), new result: 0.21052631578947367         
2025-05-07 13:03:03: BoTorchModel, best RESULT: 0.21052631578947367, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:03:08: BoTorchModel, best RESULT: 0.21052631578947367, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 13:03:17: BoTorchModel, best RESULT: 0.21052631578947367, running 1∑1 (2%/50), eval start                                          
2025-05-07 13:03:23: BoTorchModel, best RESULT: 0.21052631578947367, completed 1∑1 (2%/50), starting new job                                  
2025-05-07 13:03:30: BoTorchModel, best RESULT: 0.21052631578947367, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 13:03:38: BoTorchModel, best RESULT: 0.21052631578947367, completed/pending 1/1∑2 (4%/50), new result: 0.27368421052631575         
2025-05-07 13:03:51: BoTorchModel, best RESULT: 0.21052631578947367, pending 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:03:57: BoTorchModel, best RESULT: 0.21052631578947367, pending 1∑1 (2%/50), getting new HP set                                  
2025-05-07 13:04:05: BoTorchModel, best RESULT: 0.21052631578947367, pending 1∑1 (2%/50), eval start                                          
2025-05-07 13:04:10: BoTorchModel, best RESULT: 0.21052631578947367, pending 1∑1 (2%/50), starting new job                                    
2025-05-07 13:04:17: BoTorchModel, best RESULT: 0.21052631578947367, running/unknown 1/1∑2 (4%/50), started new job                           
2025-05-07 13:04:32: BoTorchModel, best RESULT: 0.21052631578947367, completed/running 1/1∑2 (4%/50), getting new HP set                      
2025-05-07 13:04:43: BoTorchModel, best RESULT: 0.21052631578947367, completed/running 1/1∑2 (4%/50), eval start                              
2025-05-07 13:04:52: BoTorchModel, best RESULT: 0.21052631578947367, completed/running 1/1∑2 (4%/50), starting new job                        
2025-05-07 13:05:02: BoTorchModel, best RESULT: 0.21052631578947367, completed/running/unknown 1/1/1∑3 (6%/50), started new job               
2025-05-07 13:05:10: BoTorchModel, best RESULT: 0.21052631578947367, completed/pending 2/1∑3 (6%/50), new result: 0.3631578947368421          
2025-05-07 13:05:25: BoTorchModel, best RESULT: 0.21052631578947367, completed/pending 1/1∑2 (4%/50), new result: 0.3631578947368421          
2025-05-07 13:05:40: BoTorchModel, best RESULT: 0.21052631578947367, pending 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 2 jobs  
2025-05-07 13:05:47: BoTorchModel, best RESULT: 0.21052631578947367, pending 1∑1 (2%/50), getting new HP set                                  
2025-05-07 13:05:58: BoTorchModel, best RESULT: 0.21052631578947367, running 1∑1 (2%/50), eval start                                          
2025-05-07 13:06:08: BoTorchModel, best RESULT: 0.21052631578947367, running 1∑1 (2%/50), starting new job                                    
2025-05-07 13:06:16: BoTorchModel, best RESULT: 0.21052631578947367, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 13:06:24: BoTorchModel, best RESULT: 0.21052631578947367, completed/pending 1/1∑2 (4%/50), new result: 0.26315789473684215         
2025-05-07 13:06:41: BoTorchModel, best RESULT: 0.21052631578947367, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:06:49: BoTorchModel, best RESULT: 0.21052631578947367, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 13:07:03: BoTorchModel, best RESULT: 0.21052631578947367, running 1∑1 (2%/50), eval start                                          
2025-05-07 13:07:12: BoTorchModel, best RESULT: 0.21052631578947367, running 1∑1 (2%/50), starting new job                                    
2025-05-07 13:07:21: BoTorchModel, best RESULT: 0.21052631578947367, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 13:07:28: BoTorchModel, best RESULT: 0.21052631578947367, completed/pending 1/1∑2 (4%/50), new result: 0.3631578947368421          
2025-05-07 13:07:42: BoTorchModel, best RESULT: 0.21052631578947367, pending 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:07:48: BoTorchModel, best RESULT: 0.21052631578947367, pending 1∑1 (2%/50), getting new HP set                                  
2025-05-07 13:08:00: BoTorchModel, best RESULT: 0.21052631578947367, pending 1∑1 (2%/50), eval start                                          
2025-05-07 13:08:07: BoTorchModel, best RESULT: 0.21052631578947367, running 1∑1 (2%/50), starting new job                                    
2025-05-07 13:08:16: BoTorchModel, best RESULT: 0.21052631578947367, running/unknown 1/1∑2 (4%/50), started new job                           
2025-05-07 13:08:34: BoTorchModel, best RESULT: 0.21052631578947367, completed/pending 1/1∑2 (4%/50), new result: 0.2421052631578947          
2025-05-07 13:08:50: BoTorchModel, best RESULT: 0.21052631578947367, pending 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:09:00: BoTorchModel, best RESULT: 0.21052631578947367, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 13:09:15: BoTorchModel, best RESULT: 0.21052631578947367, running 1∑1 (2%/50), eval start                                          
2025-05-07 13:09:24: BoTorchModel, best RESULT: 0.21052631578947367, running 1∑1 (2%/50), starting new job                                    
2025-05-07 13:09:34: BoTorchModel, best RESULT: 0.21052631578947367, running/unknown 1/1∑2 (4%/50), started new job                           
2025-05-07 13:09:43: BoTorchModel, best RESULT: 0.21052631578947367, completed/pending 1/1∑2 (4%/50), new result: 0.2789473684210526          
2025-05-07 13:10:02: BoTorchModel, best RESULT: 0.21052631578947367, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:10:12: BoTorchModel, best RESULT: 0.21052631578947367, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 13:10:30: BoTorchModel, best RESULT: 0.21052631578947367, running 1∑1 (2%/50), eval start                                          
2025-05-07 13:10:39: BoTorchModel, best RESULT: 0.21052631578947367, running 1∑1 (2%/50), starting new job                                    
2025-05-07 13:10:49: BoTorchModel, best RESULT: 0.21052631578947367, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 13:10:59: BoTorchModel, best RESULT: 0.21052631578947367, completed/running 1/1∑2 (4%/50), new result: 0.28421052631578947         
2025-05-07 13:11:15: BoTorchModel, best RESULT: 0.21052631578947367, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:11:22: BoTorchModel, best RESULT: 0.21052631578947367, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 13:11:33: BoTorchModel, best RESULT: 0.21052631578947367, running 1∑1 (2%/50), eval start                                          
2025-05-07 13:11:43: BoTorchModel, best RESULT: 0.21052631578947367, completed 1∑1 (2%/50), starting new job                                  
2025-05-07 13:11:53: BoTorchModel, best RESULT: 0.21052631578947367, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 13:12:01: BoTorchModel, best RESULT: 0.21052631578947367, completed/pending 1/1∑2 (4%/50), new result: 0.26315789473684215         
2025-05-07 13:12:18: BoTorchModel, best RESULT: 0.21052631578947367, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:12:34: BoTorchModel, best RESULT: 0.21052631578947367, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 13:12:45: BoTorchModel, best RESULT: 0.21052631578947367, running 1∑1 (2%/50), eval start                                          
2025-05-07 13:12:52: BoTorchModel, best RESULT: 0.21052631578947367, running 1∑1 (2%/50), starting new job                                    
2025-05-07 13:13:02: BoTorchModel, best RESULT: 0.21052631578947367, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 13:13:11: BoTorchModel, best RESULT: 0.21052631578947367, completed/running 1/1∑2 (4%/50), new result: 0.20526315789473681         
2025-05-07 13:13:27: BoTorchModel, best RESULT: 0.20526315789473681, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:13:33: BoTorchModel, best RESULT: 0.20526315789473681, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 13:13:47: BoTorchModel, best RESULT: 0.20526315789473681, running 1∑1 (2%/50), eval start                                          
2025-05-07 13:13:54: BoTorchModel, best RESULT: 0.20526315789473681, completed 1∑1 (2%/50), starting new job                                  
2025-05-07 13:14:03: BoTorchModel, best RESULT: 0.20526315789473681, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 13:14:10: BoTorchModel, best RESULT: 0.20526315789473681, completed/pending 1/1∑2 (4%/50), new result: 0.3631578947368421          
2025-05-07 13:14:27: BoTorchModel, best RESULT: 0.20526315789473681, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:14:35: BoTorchModel, best RESULT: 0.20526315789473681, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 13:14:48: BoTorchModel, best RESULT: 0.20526315789473681, running 1∑1 (2%/50), eval start                                          
2025-05-07 13:14:55: BoTorchModel, best RESULT: 0.20526315789473681, running 1∑1 (2%/50), starting new job                                    
2025-05-07 13:15:04: BoTorchModel, best RESULT: 0.20526315789473681, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 13:15:13: BoTorchModel, best RESULT: 0.20526315789473681, completed/pending 1/1∑2 (4%/50), new result: 0.3526315789473684          
2025-05-07 13:15:26: BoTorchModel, best RESULT: 0.20526315789473681, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:15:33: BoTorchModel, best RESULT: 0.20526315789473681, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 13:15:42: BoTorchModel, best RESULT: 0.20526315789473681, running 1∑1 (2%/50), eval start                                          
2025-05-07 13:15:50: BoTorchModel, best RESULT: 0.20526315789473681, running 1∑1 (2%/50), starting new job                                    
2025-05-07 13:15:59: BoTorchModel, best RESULT: 0.20526315789473681, running/unknown 1/1∑2 (4%/50), started new job                           
2025-05-07 13:16:13: BoTorchModel, best RESULT: 0.20526315789473681, running/pending 1/1∑2 (4%/50), getting new HP set                        
2025-05-07 13:16:23: BoTorchModel, best RESULT: 0.20526315789473681, completed/pending 1/1∑2 (4%/50), eval start                              
2025-05-07 13:16:30: BoTorchModel, best RESULT: 0.20526315789473681, completed/pending 1/1∑2 (4%/50), starting new job                        
2025-05-07 13:16:39: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 1/1/1∑3 (6%/50), started new job               
2025-05-07 13:16:47: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 1/1/1∑3 (6%/50), new result: 0.2315789473684211
2025-05-07 13:17:01: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 1/1∑2 (4%/50), new result: 0.2578947368421053          
2025-05-07 13:17:18: BoTorchModel, best RESULT: 0.20526315789473681, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 2 jobs  
2025-05-07 13:17:25: BoTorchModel, best RESULT: 0.20526315789473681, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 13:17:37: BoTorchModel, best RESULT: 0.20526315789473681, running 1∑1 (2%/50), eval start                                          
2025-05-07 13:17:47: BoTorchModel, best RESULT: 0.20526315789473681, running 1∑1 (2%/50), starting new job                                    
2025-05-07 13:17:56: BoTorchModel, best RESULT: 0.20526315789473681, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 13:18:08: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 1/1∑2 (4%/50), new result: 0.19999999999999996         
2025-05-07 13:18:30: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:18:38: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 13:18:53: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 13:19:02: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 13:19:15: BoTorchModel, best RESULT: 0.19999999999999996, running/unknown 1/1∑2 (4%/50), started new job                           
2025-05-07 13:19:26: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.28421052631578947         
2025-05-07 13:19:44: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:19:51: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 13:20:02: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 13:20:10: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 13:20:19: BoTorchModel, best RESULT: 0.19999999999999996, running/unknown 1/1∑2 (4%/50), started new job                           
2025-05-07 13:20:35: BoTorchModel, best RESULT: 0.19999999999999996, running/pending 1/1∑2 (4%/50), getting new HP set                        
2025-05-07 13:20:46: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), eval start                              
2025-05-07 13:20:55: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), starting new job                        
2025-05-07 13:21:02: BoTorchModel, best RESULT: 0.19999999999999996, completed/running/unknown 1/1/1∑3 (6%/50), started new job               
2025-05-07 13:21:10: BoTorchModel, best RESULT: 0.19999999999999996, completed/running/pending 1/1/1∑3 (6%/50), new result: 0.3631578947368421
2025-05-07 13:21:28: BoTorchModel, best RESULT: 0.19999999999999996, running 2∑2 (4%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:21:37: BoTorchModel, best RESULT: 0.19999999999999996, running 2∑2 (4%/50), getting new HP set                                  
2025-05-07 13:21:51: BoTorchModel, best RESULT: 0.19999999999999996, running 2∑2 (4%/50), eval start                                          
2025-05-07 13:22:00: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), starting new job                        
2025-05-07 13:22:08: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 2/1∑3 (6%/50), started new job                         
2025-05-07 13:22:15: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 2/1∑3 (6%/50), new result: 0.3631578947368421          
2025-05-07 13:22:30: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.32105263157894737         
2025-05-07 13:22:43: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 2 jobs  
2025-05-07 13:22:49: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 13:22:59: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), eval start                                        
2025-05-07 13:23:05: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                  
2025-05-07 13:23:13: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 13:23:20: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.33684210526315794         
2025-05-07 13:23:34: BoTorchModel, best RESULT: 0.19999999999999996, pending 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:23:41: BoTorchModel, best RESULT: 0.19999999999999996, pending 1∑1 (2%/50), getting new HP set                                  
2025-05-07 13:23:50: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 13:23:57: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 13:24:04: BoTorchModel, best RESULT: 0.19999999999999996, running/unknown 1/1∑2 (4%/50), started new job                           
2025-05-07 13:24:12: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.28421052631578947         
2025-05-07 13:24:26: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), new result: 0.2789473684210526                    
2025-05-07 13:24:41: BoTorchModel, best RESULT: 0.19999999999999996, finishing jobs (_get_next_trials), finished 2 jobs                       
2025-05-07 13:24:47: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                       
2025-05-07 13:24:58: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                               
2025-05-07 13:25:03: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                         
2025-05-07 13:25:13: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1∑1 (2%/50), started new job                                     
2025-05-07 13:25:29: BoTorchModel, best RESULT: 0.19999999999999996, pending 1∑1 (2%/50), getting new HP set                                  
2025-05-07 13:25:38: BoTorchModel, best RESULT: 0.19999999999999996, pending 1∑1 (2%/50), eval start                                          
2025-05-07 13:25:44: BoTorchModel, best RESULT: 0.19999999999999996, pending 1∑1 (2%/50), starting new job                                    
2025-05-07 13:25:54: BoTorchModel, best RESULT: 0.19999999999999996, running/unknown 1/1∑2 (4%/50), started new job                           
2025-05-07 13:26:12: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), getting new HP set                      
2025-05-07 13:26:24: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), eval start                              
2025-05-07 13:26:43: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), starting new job                        
2025-05-07 13:26:56: BoTorchModel, best RESULT: 0.19999999999999996, completed/running/unknown 1/1/1∑3 (6%/50), started new job               
2025-05-07 13:27:07: BoTorchModel, best RESULT: 0.19999999999999996, completed/running/pending 1/1/1∑3 (6%/50), new result: 0.3421052631578947
2025-05-07 13:27:28: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.3526315789473684          
2025-05-07 13:27:47: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 2 jobs  
2025-05-07 13:27:56: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 13:28:10: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), eval start                                        
2025-05-07 13:28:21: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                  
2025-05-07 13:28:35: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 13:28:48: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.2315789473684211          
2025-05-07 13:29:13: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:29:23: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 13:29:34: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 13:29:45: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 13:29:56: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 13:30:06: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.3631578947368421          
2025-05-07 13:30:26: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:30:34: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 13:30:48: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 13:30:58: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 13:31:10: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 13:31:23: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.20526315789473681         
2025-05-07 13:31:47: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:31:59: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 13:32:15: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), eval start                                        
2025-05-07 13:32:27: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                  
2025-05-07 13:32:43: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 13:32:55: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.2947368421052632          
2025-05-07 13:33:16: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:33:23: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 13:33:37: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 13:33:47: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 13:33:58: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 13:34:08: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.27368421052631575         
2025-05-07 13:34:34: BoTorchModel, best RESULT: 0.19999999999999996, pending 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:34:45: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 13:34:59: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 13:35:09: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 13:35:20: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 13:35:29: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.31052631578947365         
2025-05-07 13:35:51: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:36:04: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 13:36:19: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 13:36:32: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 13:36:45: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 13:36:58: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.2421052631578947          
2025-05-07 13:37:24: BoTorchModel, best RESULT: 0.19999999999999996, pending 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:37:40: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 13:37:56: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 13:38:06: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 13:38:21: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 13:38:34: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.2684210526315789          
2025-05-07 13:39:01: BoTorchModel, best RESULT: 0.19999999999999996, pending 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:39:13: BoTorchModel, best RESULT: 0.19999999999999996, pending 1∑1 (2%/50), getting new HP set                                  
2025-05-07 13:39:28: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), eval start                                        
2025-05-07 13:39:45: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                  
2025-05-07 13:40:00: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 13:40:14: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.3157894736842105          
2025-05-07 13:40:38: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:40:49: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 13:41:01: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 13:41:10: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 13:41:20: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 13:41:29: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.32105263157894737         
2025-05-07 13:41:47: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:41:55: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 13:42:07: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 13:42:16: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                  
2025-05-07 13:42:27: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 13:42:37: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.2894736842105263          
2025-05-07 13:42:58: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:43:11: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 13:43:27: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 13:43:40: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 13:43:58: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 13:44:15: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.35789473684210527         
2025-05-07 13:44:38: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:44:52: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 13:45:05: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 13:45:17: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 13:45:30: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 13:45:41: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.3631578947368421          
2025-05-07 13:46:06: BoTorchModel, best RESULT: 0.19999999999999996, pending 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:46:19: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 13:46:33: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 13:46:45: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 13:46:56: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 13:47:06: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.21052631578947367         
2025-05-07 13:47:28: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:47:36: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 13:47:49: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 13:47:57: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 13:48:06: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 13:48:15: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.21578947368421053         
2025-05-07 13:48:31: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:48:40: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 13:48:52: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 13:49:02: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                  
2025-05-07 13:49:12: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 13:49:23: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.2210526315789474          
2025-05-07 13:49:41: BoTorchModel, best RESULT: 0.19999999999999996, pending 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:49:50: BoTorchModel, best RESULT: 0.19999999999999996, pending 1∑1 (2%/50), getting new HP set                                  
2025-05-07 13:50:03: BoTorchModel, best RESULT: 0.19999999999999996, pending 1∑1 (2%/50), eval start                                          
2025-05-07 13:50:12: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 13:50:23: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 13:50:34: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.26315789473684215         
2025-05-07 13:50:57: BoTorchModel, best RESULT: 0.19999999999999996, pending 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:51:09: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 13:51:22: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 13:51:35: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 13:51:50: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 13:51:59: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.2578947368421053          
2025-05-07 13:52:20: BoTorchModel, best RESULT: 0.19999999999999996, pending 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:52:31: BoTorchModel, best RESULT: 0.19999999999999996, pending 1∑1 (2%/50), getting new HP set                                  
2025-05-07 13:52:47: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 13:53:04: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 13:53:17: BoTorchModel, best RESULT: 0.19999999999999996, running/unknown 1/1∑2 (4%/50), started new job                           
2025-05-07 13:53:38: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.24736842105263157         
2025-05-07 13:54:28: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:54:56: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 13:55:35: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 13:56:07: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 13:56:27: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 13:56:47: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.27368421052631575         
2025-05-07 13:57:41: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:58:12: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 13:58:37: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 13:58:54: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 13:59:16: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 13:59:45: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.25263157894736843         
2025-05-07 14:00:39: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 14:01:01: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 14:01:41: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 14:02:13: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                  
2025-05-07 14:02:40: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 14:03:06: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.30000000000000004         
2025-05-07 14:04:04: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 14:04:27: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 14:04:47: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 14:05:11: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 14:05:33: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 14:06:10: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.3631578947368421          
2025-05-07 14:07:13: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs, finished 1 job                      
2025-05-07 14:07:55: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), waiting for 1 job                                   
2025-05-07 14:08:37: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), waiting for 1 job                                   
2025-05-07 14:09:34: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), new result: 0.24736842105263157                   
2025-05-07 14:10:26: BoTorchModel, best RESULT: 0.19999999999999996, waiting for 1 job), finished 1 job                                       
2025-05-07 14:10:51: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                       
2025-05-07 14:11:25: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                               
2025-05-07 14:11:49: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                         
2025-05-07 14:12:10: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1∑1 (2%/50), started new job                                     
2025-05-07 14:13:07: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 14:13:41: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 14:14:03: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 14:14:28: BoTorchModel, best RESULT: 0.19999999999999996, running/unknown 1/1∑2 (4%/50), started new job                           
2025-05-07 14:14:55: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.33684210526315794         
2025-05-07 14:15:45: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 14:16:04: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 14:16:32: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 14:17:01: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 14:17:34: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 14:18:07: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.33684210526315794         
2025-05-07 14:19:21: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 14:20:02: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 14:20:30: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 14:21:06: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 14:21:37: BoTorchModel, best RESULT: 0.19999999999999996, running/unknown 1/1∑2 (4%/50), started new job                           
2025-05-07 14:22:34: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), getting new HP set                      
2025-05-07 14:23:11: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), eval start                              
2025-05-07 14:23:38: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), starting new job                        
2025-05-07 14:24:11: BoTorchModel, best RESULT: 0.19999999999999996, completed/running/unknown 1/1/1∑3 (6%/50), started new job               
2025-05-07 14:24:38: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 2/1∑3 (6%/50), new result: 0.3631578947368421          
2025-05-07 14:25:42: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.2789473684210526          
2025-05-07 14:26:49: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), new result: 0.33684210526315794                   
2025-05-07 14:27:44: BoTorchModel, best RESULT: 0.19999999999999996, finishing jobs (_get_next_trials), finished 3 jobs                       
2025-05-07 14:28:04: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                       
2025-05-07 14:28:46: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                               
2025-05-07 14:29:17: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                         
2025-05-07 14:29:54: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1∑1 (2%/50), started new job                                     
2025-05-07 14:30:56: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 14:31:42: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 14:32:15: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 14:32:45: BoTorchModel, best RESULT: 0.19999999999999996, running/unknown 1/1∑2 (4%/50), started new job                           
2025-05-07 14:33:16: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.24736842105263157         
2025-05-07 14:34:36: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 14:35:02: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 14:35:45: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 14:36:14: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 14:36:34: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 14:36:54: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.27368421052631575         
2025-05-07 14:37:40: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 14:37:59: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 14:38:24: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 14:38:41: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 14:38:59: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 14:39:16: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.3157894736842105          
2025-05-07 14:39:49: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 14:40:08: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 14:40:28: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 14:40:52: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                  
2025-05-07 14:41:16: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 14:41:35: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.2578947368421053          
2025-05-07 14:42:19: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 14:42:40: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 14:43:05: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 14:43:21: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 14:43:38: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 14:43:54: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.3631578947368421          
2025-05-07 14:44:38: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 14:45:10: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 14:45:32: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 14:45:54: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 14:46:11: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 14:46:28: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.35789473684210527         
2025-05-07 14:46:57: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 14:47:20: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 14:47:41: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 14:47:55: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 14:48:09: BoTorchModel, best RESULT: 0.19999999999999996, running/unknown 1/1∑2 (4%/50), started new job                           
2025-05-07 14:49:05: BoTorchModel, best RESULT: 0.19999999999999996, running 2∑2 (4%/50), getting new HP set                                  
2025-05-07 14:49:52: BoTorchModel, best RESULT: 0.19999999999999996, running 2∑2 (4%/50), eval start                                          
2025-05-07 14:50:25: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), starting new job                        
2025-05-07 14:50:58: BoTorchModel, best RESULT: 0.19999999999999996, completed/running/unknown 1/1/1∑3 (6%/50), started new job               
2025-05-07 14:51:31: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 2/1∑3 (6%/50), new result: 0.28421052631578947         
2025-05-07 14:53:18: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.26315789473684215         
2025-05-07 14:54:49: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), new result: 0.24736842105263157                   
2025-05-07 14:55:51: BoTorchModel, best RESULT: 0.19999999999999996, finishing jobs (_get_next_trials), finished 3 jobs                       
2025-05-07 14:56:15: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                       
2025-05-07 14:56:37: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                               
2025-05-07 14:56:54: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                         
2025-05-07 14:57:12: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1∑1 (2%/50), started new job                                     
2025-05-07 14:57:52: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 14:58:11: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 14:58:31: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 14:58:56: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 14:59:13: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.4052631578947369          
2025-05-07 14:59:50: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 15:00:15: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), getting new HP set                                
2025-05-07 15:00:37: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), eval start                                        
2025-05-07 15:00:55: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                  
2025-05-07 15:01:16: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 15:01:38: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.22631578947368425         
2025-05-07 15:02:14: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 15:02:39: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 15:03:01: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 15:03:23: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                  
2025-05-07 15:03:42: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 15:04:00: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.2421052631578947          
2025-05-07 15:04:35: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 15:04:50: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 15:05:08: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 15:05:27: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 15:05:46: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 15:06:05: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.3315789473684211          
2025-05-07 15:06:43: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 15:07:01: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 15:07:21: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 15:07:41: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 15:08:02: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 15:08:24: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.20526315789473681         
2025-05-07 15:09:03: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 15:09:24: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 15:09:44: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 15:10:06: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                  
2025-05-07 15:10:31: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 15:10:55: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.28421052631578947         
2025-05-07 15:11:43: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), new result: 0.3631578947368421                      
2025-05-07 15:12:21: BoTorchModel, best RESULT: 0.19999999999999996, finishing jobs (_get_next_trials), finished 2 jobs                       
2025-05-07 15:12:40: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                       
2025-05-07 15:13:06: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                               
2025-05-07 15:13:29: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                         
2025-05-07 15:13:50: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1∑1 (2%/50), started new job                                     
2025-05-07 15:14:31: BoTorchModel, best RESULT: 0.19999999999999996, pending 1∑1 (2%/50), getting new HP set                                  
2025-05-07 15:14:51: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 15:15:08: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 15:15:24: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 15:15:42: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.2421052631578947          
2025-05-07 15:16:21: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 15:16:42: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 15:17:08: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 15:17:26: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                  
2025-05-07 15:17:49: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 15:18:18: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.3631578947368421          
2025-05-07 15:18:56: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), new result: 0.2684210526315789                    
2025-05-07 15:19:39: BoTorchModel, best RESULT: 0.19999999999999996, finishing jobs (_get_next_trials), finished 2 jobs                       
2025-05-07 15:19:58: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                       
2025-05-07 15:20:25: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                               
2025-05-07 15:20:47: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                         
2025-05-07 15:21:09: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1∑1 (2%/50), started new job                                     
2025-05-07 15:21:49: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 15:22:10: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 15:22:29: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 15:22:48: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 15:23:10: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.3631578947368421          
2025-05-07 15:23:55: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), new result: 0.24736842105263157                   
2025-05-07 15:24:43: BoTorchModel, best RESULT: 0.19999999999999996, finishing jobs (_get_next_trials), finished 2 jobs                       
2025-05-07 15:25:04: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                       
2025-05-07 15:25:26: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                               
2025-05-07 15:25:47: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                         
2025-05-07 15:26:09: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1∑1 (2%/50), started new job                                     
2025-05-07 15:26:53: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 15:27:18: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), eval start                                        
2025-05-07 15:27:38: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                  
2025-05-07 15:28:04: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 15:28:25: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.21578947368421053         
2025-05-07 15:29:12: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), new result: 0.32105263157894737                     
2025-05-07 15:29:59: BoTorchModel, best RESULT: 0.19999999999999996, finishing jobs (_get_next_trials), finished 2 jobs                       
2025-05-07 15:30:19: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                       
2025-05-07 15:30:50: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                               
2025-05-07 15:31:23: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                         
2025-05-07 15:31:56: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1∑1 (2%/50), started new job                                     
2025-05-07 15:32:59: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 15:33:38: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 15:34:15: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                  
2025-05-07 15:34:44: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 15:35:20: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.26315789473684215         
2025-05-07 15:36:07: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 15:36:23: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 15:36:47: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 15:37:20: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 15:37:49: BoTorchModel, best RESULT: 0.19999999999999996, running/unknown 1/1∑2 (4%/50), started new job                           
2025-05-07 15:38:33: BoTorchModel, best RESULT: 0.19999999999999996, running 2∑2 (4%/50), getting new HP set                                  
2025-05-07 15:38:57: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), eval start                              
2025-05-07 15:39:18: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), starting new job                        
2025-05-07 15:39:40: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 2/1∑3 (6%/50), started new job                         
2025-05-07 15:40:00: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 2/1∑3 (6%/50), new result: 0.3315789473684211          
2025-05-07 15:40:52: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.27368421052631575         
2025-05-07 15:41:35: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), new result: 0.3631578947368421                    
2025-05-07 15:42:12: BoTorchModel, best RESULT: 0.19999999999999996, finishing jobs (_get_next_trials), finished 3 jobs                       
2025-05-07 15:42:28: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                       
2025-05-07 15:42:53: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                               
2025-05-07 15:43:07: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                         
2025-05-07 15:43:26: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1∑1 (2%/50), started new job                                     
2025-05-07 15:43:59: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 15:44:21: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 15:44:36: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                  
2025-05-07 15:44:58: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 15:45:14: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.3052631578947368          
2025-05-07 15:46:01: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 15:46:17: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 15:46:36: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), eval start                                        
2025-05-07 15:46:54: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                  
2025-05-07 15:47:20: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 15:47:40: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.3631578947368421          
2025-05-07 15:48:24: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 15:48:44: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), getting new HP set                                
2025-05-07 15:49:11: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), eval start                                        
2025-05-07 15:49:29: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                  
2025-05-07 15:49:52: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 15:50:14: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.3052631578947368          
2025-05-07 15:50:52: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 15:51:15: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 15:51:40: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 15:52:02: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                  
2025-05-07 15:52:25: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 15:52:47: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.24736842105263157         
2025-05-07 15:53:33: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 15:53:56: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 15:54:25: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 15:54:47: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                  
2025-05-07 15:55:06: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 15:55:27: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.25263157894736843         
2025-05-07 15:56:11: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 15:56:32: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 15:57:02: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 15:57:30: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                  
2025-05-07 15:58:08: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 15:58:39: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.22631578947368425         
2025-05-07 15:59:34: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 16:01:19: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 16:01:55: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 16:03:17: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 16:03:41: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 16:04:08: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.21578947368421053         
2025-05-07 16:04:38: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), new result: 0.23684210526315785                   
2025-05-07 16:05:21: BoTorchModel, best RESULT: 0.19999999999999996, finishing jobs (_get_next_trials), finished 2 jobs                       
2025-05-07 16:05:41: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                       
2025-05-07 16:06:06: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                               
2025-05-07 16:06:29: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                         
2025-05-07 16:06:59: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1∑1 (2%/50), started new job                                     
2025-05-07 16:07:52: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 16:08:28: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 16:08:54: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                  
2025-05-07 16:09:22: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 16:09:49: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.2210526315789474          
2025-05-07 16:10:35: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), new result: 0.21578947368421053                   
2025-05-07 16:12:40: BoTorchModel, best RESULT: 0.19999999999999996, finishing jobs (_get_next_trials), finished 2 jobs                       
2025-05-07 16:13:24: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                       
2025-05-07 16:14:21: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                               
2025-05-07 16:14:51: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                         
2025-05-07 16:15:16: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1∑1 (2%/50), started new job                                     
2025-05-07 16:15:50: BoTorchModel, best RESULT: 0.19999999999999996, pending 1∑1 (2%/50), getting new HP set                                  
2025-05-07 16:16:12: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 16:16:30: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 16:16:52: BoTorchModel, best RESULT: 0.19999999999999996, running/unknown 1/1∑2 (4%/50), started new job                           
2025-05-07 16:17:30: BoTorchModel, best RESULT: 0.19999999999999996, running 2∑2 (4%/50), getting new HP set                                  
2025-05-07 16:17:53: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), eval start                              
2025-05-07 16:18:12: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), starting new job                        
2025-05-07 16:18:32: BoTorchModel, best RESULT: 0.19999999999999996, completed/running/unknown 1/1/1∑3 (6%/50), started new job               
2025-05-07 16:18:54: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/2∑3 (6%/50), new result: 0.2789473684210526          
2025-05-07 16:19:36: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.28421052631578947         
2025-05-07 16:20:13: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 2 jobs  
2025-05-07 16:20:35: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 16:20:56: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), eval start                                        
2025-05-07 16:21:20: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                  
2025-05-07 16:21:43: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 16:22:03: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.35789473684210527         
2025-05-07 16:22:40: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), new result: 0.2421052631578947                    
2025-05-07 16:23:21: BoTorchModel, best RESULT: 0.19999999999999996, finishing jobs (_get_next_trials), finished 2 jobs                       
2025-05-07 16:23:41: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                       
2025-05-07 16:24:02: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                               
2025-05-07 16:24:27: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                         
2025-05-07 16:24:55: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1∑1 (2%/50), started new job                                     
2025-05-07 16:25:42: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 16:26:08: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), eval start                                        
2025-05-07 16:26:27: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                  
2025-05-07 16:26:47: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 16:27:06: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.3157894736842105          
2025-05-07 16:27:43: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), new result: 0.30000000000000004                   
2025-05-07 16:28:26: BoTorchModel, best RESULT: 0.19999999999999996, finishing jobs (_get_next_trials), finished 2 jobs                       
2025-05-07 16:28:46: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                       
2025-05-07 16:29:09: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                               
2025-05-07 16:29:32: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                         
2025-05-07 16:29:59: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1∑1 (2%/50), started new job                                     
2025-05-07 16:30:53: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 16:31:27: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 16:31:47: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 16:32:09: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 16:32:32: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.3631578947368421          
2025-05-07 16:33:14: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), new result: 0.2789473684210526                    
2025-05-07 16:33:58: BoTorchModel, best RESULT: 0.19999999999999996, finishing jobs, finished 2 jobs                                          
2025-05-07 16:34:23: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                       
2025-05-07 16:34:55: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                               
2025-05-07 16:35:17: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                         
2025-05-07 16:35:39: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1∑1 (2%/50), started new job                                     
2025-05-07 16:36:18: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 16:36:43: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), eval start                                        
2025-05-07 16:37:05: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                  
2025-05-07 16:37:27: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 16:37:54: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.3631578947368421          
2025-05-07 16:38:35: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 16:38:53: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 16:39:17: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 16:39:40: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 16:39:59: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 16:40:19: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.2315789473684211          
2025-05-07 16:40:56: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 16:41:12: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 16:41:34: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 16:41:57: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                  
2025-05-07 16:42:20: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 16:42:44: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.23684210526315785         
2025-05-07 16:43:28: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), new result: 0.3631578947368421                    
2025-05-07 16:44:19: BoTorchModel, best RESULT: 0.19999999999999996, finishing jobs (_get_next_trials), finished 2 jobs                       
2025-05-07 16:44:43: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                       
2025-05-07 16:45:06: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                               
2025-05-07 16:45:28: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                         
2025-05-07 16:45:45: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1∑1 (2%/50), started new job                                     
2025-05-07 16:46:36: BoTorchModel, best RESULT: 0.19999999999999996, pending 1∑1 (2%/50), getting new HP set                                  
2025-05-07 16:46:57: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 16:47:21: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 16:47:45: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 16:48:09: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.22631578947368425         
2025-05-07 16:48:53: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), new result: 0.2421052631578947                    
2025-05-07 16:49:36: BoTorchModel, best RESULT: 0.19999999999999996, finishing jobs (_get_next_trials), finished 2 jobs                       
2025-05-07 16:50:03: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                       
2025-05-07 16:50:27: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                               
2025-05-07 16:50:55: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                         
2025-05-07 16:51:21: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1∑1 (2%/50), started new job                                     
2025-05-07 16:52:19: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 16:52:43: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), eval start                                        
2025-05-07 16:53:02: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                  
2025-05-07 16:53:26: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 16:53:47: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.3421052631578947          
2025-05-07 16:54:40: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 16:55:06: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), getting new HP set                                
2025-05-07 16:55:36: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), eval start                                        
2025-05-07 16:56:01: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                  
2025-05-07 16:56:29: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 16:56:51: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.2947368421052632          
2025-05-07 16:57:40: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 16:58:04: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), getting new HP set                                
2025-05-07 16:58:30: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), eval start                                        
2025-05-07 16:58:56: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                  
2025-05-07 16:59:22: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 16:59:55: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.26315789473684215         
2025-05-07 17:00:39: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), new result: 0.3526315789473684                    
2025-05-07 17:01:30: BoTorchModel, best RESULT: 0.19999999999999996, finishing jobs (_get_next_trials), finished 2 jobs                       
2025-05-07 17:01:50: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                       
2025-05-07 17:02:13: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                               
2025-05-07 17:02:21: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                         
2025-05-07 17:02:32: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1∑1 (2%/50), started new job                                     
2025-05-07 17:02:56: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 17:03:08: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 17:03:16: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 17:03:27: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 17:03:36: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.32105263157894737         
2025-05-07 17:03:58: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 17:04:07: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 17:04:26: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), eval start                                        
2025-05-07 17:04:35: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                  
2025-05-07 17:04:43: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 17:04:54: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.42105263157894735         
2025-05-07 17:05:16: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 17:05:27: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 17:05:38: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 17:05:48: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                  
2025-05-07 17:05:57: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 17:06:05: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.3526315789473684          
2025-05-07 17:06:21: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 17:06:29: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 17:06:42: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 17:06:51: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 17:07:00: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 17:07:08: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.2210526315789474          
2025-05-07 17:07:24: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 17:07:36: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 17:07:48: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 17:07:57: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 17:08:06: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 17:08:14: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.32105263157894737         
2025-05-07 17:08:42: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 17:08:50: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 17:09:03: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), eval start                                        
2025-05-07 17:09:13: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                  
2025-05-07 17:09:27: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 17:09:41: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.31052631578947365         
2025-05-07 17:10:08: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), new result: 0.2947368421052632                    
2025-05-07 17:10:33: BoTorchModel, best RESULT: 0.19999999999999996, finishing jobs (_get_next_trials), finished 2 jobs                       
2025-05-07 17:10:41: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                       
2025-05-07 17:10:58: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                               
2025-05-07 17:11:08: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                         
2025-05-07 17:11:21: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1∑1 (2%/50), started new job                                     
2025-05-07 17:11:43: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 17:11:57: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 17:12:06: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 17:12:24: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 17:12:34: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.20526315789473681         
2025-05-07 17:12:55: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 17:13:03: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 17:13:17: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 17:13:31: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 17:13:44: BoTorchModel, best RESULT: 0.19999999999999996, running/unknown 1/1∑2 (4%/50), started new job                           
2025-05-07 17:13:54: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.22631578947368425         
2025-05-07 17:14:15: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 17:14:30: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 17:14:45: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 17:14:54: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                  
2025-05-07 17:15:02: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 17:15:11: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.2578947368421053          
2025-05-07 17:15:30: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 17:15:39: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 17:15:51: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 17:16:02: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                  
2025-05-07 17:16:11: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 17:16:19: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.2421052631578947          
2025-05-07 17:16:42: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 17:16:51: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 17:17:04: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 17:17:12: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 17:17:20: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 17:17:31: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.22631578947368425         
2025-05-07 17:17:53: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), new result: 0.2210526315789474                      
2025-05-07 17:18:12: BoTorchModel, best RESULT: 0.19999999999999996, finishing jobs (_get_next_trials), finished 2 jobs                       
2025-05-07 17:18:19: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                       
2025-05-07 17:18:32: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                               
2025-05-07 17:18:44: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                         
2025-05-07 17:18:56: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1∑1 (2%/50), started new job                                     
2025-05-07 17:19:15: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 17:19:27: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 17:19:39: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                  
2025-05-07 17:19:51: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 17:20:03: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.32105263157894737         
2025-05-07 17:20:23: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 17:20:32: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 17:20:47: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 17:20:56: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                  
2025-05-07 17:21:07: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 17:21:16: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.3631578947368421          
2025-05-07 17:21:35: BoTorchModel, best RESULT: 0.19999999999999996, pending 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 17:21:48: BoTorchModel, best RESULT: 0.19999999999999996, pending 1∑1 (2%/50), getting new HP set                                  
2025-05-07 17:22:06: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 17:22:14: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 17:22:24: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 17:22:32: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.3631578947368421          
2025-05-07 17:22:53: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 17:23:04: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 17:23:22: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 17:23:33: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 17:23:46: BoTorchModel, best RESULT: 0.19999999999999996, running/unknown 1/1∑2 (4%/50), started new job                           
2025-05-07 17:24:05: BoTorchModel, best RESULT: 0.19999999999999996, running/pending 1/1∑2 (4%/50), getting new HP set                        
2025-05-07 17:24:20: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), eval start                              
2025-05-07 17:24:30: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), starting new job                        
2025-05-07 17:24:39: BoTorchModel, best RESULT: 0.19999999999999996, completed/running/unknown 1/1/1∑3 (6%/50), started new job               
2025-05-07 17:24:48: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/2∑3 (6%/50), new result: 0.23684210526315785         
2025-05-07 17:25:06: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.4052631578947369          
2025-05-07 17:25:25: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), new result: 0.3421052631578947                      
2025-05-07 17:25:42: BoTorchModel, best RESULT: 0.19999999999999996, finishing jobs (_get_next_trials), finished 3 jobs                       
2025-05-07 17:25:50: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                       
2025-05-07 17:26:04: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                               
2025-05-07 17:26:13: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                         
2025-05-07 17:26:25: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1∑1 (2%/50), started new job                                     
2025-05-07 17:26:47: BoTorchModel, best RESULT: 0.19999999999999996, pending 1∑1 (2%/50), getting new HP set                                  
2025-05-07 17:26:59: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 17:27:09: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 17:27:19: BoTorchModel, best RESULT: 0.19999999999999996, running/unknown 1/1∑2 (4%/50), started new job                           
2025-05-07 17:27:27: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.32105263157894737         
2025-05-07 17:27:46: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 17:27:55: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 17:28:10: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 17:28:19: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 17:28:30: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 17:28:40: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.27368421052631575         
2025-05-07 17:28:59: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 17:29:08: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 17:29:22: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 17:29:30: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                  
2025-05-07 17:29:42: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 17:29:51: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.2421052631578947          
2025-05-07 17:30:11: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 17:30:21: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 17:30:36: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 17:30:46: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                  
2025-05-07 17:30:58: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 17:31:10: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.25263157894736843         
2025-05-07 17:31:45: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 17:31:57: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 17:32:12: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 17:32:28: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 17:32:38: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 17:32:48: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.3526315789473684          
2025-05-07 17:33:09: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 17:33:22: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 17:33:38: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 17:33:47: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                  
2025-05-07 17:33:58: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 17:34:07: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.2789473684210526          
2025-05-07 17:34:28: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 17:34:38: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 17:34:52: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 17:35:01: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                  
2025-05-07 17:35:12: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                         
2025-05-07 17:35:23: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.27368421052631575         
2025-05-07 17:35:55: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 17:36:05: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                  
2025-05-07 17:36:22: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                          
2025-05-07 17:36:33: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                    
2025-05-07 17:36:45: BoTorchModel, best RESULT: 0.19999999999999996, running/unknown 1/1∑2 (4%/50), started new job                           
2025-05-07 17:37:08: BoTorchModel, best RESULT: 0.19999999999999996, running 2∑2 (4%/50), getting new HP set                                  
2025-05-07 17:37:25: BoTorchModel, best RESULT: 0.19999999999999996, running 2∑2 (4%/50), eval start                                          
2025-05-07 17:37:36: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), starting new job                        
2025-05-07 17:37:48: BoTorchModel, best RESULT: 0.19999999999999996, completed/running/unknown 1/1/1∑3 (6%/50), started new job               
2025-05-07 17:37:58: BoTorchModel, best RESULT: 0.19999999999999996, completed/running/pending 1/1/1∑3 (6%/50), new result: 0.21052631578947367
2025-05-07 17:38:22: BoTorchModel, best RESULT: 0.19999999999999996, running 2∑2 (4%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 17:38:31: BoTorchModel, best RESULT: 0.19999999999999996, running 2∑2 (4%/50), getting new HP set                                   
2025-05-07 17:38:50: BoTorchModel, best RESULT: 0.19999999999999996, running 2∑2 (4%/50), eval start                                           
2025-05-07 17:39:00: BoTorchModel, best RESULT: 0.19999999999999996, completed 2∑2 (4%/50), starting new job                                   
2025-05-07 17:39:11: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 2/1∑3 (6%/50), started new job                          
2025-05-07 17:39:23: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 2/1∑3 (6%/50), new result: 0.3157894736842105           
2025-05-07 17:39:47: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.2684210526315789           
2025-05-07 17:40:10: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 2 jobs   
2025-05-07 17:40:20: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 17:40:40: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), eval start                                         
2025-05-07 17:40:51: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 17:41:02: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 17:41:13: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.3631578947368421           
2025-05-07 17:41:40: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 17:41:50: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 17:42:06: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), eval start                                         
2025-05-07 17:42:15: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 17:42:26: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 17:42:36: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.2789473684210526           
2025-05-07 17:42:57: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 17:43:06: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 17:43:23: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                           
2025-05-07 17:43:32: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 17:43:43: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 17:43:53: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.20526315789473681          
2025-05-07 17:44:14: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 17:44:24: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 17:44:42: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                           
2025-05-07 17:44:51: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 17:45:02: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 17:45:12: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.24736842105263157          
2025-05-07 17:45:33: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 17:45:43: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 17:45:59: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                           
2025-05-07 17:46:09: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                     
2025-05-07 17:46:20: BoTorchModel, best RESULT: 0.19999999999999996, running/unknown 1/1∑2 (4%/50), started new job                            
2025-05-07 17:46:30: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.3631578947368421           
2025-05-07 17:46:52: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 17:47:02: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 17:47:26: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), eval start                                         
2025-05-07 17:47:35: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 17:47:47: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 17:47:57: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.3631578947368421           
2025-05-07 17:48:18: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 17:48:28: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 17:48:45: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                           
2025-05-07 17:48:54: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 17:49:06: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 17:49:17: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.30000000000000004          
2025-05-07 17:49:38: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 17:49:48: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 17:50:04: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                           
2025-05-07 17:50:14: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                     
2025-05-07 17:50:26: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 17:50:36: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.2947368421052632           
2025-05-07 17:50:58: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 17:51:08: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 17:51:26: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                           
2025-05-07 17:51:36: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 17:51:47: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 17:51:57: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.3526315789473684           
2025-05-07 17:52:19: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 17:52:29: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 17:52:46: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                           
2025-05-07 17:52:56: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                     
2025-05-07 17:53:08: BoTorchModel, best RESULT: 0.19999999999999996, running/unknown 1/1∑2 (4%/50), started new job                            
2025-05-07 17:53:30: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.3526315789473684           
2025-05-07 17:53:52: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing previous jobs (2), finished 1 job          
2025-05-07 17:54:03: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), waiting for 1 job                                    
2025-05-07 17:54:18: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), new result: 0.2947368421052632                       
2025-05-07 17:54:40: BoTorchModel, best RESULT: 0.19999999999999996, waiting for 1 job), finished 1 job                                        
2025-05-07 17:54:50: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                        
2025-05-07 17:55:08: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                                
2025-05-07 17:55:18: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                          
2025-05-07 17:55:29: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1∑1 (2%/50), started new job                                      
2025-05-07 17:55:50: BoTorchModel, best RESULT: 0.19999999999999996, pending 1∑1 (2%/50), getting new HP set                                   
2025-05-07 17:56:06: BoTorchModel, best RESULT: 0.19999999999999996, pending 1∑1 (2%/50), eval start                                           
2025-05-07 17:56:16: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                     
2025-05-07 17:56:27: BoTorchModel, best RESULT: 0.19999999999999996, running/unknown 1/1∑2 (4%/50), started new job                            
2025-05-07 17:56:38: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.3526315789473684           
2025-05-07 17:57:01: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 17:57:11: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 17:57:27: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                           
2025-05-07 17:57:38: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 17:57:49: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 17:57:59: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.31052631578947365          
2025-05-07 17:58:22: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 17:58:32: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 17:58:49: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                           
2025-05-07 17:58:59: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 17:59:11: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 17:59:21: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.2578947368421053           
2025-05-07 17:59:43: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 17:59:54: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 18:00:12: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                           
2025-05-07 18:00:23: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                     
2025-05-07 18:00:34: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 18:00:44: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.28421052631578947          
2025-05-07 18:01:07: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 18:01:17: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 18:01:34: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                           
2025-05-07 18:01:44: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                     
2025-05-07 18:01:55: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 18:02:05: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.3631578947368421           
2025-05-07 18:02:27: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 18:02:38: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 18:02:56: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                           
2025-05-07 18:03:07: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 18:03:18: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 18:03:29: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.34736842105263155          
2025-05-07 18:03:52: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 18:04:01: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 18:04:21: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                           
2025-05-07 18:04:31: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 18:04:43: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 18:04:55: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.3631578947368421           
2025-05-07 18:05:18: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 18:05:27: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 18:05:45: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                           
2025-05-07 18:05:56: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                     
2025-05-07 18:06:08: BoTorchModel, best RESULT: 0.19999999999999996, running/unknown 1/1∑2 (4%/50), started new job                            
2025-05-07 18:06:19: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.24736842105263157          
2025-05-07 18:06:42: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 18:06:52: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 18:07:10: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                           
2025-05-07 18:07:21: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                     
2025-05-07 18:07:33: BoTorchModel, best RESULT: 0.19999999999999996, running/unknown 1/1∑2 (4%/50), started new job                            
2025-05-07 18:07:47: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.3631578947368421           
2025-05-07 18:08:10: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 18:08:21: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 18:08:42: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                           
2025-05-07 18:08:53: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 18:09:04: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 18:09:15: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.20526315789473681          
2025-05-07 18:09:39: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 18:09:49: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 18:10:07: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                           
2025-05-07 18:10:18: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                     
2025-05-07 18:10:29: BoTorchModel, best RESULT: 0.19999999999999996, running/unknown 1/1∑2 (4%/50), started new job                            
2025-05-07 18:10:40: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.25263157894736843          
2025-05-07 18:11:07: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 18:11:18: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 18:11:35: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                           
2025-05-07 18:11:45: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 18:11:56: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 18:12:07: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.2684210526315789           
2025-05-07 18:12:29: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 18:12:40: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 18:13:01: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                           
2025-05-07 18:13:11: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 18:13:23: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 18:13:34: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.21578947368421053          
2025-05-07 18:13:57: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 18:14:07: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 18:14:26: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                           
2025-05-07 18:14:37: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 18:14:48: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 18:14:59: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.3631578947368421           
2025-05-07 18:15:22: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 18:15:33: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 18:15:51: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                           
2025-05-07 18:16:01: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 18:16:13: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 18:16:24: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.26315789473684215          
2025-05-07 18:16:48: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 18:16:59: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 18:17:18: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                           
2025-05-07 18:17:28: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 18:17:41: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 18:17:52: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.34736842105263155          
2025-05-07 18:18:15: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), new result: 0.24736842105263157                    
2025-05-07 18:18:37: BoTorchModel, best RESULT: 0.19999999999999996, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 18:18:47: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                        
2025-05-07 18:19:06: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                                
2025-05-07 18:19:17: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                          
2025-05-07 18:19:29: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1∑1 (2%/50), started new job                                      
2025-05-07 18:19:51: BoTorchModel, best RESULT: 0.19999999999999996, pending 1∑1 (2%/50), getting new HP set                                   
2025-05-07 18:20:10: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                           
2025-05-07 18:20:21: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                     
2025-05-07 18:20:33: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 18:20:45: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.22631578947368425          
2025-05-07 18:21:09: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 18:21:20: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 18:21:39: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                           
2025-05-07 18:21:50: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 18:22:01: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 18:22:13: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.35789473684210527          
2025-05-07 18:22:37: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 18:22:47: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 18:23:06: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                           
2025-05-07 18:23:17: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 18:23:28: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 18:23:39: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.24736842105263157          
2025-05-07 18:24:03: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), new result: 0.2421052631578947                     
2025-05-07 18:24:26: BoTorchModel, best RESULT: 0.19999999999999996, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 18:24:37: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                        
2025-05-07 18:24:57: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                                
2025-05-07 18:25:09: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                          
2025-05-07 18:25:23: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1∑1 (2%/50), started new job                                      
2025-05-07 18:25:47: BoTorchModel, best RESULT: 0.19999999999999996, pending 1∑1 (2%/50), getting new HP set                                   
2025-05-07 18:26:07: BoTorchModel, best RESULT: 0.19999999999999996, pending 1∑1 (2%/50), eval start                                           
2025-05-07 18:26:18: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 18:26:30: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 18:26:41: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.22631578947368425          
2025-05-07 18:27:04: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 18:27:16: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 18:27:35: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                           
2025-05-07 18:27:46: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 18:27:58: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 18:28:09: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.3631578947368421           
2025-05-07 18:28:32: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), new result: 0.2578947368421053                     
2025-05-07 18:28:55: BoTorchModel, best RESULT: 0.19999999999999996, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 18:29:06: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                        
2025-05-07 18:29:28: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                                
2025-05-07 18:29:39: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                          
2025-05-07 18:29:50: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1∑1 (2%/50), started new job                                      
2025-05-07 18:30:14: BoTorchModel, best RESULT: 0.19999999999999996, pending 1∑1 (2%/50), getting new HP set                                   
2025-05-07 18:30:32: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                           
2025-05-07 18:30:43: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), starting new job                                     
2025-05-07 18:30:55: BoTorchModel, best RESULT: 0.19999999999999996, running/unknown 1/1∑2 (4%/50), started new job                            
2025-05-07 18:31:06: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.3631578947368421           
2025-05-07 18:31:30: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 18:31:40: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 18:31:59: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                           
2025-05-07 18:32:10: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 18:32:25: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 18:32:36: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1∑2 (4%/50), new result: 0.3631578947368421           
2025-05-07 18:32:59: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 18:33:10: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 18:33:30: BoTorchModel, best RESULT: 0.19999999999999996, running 1∑1 (2%/50), eval start                                           
2025-05-07 18:33:41: BoTorchModel, best RESULT: 0.19999999999999996, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 18:33:52: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 18:34:04: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1∑2 (4%/50), new result: 0.18947368421052635          
2025-05-07 18:34:27: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), new result: 0.28421052631578947                    
2025-05-07 18:34:51: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 18:35:01: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 18:35:20: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 18:35:31: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 18:35:43: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1∑1 (2%/50), started new job                                      
2025-05-07 18:36:05: BoTorchModel, best RESULT: 0.18947368421052635, pending 1∑1 (2%/50), getting new HP set                                   
2025-05-07 18:36:23: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 18:36:34: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), starting new job                                     
2025-05-07 18:36:46: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 18:36:57: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1∑2 (4%/50), new result: 0.21578947368421053          
2025-05-07 18:37:25: BoTorchModel, best RESULT: 0.18947368421052635, pending 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 18:37:35: BoTorchModel, best RESULT: 0.18947368421052635, pending 1∑1 (2%/50), getting new HP set                                   
2025-05-07 18:37:57: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), eval start                                         
2025-05-07 18:38:08: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 18:38:20: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 18:38:31: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1∑2 (4%/50), new result: 0.35789473684210527          
2025-05-07 18:38:54: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), new result: 0.23684210526315785                    
2025-05-07 18:39:17: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 18:39:27: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 18:39:52: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 18:40:03: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 18:40:15: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1∑1 (2%/50), started new job                                      
2025-05-07 18:40:39: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 18:40:57: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 18:41:09: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 18:41:21: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 18:41:32: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1∑2 (4%/50), new result: 0.19999999999999996          
2025-05-07 18:41:56: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), new result: 0.21578947368421053                    
2025-05-07 18:42:18: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 18:42:29: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 18:42:48: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 18:42:59: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 18:43:11: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1∑1 (2%/50), started new job                                      
2025-05-07 18:43:35: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 18:43:53: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), eval start                                         
2025-05-07 18:44:04: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 18:44:16: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 18:44:28: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1∑2 (4%/50), new result: 0.21052631578947367          
2025-05-07 18:44:51: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), new result: 0.26315789473684215                    
2025-05-07 18:45:15: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 18:45:26: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 18:45:45: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 18:45:56: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 18:46:09: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1∑1 (2%/50), started new job                                      
2025-05-07 18:46:32: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 18:46:51: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 18:47:02: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 18:47:16: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 18:47:27: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1∑2 (4%/50), new result: 0.3052631578947368           
2025-05-07 18:47:52: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), new result: 0.3631578947368421                     
2025-05-07 18:48:16: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 18:48:27: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 18:48:46: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 18:48:57: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 18:49:09: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1∑1 (2%/50), started new job                                      
2025-05-07 18:49:33: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 18:49:51: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), eval start                                         
2025-05-07 18:50:06: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 18:50:18: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 18:50:29: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1∑2 (4%/50), new result: 0.2894736842105263           
2025-05-07 18:50:54: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 18:51:05: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 18:51:26: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 18:51:37: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 18:51:50: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 18:52:02: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1∑2 (4%/50), new result: 0.22631578947368425          
2025-05-07 18:52:25: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), new result: 0.21578947368421053                    
2025-05-07 18:52:52: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 18:53:03: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 18:53:24: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 18:53:35: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 18:53:48: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1∑1 (2%/50), started new job                                      
2025-05-07 18:54:13: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 18:54:32: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 18:54:43: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 18:54:56: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 18:55:07: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1∑2 (4%/50), new result: 0.27368421052631575          
2025-05-07 18:55:31: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), new result: 0.24736842105263157                    
2025-05-07 18:55:55: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 18:56:06: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 18:56:27: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 18:56:38: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 18:56:50: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1∑1 (2%/50), started new job                                      
2025-05-07 18:57:13: BoTorchModel, best RESULT: 0.18947368421052635, pending 1∑1 (2%/50), getting new HP set                                   
2025-05-07 18:57:34: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), eval start                                         
2025-05-07 18:57:45: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 18:57:58: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 18:58:10: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1∑2 (4%/50), new result: 0.20526315789473681          
2025-05-07 18:58:36: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 18:58:47: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 18:59:06: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 18:59:17: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 18:59:30: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 18:59:42: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1∑2 (4%/50), new result: 0.25263157894736843          
2025-05-07 19:00:07: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 19:00:18: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 19:00:39: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 19:00:51: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 19:01:03: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 19:01:15: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1∑2 (4%/50), new result: 0.2210526315789474           
2025-05-07 19:01:41: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 19:01:53: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 19:02:13: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 19:02:24: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 19:02:37: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 19:02:49: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1∑2 (4%/50), new result: 0.3315789473684211           
2025-05-07 19:03:14: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 19:03:25: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 19:03:45: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 19:03:57: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 19:04:09: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 19:04:22: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1∑2 (4%/50), new result: 0.24736842105263157          
2025-05-07 19:04:48: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 19:05:00: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 19:05:20: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 19:05:32: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 19:05:45: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 19:05:58: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1∑2 (4%/50), new result: 0.3157894736842105           
2025-05-07 19:06:24: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 19:06:36: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 19:06:57: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 19:07:08: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 19:07:21: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 19:07:33: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1∑2 (4%/50), new result: 0.2421052631578947           
2025-05-07 19:08:01: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs, finished 1 job                       
2025-05-07 19:08:13: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), new result: 0.33684210526315794                      
2025-05-07 19:08:38: BoTorchModel, best RESULT: 0.18947368421052635, finishing previous jobs (1), finished 1 job                               
2025-05-07 19:08:52: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 19:09:15: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 19:09:27: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 19:09:39: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1∑1 (2%/50), started new job                                      
2025-05-07 19:10:06: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), getting new HP set                                 
2025-05-07 19:10:25: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), eval start                                         
2025-05-07 19:10:38: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 19:10:50: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 19:11:03: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1∑2 (4%/50), new result: 0.24736842105263157          
2025-05-07 19:11:31: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 19:11:43: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 19:12:07: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 19:12:20: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 19:12:34: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 19:12:46: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1∑2 (4%/50), new result: 0.2315789473684211           
2025-05-07 19:13:12: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), new result: 0.2421052631578947                     
2025-05-07 19:13:37: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 19:13:49: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 19:14:14: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 19:14:25: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 19:14:39: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1∑1 (2%/50), started new job                                      
2025-05-07 19:15:04: BoTorchModel, best RESULT: 0.18947368421052635, pending 1∑1 (2%/50), getting new HP set                                   
2025-05-07 19:15:27: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), eval start                                         
2025-05-07 19:15:40: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 19:15:55: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 19:16:09: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1∑2 (4%/50), new result: 0.2210526315789474           
2025-05-07 19:16:40: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), new result: 0.2421052631578947                     
2025-05-07 19:17:05: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 19:17:16: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 19:17:43: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 19:17:55: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 19:18:08: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1∑1 (2%/50), started new job                                      
2025-05-07 19:18:33: BoTorchModel, best RESULT: 0.18947368421052635, pending 1∑1 (2%/50), getting new HP set                                   
2025-05-07 19:18:54: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 19:19:06: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), starting new job                                     
2025-05-07 19:19:19: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 19:19:31: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1∑2 (4%/50), new result: 0.20526315789473681          
2025-05-07 19:19:59: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 19:20:10: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 19:20:30: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 19:20:42: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 19:20:56: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 19:21:08: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1∑2 (4%/50), new result: 0.3263157894736842           
2025-05-07 19:21:35: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 19:21:46: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 19:22:09: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 19:22:21: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 19:22:34: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 19:22:46: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1∑2 (4%/50), new result: 0.3631578947368421           
2025-05-07 19:23:11: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), new result: 0.2421052631578947                     
2025-05-07 19:23:37: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 19:23:48: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 19:24:10: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 19:24:22: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 19:24:35: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1∑1 (2%/50), started new job                                      
2025-05-07 19:25:01: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 19:25:20: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), eval start                                         
2025-05-07 19:25:31: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 19:25:45: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 19:25:57: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1∑2 (4%/50), new result: 0.31052631578947365          
2025-05-07 19:26:23: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), new result: 0.3315789473684211                     
2025-05-07 19:26:48: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 19:26:59: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 19:27:23: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 19:27:35: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 19:27:48: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1∑1 (2%/50), started new job                                      
2025-05-07 19:28:15: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 19:28:36: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 19:28:48: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 19:29:01: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 19:29:13: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1∑2 (4%/50), new result: 0.2684210526315789           
2025-05-07 19:29:39: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 19:29:50: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 19:30:09: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 19:30:21: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 19:30:33: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 19:30:45: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1∑2 (4%/50), new result: 0.2421052631578947           
2025-05-07 19:31:11: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 19:31:22: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 19:31:42: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 19:31:54: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 19:32:07: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 19:32:18: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1∑2 (4%/50), new result: 0.3052631578947368           
2025-05-07 19:32:44: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 19:32:55: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 19:33:18: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 19:33:30: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 19:33:43: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 19:33:55: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1∑2 (4%/50), new result: 0.24736842105263157          
2025-05-07 19:34:21: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 19:34:32: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 19:34:57: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), eval start                                         
2025-05-07 19:35:08: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 19:35:21: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 19:35:33: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1∑2 (4%/50), new result: 0.3315789473684211           
2025-05-07 19:35:59: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 19:36:10: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 19:36:31: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 19:36:43: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 19:36:56: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 19:37:07: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1∑2 (4%/50), new result: 0.2421052631578947           
2025-05-07 19:37:34: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 19:37:45: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 19:38:06: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 19:38:18: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 19:38:31: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 19:38:42: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1∑2 (4%/50), new result: 0.32105263157894737          
2025-05-07 19:39:09: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 19:39:20: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 19:39:41: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 19:39:53: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 19:40:05: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 19:40:17: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1∑2 (4%/50), new result: 0.31052631578947365          
2025-05-07 19:40:44: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 19:40:55: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 19:41:15: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 19:41:27: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 19:41:40: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 19:41:51: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1∑2 (4%/50), new result: 0.25263157894736843          
2025-05-07 19:42:18: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 19:42:29: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 19:42:49: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 19:43:01: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 19:43:13: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 19:43:25: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1∑2 (4%/50), new result: 0.23684210526315785          
2025-05-07 19:43:51: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 19:44:03: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 19:44:24: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 19:44:36: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 19:44:52: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 19:45:04: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1∑2 (4%/50), new result: 0.2789473684210526           
2025-05-07 19:45:30: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), new result: 0.21052631578947367                      
2025-05-07 19:45:55: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 19:46:07: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 19:46:28: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 19:46:40: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 19:46:54: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1∑1 (2%/50), started new job                                      
2025-05-07 19:47:20: BoTorchModel, best RESULT: 0.18947368421052635, pending 1∑1 (2%/50), getting new HP set                                   
2025-05-07 19:47:41: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), eval start                                         
2025-05-07 19:47:53: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 19:48:06: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 19:48:18: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1∑2 (4%/50), new result: 0.3631578947368421           
2025-05-07 19:48:44: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), new result: 0.21052631578947367                    
2025-05-07 19:49:09: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 19:49:21: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 19:49:56: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 19:50:08: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 19:50:20: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1∑1 (2%/50), started new job                                      
2025-05-07 19:50:46: BoTorchModel, best RESULT: 0.18947368421052635, pending 1∑1 (2%/50), getting new HP set                                   
2025-05-07 19:51:09: BoTorchModel, best RESULT: 0.18947368421052635, pending 1∑1 (2%/50), eval start                                           
2025-05-07 19:51:22: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 19:51:35: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 19:51:48: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1∑2 (4%/50), new result: 0.2947368421052632           
2025-05-07 19:52:15: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 19:52:27: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 19:52:50: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 19:53:02: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 19:53:16: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 19:53:29: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1∑2 (4%/50), new result: 0.23684210526315785          
2025-05-07 19:53:55: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), new result: 0.27368421052631575                    
2025-05-07 19:54:21: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 19:54:33: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 19:54:56: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 19:55:08: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 19:55:22: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1∑1 (2%/50), started new job                                      
2025-05-07 19:55:48: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 19:56:12: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 19:56:24: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 19:56:38: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 19:56:51: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1∑2 (4%/50), new result: 0.2789473684210526           
2025-05-07 19:57:16: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), new result: 0.3631578947368421                     
2025-05-07 19:57:43: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 19:57:56: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 19:58:20: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 19:58:31: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 19:58:45: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1∑1 (2%/50), started new job                                      
2025-05-07 19:59:11: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 19:59:35: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 19:59:47: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 20:00:01: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 20:00:13: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1∑2 (4%/50), new result: 0.21578947368421053          
2025-05-07 20:00:41: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 20:00:53: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 20:01:16: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 20:01:28: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 20:01:42: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 20:01:55: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1∑2 (4%/50), new result: 0.27368421052631575          
2025-05-07 20:02:22: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 20:02:35: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 20:02:57: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 20:03:09: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 20:03:23: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 20:03:36: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1∑2 (4%/50), new result: 0.27368421052631575          
2025-05-07 20:04:06: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 20:04:19: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 20:04:41: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 20:04:53: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 20:05:07: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 20:05:20: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1∑2 (4%/50), new result: 0.21578947368421053          
2025-05-07 20:05:47: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), new result: 0.2947368421052632                       
2025-05-07 20:06:14: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 20:06:26: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 20:06:51: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 20:07:03: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 20:07:17: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1∑1 (2%/50), started new job                                      
2025-05-07 20:07:44: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 20:08:08: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 20:08:20: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 20:08:34: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 20:08:47: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1∑2 (4%/50), new result: 0.3631578947368421           
2025-05-07 20:09:14: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), new result: 0.21578947368421053                    
2025-05-07 20:09:40: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 20:09:53: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 20:10:19: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 20:10:32: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 20:10:46: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1∑1 (2%/50), started new job                                      
2025-05-07 20:11:13: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), getting new HP set                                 
2025-05-07 20:11:35: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), eval start                                         
2025-05-07 20:11:47: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 20:12:01: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 20:12:14: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1∑2 (4%/50), new result: 0.30000000000000004          
2025-05-07 20:12:42: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 20:12:54: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 20:13:19: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 20:13:33: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 20:13:47: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 20:14:00: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1∑2 (4%/50), new result: 0.2421052631578947           
2025-05-07 20:14:28: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 20:14:42: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 20:15:05: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 20:15:18: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 20:15:32: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 20:15:46: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1∑2 (4%/50), new result: 0.24736842105263157          
2025-05-07 20:16:14: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), new result: 0.24736842105263157                    
2025-05-07 20:16:41: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 20:16:53: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 20:17:19: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 20:17:31: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 20:17:45: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1∑1 (2%/50), started new job                                      
2025-05-07 20:18:12: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 20:18:34: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 20:18:47: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 20:19:01: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 20:19:14: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1∑2 (4%/50), new result: 0.2894736842105263           
2025-05-07 20:19:42: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 20:19:55: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 20:20:19: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 20:20:32: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 20:20:45: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 20:20:58: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1∑2 (4%/50), new result: 0.22631578947368425          
2025-05-07 20:21:26: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 20:21:38: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 20:22:04: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), eval start                                         
2025-05-07 20:22:17: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 20:22:30: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 20:22:44: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1∑2 (4%/50), new result: 0.2315789473684211           
2025-05-07 20:23:15: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), new result: 0.21578947368421053                      
2025-05-07 20:23:42: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 20:23:54: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 20:24:20: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 20:24:38: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 20:24:53: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1∑1 (2%/50), started new job                                      
2025-05-07 20:25:21: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 20:25:45: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 20:25:58: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 20:26:11: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 20:26:24: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1∑2 (4%/50), new result: 0.2421052631578947           
2025-05-07 20:26:53: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 20:27:05: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 20:27:29: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 20:27:42: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), starting new job                                     
2025-05-07 20:27:56: BoTorchModel, best RESULT: 0.18947368421052635, running/unknown 1/1∑2 (4%/50), started new job                            
2025-05-07 20:28:27: BoTorchModel, best RESULT: 0.18947368421052635, running 2∑2 (4%/50), getting new HP set                                   
2025-05-07 20:28:52: BoTorchModel, best RESULT: 0.18947368421052635, running 2∑2 (4%/50), eval start                                           
2025-05-07 20:29:04: BoTorchModel, best RESULT: 0.18947368421052635, running 2∑2 (4%/50), starting new job                                     
2025-05-07 20:29:19: BoTorchModel, best RESULT: 0.18947368421052635, running/unknown 2/1∑3 (6%/50), started new job                            
2025-05-07 20:29:53: BoTorchModel, best RESULT: 0.18947368421052635, running 3∑3 (6%/50), getting new HP set                                   
2025-05-07 20:30:17: BoTorchModel, best RESULT: 0.18947368421052635, running 3∑3 (6%/50), eval start                                           
2025-05-07 20:30:30: BoTorchModel, best RESULT: 0.18947368421052635, running 3∑3 (6%/50), starting new job                                     
2025-05-07 20:30:45: BoTorchModel, best RESULT: 0.18947368421052635, running/unknown 3/1∑4 (8%/50), started new job                            
2025-05-07 20:31:21: BoTorchModel, best RESULT: 0.18947368421052635, running 4∑4 (8%/50), waiting for 4 jobs                                   
2025-05-07 20:31:43: BoTorchModel, best RESULT: 0.18947368421052635, running 4∑4 (8%/50), waiting for 4 jobs                                   
2025-05-07 20:32:05: BoTorchModel, best RESULT: 0.18947368421052635, running 4∑4 (8%/50), waiting for 4 jobs                                   
2025-05-07 20:32:28: BoTorchModel, best RESULT: 0.18947368421052635, running 4∑4 (8%/50), waiting for 4 jobs                                   
2025-05-07 20:32:51: BoTorchModel, best RESULT: 0.18947368421052635, running 4∑4 (8%/50), waiting for 4 jobs                                   
2025-05-07 20:33:17: BoTorchModel, best RESULT: 0.18947368421052635, running 4∑4 (8%/50), waiting for 4 jobs                                   
2025-05-07 20:33:39: BoTorchModel, best RESULT: 0.18947368421052635, running 4∑4 (8%/50), waiting for 4 jobs                                   
2025-05-07 20:34:02: BoTorchModel, best RESULT: 0.18947368421052635, running 4∑4 (8%/50), waiting for 4 jobs                                   
2025-05-07 20:34:25: BoTorchModel, best RESULT: 0.18947368421052635, running 4∑4 (8%/50), waiting for 4 jobs                                   
2025-05-07 20:34:50: BoTorchModel, best RESULT: 0.18947368421052635, running 4∑4 (8%/50), waiting for 4 jobs                                   
2025-05-07 20:35:13: BoTorchModel, best RESULT: 0.18947368421052635, running 4∑4 (8%/50), waiting for 4 jobs                                   
2025-05-07 20:35:36: BoTorchModel, best RESULT: 0.18947368421052635, running 4∑4 (8%/50), waiting for 4 jobs                                   
2025-05-07 20:35:59: BoTorchModel, best RESULT: 0.18947368421052635, running 4∑4 (8%/50), waiting for 4 jobs                                   
2025-05-07 20:36:21: BoTorchModel, best RESULT: 0.18947368421052635, running 4∑4 (8%/50), waiting for 4 jobs                                   
2025-05-07 20:36:44: BoTorchModel, best RESULT: 0.18947368421052635, running 4∑4 (8%/50), waiting for 4 jobs                                   
2025-05-07 20:37:07: BoTorchModel, best RESULT: 0.18947368421052635, running 4∑4 (8%/50), waiting for 4 jobs                                   
2025-05-07 20:37:31: BoTorchModel, best RESULT: 0.18947368421052635, running 4∑4 (8%/50), waiting for 4 jobs                                   
2025-05-07 20:37:54: BoTorchModel, best RESULT: 0.18947368421052635, running 4∑4 (8%/50), waiting for 4 jobs                                   
2025-05-07 20:38:18: BoTorchModel, best RESULT: 0.18947368421052635, running 4∑4 (8%/50), waiting for 4 jobs                                   
2025-05-07 20:38:42: BoTorchModel, best RESULT: 0.18947368421052635, running 4∑4 (8%/50), waiting for 4 jobs                                   
2025-05-07 20:39:07: BoTorchModel, best RESULT: 0.18947368421052635, running 4∑4 (8%/50), waiting for 4 jobs                                   
2025-05-07 20:39:30: BoTorchModel, best RESULT: 0.18947368421052635, running 4∑4 (8%/50), waiting for 4 jobs                                   
2025-05-07 20:39:50: BoTorchModel, best RESULT: 0.18947368421052635, running 4∑4 (8%/50), new result: 0.26315789473684215                      
2025-05-07 20:40:20: BoTorchModel, best RESULT: 0.18947368421052635, running 3∑3 (6%/50), new result: 0.2894736842105263                       
2025-05-07 20:40:49: BoTorchModel, best RESULT: 0.18947368421052635, running 2∑2 (4%/50), new result: 0.3631578947368421                       
2025-05-07 20:41:19: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), new result: 0.2684210526315789                       
2025-05-07 20:41:51: BoTorchModel, best RESULT: 0.18947368421052635, waiting for 4 jobs, finished 4 jobs                                       
2025-05-07 20:42:07: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 20:42:34: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 20:42:48: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 20:43:05: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1∑1 (2%/50), started new job                                      
2025-05-07 20:43:36: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 20:44:03: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 20:44:18: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 20:44:34: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 20:44:48: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1∑2 (4%/50), new result: 0.22631578947368425          
2025-05-07 20:45:21: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 20:45:35: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 20:46:01: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 20:46:16: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 20:46:32: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 20:46:49: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1∑2 (4%/50), new result: 0.2421052631578947           
2025-05-07 20:47:26: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 20:47:42: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 20:48:11: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), eval start                                         
2025-05-07 20:48:28: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 20:48:45: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 20:49:00: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1∑2 (4%/50), new result: 0.3631578947368421           
2025-05-07 20:49:35: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 20:49:51: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 20:50:25: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), eval start                                         
2025-05-07 20:50:40: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 20:50:58: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 20:51:16: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1∑2 (4%/50), new result: 0.32105263157894737          
2025-05-07 20:51:51: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), new result: 0.2789473684210526                     
2025-05-07 20:52:28: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 20:52:44: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 20:53:15: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 20:53:31: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 20:53:50: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1∑1 (2%/50), started new job                                      
2025-05-07 20:54:24: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 20:54:54: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 20:55:11: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 20:55:29: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 20:55:45: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1∑2 (4%/50), new result: 0.21578947368421053          
2025-05-07 20:56:23: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 20:56:40: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 20:57:09: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 20:57:26: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), starting new job                                     
2025-05-07 20:57:44: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 20:58:02: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1∑2 (4%/50), new result: 0.26315789473684215          
2025-05-07 20:58:39: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 20:58:56: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 20:59:30: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 20:59:49: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 21:00:05: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 21:00:21: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1∑2 (4%/50), new result: 0.3631578947368421           
2025-05-07 21:00:56: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 21:01:11: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 21:01:44: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 21:01:59: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 21:02:15: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 21:02:30: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1∑2 (4%/50), new result: 0.28421052631578947          
2025-05-07 21:03:00: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), new result: 0.24736842105263157                    
2025-05-07 21:03:32: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 21:03:47: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 21:04:15: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 21:04:30: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 21:04:47: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1∑1 (2%/50), started new job                                      
2025-05-07 21:05:19: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 21:05:49: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 21:06:05: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 21:06:21: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 21:06:36: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1∑2 (4%/50), new result: 0.26315789473684215          
2025-05-07 21:07:08: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 21:07:22: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 21:07:51: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 21:08:05: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 21:08:22: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 21:08:38: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1∑2 (4%/50), new result: 0.3631578947368421           
2025-05-07 21:09:11: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 21:09:26: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 21:09:53: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 21:10:07: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 21:10:22: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 21:10:37: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1∑2 (4%/50), new result: 0.3052631578947368           
2025-05-07 21:11:08: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), new result: 0.24736842105263157                    
2025-05-07 21:11:40: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 21:11:56: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 21:12:26: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 21:12:45: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 21:13:07: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1∑1 (2%/50), started new job                                      
2025-05-07 21:13:47: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 21:14:25: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), eval start                                         
2025-05-07 21:14:42: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 21:14:59: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 21:15:16: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1∑2 (4%/50), new result: 0.33684210526315794          
2025-05-07 21:15:53: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 21:16:10: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 21:16:39: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 21:16:55: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 21:17:13: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 21:17:33: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1∑2 (4%/50), new result: 0.24736842105263157          
2025-05-07 21:18:08: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 21:18:26: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 21:18:57: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 21:19:13: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 21:19:31: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 21:19:48: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1∑2 (4%/50), new result: 0.21052631578947367          
2025-05-07 21:20:24: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 21:20:40: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 21:21:08: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 21:21:24: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 21:21:43: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 21:22:03: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1∑2 (4%/50), new result: 0.30000000000000004          
2025-05-07 21:22:37: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), new result: 0.23684210526315785                    
2025-05-07 21:23:11: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 21:23:28: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 21:24:00: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 21:24:17: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 21:24:37: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1∑1 (2%/50), started new job                                      
2025-05-07 21:25:15: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 21:26:00: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), eval start                                         
2025-05-07 21:26:17: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 21:26:35: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 21:26:53: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1∑2 (4%/50), new result: 0.2210526315789474           
2025-05-07 21:27:30: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), new result: 0.2789473684210526                     
2025-05-07 21:28:06: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 21:28:21: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 21:28:52: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 21:29:09: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 21:29:27: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1∑1 (2%/50), started new job                                      
2025-05-07 21:30:07: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 21:30:38: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 21:30:57: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 21:31:17: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 21:31:35: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1∑2 (4%/50), new result: 0.27368421052631575          
2025-05-07 21:32:16: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 21:32:35: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 21:33:10: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 21:33:29: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 21:33:51: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 21:34:10: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1∑2 (4%/50), new result: 0.2894736842105263           
2025-05-07 21:34:53: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 21:35:10: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 21:35:44: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 21:36:01: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 21:36:20: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 21:36:40: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1∑2 (4%/50), new result: 0.26315789473684215          
2025-05-07 21:37:20: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 21:37:43: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 21:38:15: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 21:38:32: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), starting new job                                     
2025-05-07 21:38:52: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 21:39:10: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1∑2 (4%/50), new result: 0.2210526315789474           
2025-05-07 21:39:48: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 21:40:08: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 21:40:38: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 21:41:00: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 21:41:20: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 21:41:37: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1∑2 (4%/50), new result: 0.30000000000000004          
2025-05-07 21:42:13: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 21:42:30: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 21:43:02: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 21:43:22: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 21:43:40: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 21:43:57: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1∑2 (4%/50), new result: 0.27368421052631575          
2025-05-07 21:44:33: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), new result: 0.2684210526315789                     
2025-05-07 21:45:10: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 21:45:27: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 21:46:04: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 21:46:28: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 21:46:48: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1∑1 (2%/50), started new job                                      
2025-05-07 21:47:25: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 21:47:54: BoTorchModel, best RESULT: 0.18947368421052635, running 1∑1 (2%/50), eval start                                           
2025-05-07 21:48:12: BoTorchModel, best RESULT: 0.18947368421052635, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 21:48:32: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 21:48:54: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1∑2 (4%/50), new result: 0.16842105263157892          
2025-05-07 21:49:32: BoTorchModel, best RESULT: 0.16842105263157892, completed 1∑1 (2%/50), new result: 0.3263157894736842                     
2025-05-07 21:50:12: BoTorchModel, best RESULT: 0.16842105263157892, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 21:50:32: BoTorchModel, best RESULT: 0.16842105263157892, getting new HP set                                                        
2025-05-07 21:51:15: BoTorchModel, best RESULT: 0.16842105263157892, eval start                                                                
2025-05-07 21:51:33: BoTorchModel, best RESULT: 0.16842105263157892, starting new job                                                          
2025-05-07 21:51:51: BoTorchModel, best RESULT: 0.16842105263157892, unknown 1∑1 (2%/50), started new job                                      
2025-05-07 21:52:29: BoTorchModel, best RESULT: 0.16842105263157892, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 21:53:00: BoTorchModel, best RESULT: 0.16842105263157892, running 1∑1 (2%/50), eval start                                           
2025-05-07 21:53:19: BoTorchModel, best RESULT: 0.16842105263157892, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 21:53:37: BoTorchModel, best RESULT: 0.16842105263157892, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 21:53:55: BoTorchModel, best RESULT: 0.16842105263157892, completed/pending 1/1∑2 (4%/50), new result: 0.35789473684210527          
2025-05-07 21:54:33: BoTorchModel, best RESULT: 0.16842105263157892, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 21:54:50: BoTorchModel, best RESULT: 0.16842105263157892, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 21:55:21: BoTorchModel, best RESULT: 0.16842105263157892, running 1∑1 (2%/50), eval start                                           
2025-05-07 21:55:38: BoTorchModel, best RESULT: 0.16842105263157892, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 21:55:57: BoTorchModel, best RESULT: 0.16842105263157892, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 21:56:16: BoTorchModel, best RESULT: 0.16842105263157892, completed/running 1/1∑2 (4%/50), new result: 0.25263157894736843          
2025-05-07 21:56:53: BoTorchModel, best RESULT: 0.16842105263157892, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 21:57:09: BoTorchModel, best RESULT: 0.16842105263157892, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 21:57:45: BoTorchModel, best RESULT: 0.16842105263157892, running 1∑1 (2%/50), eval start                                           
2025-05-07 21:58:02: BoTorchModel, best RESULT: 0.16842105263157892, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 21:58:20: BoTorchModel, best RESULT: 0.16842105263157892, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 21:58:40: BoTorchModel, best RESULT: 0.16842105263157892, completed/running 1/1∑2 (4%/50), new result: 0.3631578947368421           
2025-05-07 21:59:15: BoTorchModel, best RESULT: 0.16842105263157892, completed 1∑1 (2%/50), new result: 0.23684210526315785                    
2025-05-07 21:59:52: BoTorchModel, best RESULT: 0.16842105263157892, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 22:00:07: BoTorchModel, best RESULT: 0.16842105263157892, getting new HP set                                                        
2025-05-07 22:00:56: BoTorchModel, best RESULT: 0.16842105263157892, eval start                                                                
2025-05-07 22:01:15: BoTorchModel, best RESULT: 0.16842105263157892, starting new job                                                          
2025-05-07 22:01:35: BoTorchModel, best RESULT: 0.16842105263157892, unknown 1∑1 (2%/50), started new job                                      
2025-05-07 22:02:12: BoTorchModel, best RESULT: 0.16842105263157892, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 22:02:43: BoTorchModel, best RESULT: 0.16842105263157892, running 1∑1 (2%/50), eval start                                           
2025-05-07 22:02:59: BoTorchModel, best RESULT: 0.16842105263157892, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 22:03:15: BoTorchModel, best RESULT: 0.16842105263157892, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 22:03:33: BoTorchModel, best RESULT: 0.16842105263157892, completed/pending 1/1∑2 (4%/50), new result: 0.3631578947368421           
2025-05-07 22:04:07: BoTorchModel, best RESULT: 0.16842105263157892, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 22:04:23: BoTorchModel, best RESULT: 0.16842105263157892, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 22:04:55: BoTorchModel, best RESULT: 0.16842105263157892, running 1∑1 (2%/50), eval start                                           
2025-05-07 22:05:12: BoTorchModel, best RESULT: 0.16842105263157892, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 22:05:29: BoTorchModel, best RESULT: 0.16842105263157892, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 22:05:48: BoTorchModel, best RESULT: 0.16842105263157892, completed/pending 1/1∑2 (4%/50), new result: 0.2894736842105263           
2025-05-07 22:06:24: BoTorchModel, best RESULT: 0.16842105263157892, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 22:06:40: BoTorchModel, best RESULT: 0.16842105263157892, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 22:07:19: BoTorchModel, best RESULT: 0.16842105263157892, completed 1∑1 (2%/50), eval start                                         
2025-05-07 22:07:37: BoTorchModel, best RESULT: 0.16842105263157892, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 22:07:55: BoTorchModel, best RESULT: 0.16842105263157892, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 22:08:14: BoTorchModel, best RESULT: 0.16842105263157892, completed/running 1/1∑2 (4%/50), new result: 0.30000000000000004          
2025-05-07 22:08:48: BoTorchModel, best RESULT: 0.16842105263157892, completed 1∑1 (2%/50), new result: 0.2578947368421053                     
2025-05-07 22:09:30: BoTorchModel, best RESULT: 0.16842105263157892, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 22:09:50: BoTorchModel, best RESULT: 0.16842105263157892, getting new HP set                                                        
2025-05-07 22:10:28: BoTorchModel, best RESULT: 0.16842105263157892, eval start                                                                
2025-05-07 22:10:47: BoTorchModel, best RESULT: 0.16842105263157892, starting new job                                                          
2025-05-07 22:11:06: BoTorchModel, best RESULT: 0.16842105263157892, unknown 1∑1 (2%/50), started new job                                      
2025-05-07 22:11:52: BoTorchModel, best RESULT: 0.16842105263157892, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 22:12:29: BoTorchModel, best RESULT: 0.16842105263157892, running 1∑1 (2%/50), eval start                                           
2025-05-07 22:12:49: BoTorchModel, best RESULT: 0.16842105263157892, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 22:13:09: BoTorchModel, best RESULT: 0.16842105263157892, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 22:13:29: BoTorchModel, best RESULT: 0.16842105263157892, completed/running 1/1∑2 (4%/50), new result: 0.26315789473684215          
2025-05-07 22:14:11: BoTorchModel, best RESULT: 0.16842105263157892, completed 1∑1 (2%/50), new result: 0.2789473684210526                     
2025-05-07 22:14:51: BoTorchModel, best RESULT: 0.16842105263157892, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 22:15:15: BoTorchModel, best RESULT: 0.16842105263157892, getting new HP set                                                        
2025-05-07 22:16:00: BoTorchModel, best RESULT: 0.16842105263157892, eval start                                                                
2025-05-07 22:16:25: BoTorchModel, best RESULT: 0.16842105263157892, starting new job                                                          
2025-05-07 22:16:50: BoTorchModel, best RESULT: 0.16842105263157892, unknown 1∑1 (2%/50), started new job                                      
2025-05-07 22:17:37: BoTorchModel, best RESULT: 0.16842105263157892, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 22:18:14: BoTorchModel, best RESULT: 0.16842105263157892, completed 1∑1 (2%/50), eval start                                         
2025-05-07 22:18:32: BoTorchModel, best RESULT: 0.16842105263157892, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 22:18:52: BoTorchModel, best RESULT: 0.16842105263157892, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 22:19:11: BoTorchModel, best RESULT: 0.16842105263157892, completed/running 1/1∑2 (4%/50), new result: 0.2947368421052632           
2025-05-07 22:19:49: BoTorchModel, best RESULT: 0.16842105263157892, completed 1∑1 (2%/50), new result: 0.3631578947368421                     
2025-05-07 22:20:28: BoTorchModel, best RESULT: 0.16842105263157892, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 22:20:51: BoTorchModel, best RESULT: 0.16842105263157892, getting new HP set                                                        
2025-05-07 22:21:32: BoTorchModel, best RESULT: 0.16842105263157892, eval start                                                                
2025-05-07 22:21:50: BoTorchModel, best RESULT: 0.16842105263157892, starting new job                                                          
2025-05-07 22:22:09: BoTorchModel, best RESULT: 0.16842105263157892, unknown 1∑1 (2%/50), started new job                                      
2025-05-07 22:22:47: BoTorchModel, best RESULT: 0.16842105263157892, pending 1∑1 (2%/50), getting new HP set                                   
2025-05-07 22:23:19: BoTorchModel, best RESULT: 0.16842105263157892, running 1∑1 (2%/50), eval start                                           
2025-05-07 22:23:36: BoTorchModel, best RESULT: 0.16842105263157892, running 1∑1 (2%/50), starting new job                                     
2025-05-07 22:23:55: BoTorchModel, best RESULT: 0.16842105263157892, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 22:24:13: BoTorchModel, best RESULT: 0.16842105263157892, completed/running 1/1∑2 (4%/50), new result: 0.26315789473684215          
2025-05-07 22:24:56: BoTorchModel, best RESULT: 0.16842105263157892, running 1∑1 (2%/50), new result: 0.1947368421052632                       
2025-05-07 22:25:42: BoTorchModel, best RESULT: 0.16842105263157892, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 22:26:01: BoTorchModel, best RESULT: 0.16842105263157892, getting new HP set                                                        
2025-05-07 22:26:40: BoTorchModel, best RESULT: 0.16842105263157892, eval start                                                                
2025-05-07 22:26:58: BoTorchModel, best RESULT: 0.16842105263157892, starting new job                                                          
2025-05-07 22:27:17: BoTorchModel, best RESULT: 0.16842105263157892, unknown 1∑1 (2%/50), started new job                                      
2025-05-07 22:27:58: BoTorchModel, best RESULT: 0.16842105263157892, running 1∑1 (2%/50), getting new HP set                                   
2025-05-07 22:28:35: BoTorchModel, best RESULT: 0.16842105263157892, running 1∑1 (2%/50), eval start                                           
2025-05-07 22:28:56: BoTorchModel, best RESULT: 0.16842105263157892, completed 1∑1 (2%/50), starting new job                                   
2025-05-07 22:29:16: BoTorchModel, best RESULT: 0.16842105263157892, completed/unknown 1/1∑2 (4%/50), started new job                          
2025-05-07 22:29:35: BoTorchModel, best RESULT: 0.16842105263157892, completed/pending 1/1∑2 (4%/50), new result: 0.2684210526315789           
2025-05-07 22:30:19: BoTorchModel, best RESULT: 0.16842105263157892, running 1∑1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    

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timestamp,ram_usage_mb,cpu_usage_percent
1746613817,622.0859375,14.0
1746613821,622.34375,14.0
1746613824,622.34375,14.0
1746613824,622.34375,16.7
1746613824,622.34375,13.3
1746613824,622.34375,13.6
1746613824,622.34375,16.7
1746615675,647.9921875,14.1
1746615675,647.9921875,14.1
1746615675,647.9921875,14.6
1746615675,647.9921875,13.0
1746619675,708.21875,12.8
1746619675,708.21875,7.2
1746619675,708.21875,7.5
1746619675,708.21875,3.8
1746628462,726.45703125,7.7
1746628462,726.45703125,9.1
1746628462,726.45703125,8.7
1746628462,726.45703125,13.3
1746633243,752.13671875,11.6
1746633243,752.13671875,17.4
1746633243,752.13671875,21.1
1746633243,752.13671875,21.7
1746637730,765.0546875,20.4
1746637730,765.0546875,21.2
1746637730,765.0546875,23.5
1746637730,765.0546875,23.3
1746642681,786.328125,18.1
1746642681,786.328125,15.4
1746642681,786.328125,16.7
1746642681,786.328125,17.4

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Correlation Heatmap Explanation

This is a heatmap that visualizes the correlation between numerical columns in a dataset. The values represented in the heatmap show the strength and direction of relationships between different variables.

How It Works

The heatmap uses a matrix to represent correlations between each pair of numerical columns. The calculation behind this is based on the concept of "correlation," which measures how strongly two variables are related. A correlation can be positive, negative, or zero:

• Positive correlation: Both variables increase or decrease together (e.g., if the temperature rises, ice cream sales increase).
• Negative correlation: As one variable increases, the other decreases (e.g., as the price of a product rises, the demand for it decreases).
• Zero correlation: There is no relationship between the two variables (e.g., height and shoe size might show zero correlation in some contexts).

Color Scale: Yellow to Purple (Viridis)

The heatmap uses a color scale called "Viridis," which ranges from yellow to purple. Here's what the colors represent:

• Yellow (brightest): A strong positive correlation (close to +1). This indicates that as one variable increases, the other increases in a very predictable manner.
• Green: A moderate positive correlation. Variables are still positively related, but the relationship is not as strong.
• Blue: A weak or near-zero correlation. There is a small or no discernible relationship between the variables.
• Purple (darkest): A strong negative correlation (close to -1). This indicates that as one variable increases, the other decreases in a very predictable manner.

What the Heatmap Shows

In the heatmap, each cell represents the correlation between two numerical columns. The color of the cell is determined by the correlation coefficient: from yellow for strong positive correlations, through green and blue for weaker correlations, to purple for strong negative correlations.

•  Job-Infos
•  Main-Log
•  Debug-Logs
•  Single Logs

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				text-decoration: none;
				font-size: 16px;
				font-weight: bold;
				border-radius: 6px;
				border: 2px solid #0056b3;
				text-align: center;
				transition: all 0.3s ease-in-out;
			}
			
			.top_link:hover {
				background-color: #0056b3;
				border-color: #004494;
			}
			
			.top_link:active {
				background-color: #003366;
				border-color: #002244;
			}
			
			button {
				color: black;
			}
			
			.share_folder_buttons {
				width: fit-content;
			}
			
			button {
				background: #fcfcfe;
				border-color: #919b9c;
				border-top-color: rgb(145, 155, 156);
				border-bottom-color: rgb(145, 155, 156);
				margin-right: -1px;
				border-bottom: 1px solid transparent;
				border-top: 1px solid #e68b2c;
				box-shadow: inset 0 2px #ffc73c;
			}
			
			button {
				padding-bottom: 2px;
				margin-top: -2px;
				background-color: #ece9d8;
				position: relative;
				z-index: 8;
				margin-left: -3px;
				margin-bottom: 1px;
			}
			
			.window {
				min-width: 1100px;
			}
			
			[role="tab"] {
				padding: 10px !important;
			}
			
			[role="tabpanel"] {
				min-width: fit-content;
			}
			
			select {
				border: 1px solid #7f9db9;
				background-image: url("data:image/svg+xml;charset=utf-8,%3Csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 -0.5 15 17' shape-rendering='crispEdges'%3E%3Cpath stroke='%23e6eefc' d='M0 0h1'/%3E%3Cpath stroke='%23d1e0fd' d='M1 0h1M0 1h1m3 0h2M2 3h1M2 4h1'/%3E%3Cpath stroke='%23cad8f9' d='M2 0h1M0 2h1'/%3E%3Cpath stroke='%23c4d3f7' d='M3 0h1M0 3h1M0 4h1'/%3E%3Cpath stroke='%23bfd0f8' d='M4 0h2M0 5h1'/%3E%3Cpath stroke='%23bdcef7' d='M6 0h1M0 6h1'/%3E%3Cpath stroke='%23baccf4' d='M7 0h1m6 2h1m-1 5h1m-1 1h1'/%3E%3Cpath stroke='%23b8cbf6' d='M8 0h1M0 7h1M0 8h1'/%3E%3Cpath stroke='%23b7caf5' d='M9 0h2M0 9h1'/%3E%3Cpath stroke='%23b5c8f7' d='M11 0h1'/%3E%3Cpath stroke='%23b3c7f5' d='M12 0h1'/%3E%3Cpath stroke='%23afc5f4' d='M13 0h1'/%3E%3Cpath stroke='%23dce6f9' d='M14 0h1'/%3E%3Cpath stroke='%23e1eafe' d='M1 1h1'/%3E%3Cpath stroke='%23dae6fe' d='M2 1h1M1 2h1'/%3E%3Cpath stroke='%23d4e1fc' d='M3 1h1M1 3h1M1 4h1'/%3E%3Cpath stroke='%23d0ddfc' d='M6 1h1M1 5h1'/%3E%3Cpath stroke='%23cedbfd' d='M7 1h1M4 2h2'/%3E%3Cpath stroke='%23cad9fd' d='M8 1h1M6 2h1M3 5h1'/%3E%3Cpath stroke='%23c8d8fb' d='M9 1h2'/%3E%3Cpath stroke='%23c5d6fc' d='M11 1h1M2 11h4'/%3E%3Cpath stroke='%23c2d3fc' d='M12 1h1m-2 1h1M1 11h1m0 1h2m-2 1h2'/%3E%3Cpath stroke='%23bccefa' d='M13 1h1m-1 1h1m-1 1h1m-1 1h1M3 15h4'/%3E%3Cpath stroke='%23b9c9f3' d='M14 1h1M3 16h4'/%3E%3Cpath stroke='%23d8e3fc' d='M2 2h1'/%3E%3Cpath stroke='%23d1defd' d='M3 2h1'/%3E%3Cpath stroke='%23c9d8fc' d='M7 2h1M4 3h3M4 4h3M3 6h1m1 0h2M1 7h1M1 8h1'/%3E%3Cpath stroke='%23c5d5fc' d='M8 2h1m-8 8h5'/%3E%3Cpath stroke='%23c5d3fc' d='M9 2h2'/%3E%3Cpath stroke='%23bed0fc' d='M12 2h1M8 3h1M8 4h1m-8 8h1m-1 1h1m0 1h1m1 0h3'/%3E%3Cpath stroke='%23cddbfc' d='M3 3h1M3 4h1M1 6h2'/%3E%3Cpath stroke='%23c8d5fb' d='M7 3h1M7 4h1'/%3E%3Cpath stroke='%23bbcefd' d='M9 3h4M9 4h4M8 5h1M7 6h1'/%3E%3Cpath stroke='%23bcccf3' d='M14 3h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23ceddfd' d='M2 5h1'/%3E%3Cpath stroke='%23c8d6fb' d='M4 5h4M1 9h3'/%3E%3Cpath stroke='%23bacdfc' d='M9 5h2m1 0h2M1 14h1'/%3E%3Cpath stroke='%23b9cdfb' d='M11 5h1M8 6h2m2 0h2m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%234d6185' d='M4 6h1m5 0h1M3 7h3m3 0h3M4 8h3m1 0h3M5 9h5m-4 1h3m-2 1h1'/%3E%3Cpath stroke='%23b7cdfc' d='M11 6h1m0 1h1m-1 1h1'/%3E%3Cpath stroke='%23cad8fd' d='M2 7h1M2 8h2'/%3E%3Cpath stroke='%23c1d3fb' d='M6 7h2M7 8h1M4 9h1'/%3E%3Cpath stroke='%23b6cefb' d='M8 7h1m2 1h1m-2 1h3m-2 1h2'/%3E%3Cpath stroke='%23b6cdfb' d='M13 9h1m-6 6h1'/%3E%3Cpath stroke='%23b9cbf3' d='M14 9h1'/%3E%3Cpath stroke='%23b4c8f6' d='M0 10h1'/%3E%3Cpath stroke='%23bdd3fb' d='M9 10h2m-4 4h1'/%3E%3Cpath stroke='%23b5cdfa' d='M13 10h1'/%3E%3Cpath stroke='%23b5c9f3' d='M14 10h1'/%3E%3Cpath stroke='%23b1c7f6' d='M0 11h1'/%3E%3Cpath stroke='%23c3d5fd' d='M6 11h1'/%3E%3Cpath stroke='%23bad4fc' d='M8 11h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23b2cffb' d='M9 11h4m-2 3h1'/%3E%3Cpath stroke='%23b1cbfa' d='M13 11h1m-3 4h1'/%3E%3Cpath stroke='%23b3c8f5' d='M14 11h1m-7 5h3'/%3E%3Cpath stroke='%23adc3f6' d='M0 12h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23c2d5fc' d='M4 12h4m-4 1h4'/%3E%3Cpath stroke='%23b7d3fc' d='M9 12h2m-2 1h2m-3 1h1'/%3E%3Cpath stroke='%23b3d1fc' d='M11 12h1m-1 1h1'/%3E%3Cpath stroke='%23afcdfb' d='M12 12h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23afcbfa' d='M13 12h1m-1 1h1'/%3E%3Cpath stroke='%23b2c8f4' d='M14 12h1m-1 1h1m-4 3h1'/%3E%3Cpath stroke='%23c1d2fb' d='M3 14h1'/%3E%3Cpath stroke='%23b6d1fb' d='M9 14h2'/%3E%3Cpath stroke='%23adc9f9' d='M13 14h1m-2 1h1'/%3E%3Cpath stroke='%23b1c6f3' d='M14 14h1m-3 2h1'/%3E%3Cpath stroke='%23abc1f4' d='M0 15h1'/%3E%3Cpath stroke='%23b7cbf9' d='M1 15h1'/%3E%3Cpath stroke='%23b9cefb' d='M2 15h1'/%3E%3Cpath stroke='%23b9cffb' d='M7 15h1'/%3E%3Cpath stroke='%23b2cdfb' d='M9 15h2'/%3E%3Cpath stroke='%23aec8f7' d='M13 15h1'/%3E%3Cpath stroke='%23b0c5f2' d='M14 15h1m-2 1h1'/%3E%3Cpath stroke='%23dbe3f8' d='M0 16h1'/%3E%3Cpath stroke='%23b7c6f1' d='M1 16h1'/%3E%3Cpath stroke='%23b8c9f2' d='M2 16h1m4 0h1'/%3E%3Cpath stroke='%23d9e3f6' d='M14 16h1'/%3E%3C/svg%3E");
				background-size: 15px;
				font-size: 11px;
				border: none;
				background-color: #fff;
				box-sizing: border-box;
				height: 21px;
				appearance: none;
				-webkit-appearance: none;
				-moz-appearance: none;
				position: relative;
				padding: 5px 32px 32px 5px;
				background-position: top 50% right 2px;
				background-repeat: no-repeat;
				border-radius: 0;
				border: 1px solid black;
			}
			

			body {
				font-variant: oldstyle-nums;
				font-family: 'IBM Plex Sans', 'Source Sans Pro', sans-serif;
				background-color: #fafafa;
				text-shadow: 0 0.05em 0.1em rgba(0,0,0,0.2);
				scroll-behavior: smooth;
				text-wrap: balance;
				text-rendering: optimizeLegibility;
				-webkit-font-smoothing: antialiased;
				-moz-osx-font-smoothing: grayscale;
				font-feature-settings: "ss02", "liga", "onum";
			}
			
			.marked_text {
				background-color: yellow;
			}
			
			.time_picker_container {
				font-variant: small-caps;
				width: 100%;
			}
			
			.time_picker_container > input {
				width: 50px;
			}
			
			#loader {
				display: grid;
				justify-content: center;
				align-items: center;
				height: 100%;
			}
			
			.no_linebreak {
				line-break: auto;
			}
			
			.dark_code_bg {
				background-color: #363636;
				color: white;
			}
			
			.code_bg {
				background-color: #C0C0C0;
			}
			
			#commands {
				line-break: anywhere;
			}
			
			.color_red {
				color: red;
			}
			
			.color_orange {
				color: orange;
			}
			
			table > tbody > tr:nth-child(odd) {
				background-color: #fafafa;
			}
			
			table > tbody > tr:nth-child(even) {
				background-color: #ddd;
			}
			
			table {
				border-collapse: collapse;
				margin: 0 0;
				min-width: 200px;
			}
			
			th {
				background-color: #4eae46;
				color: #ffffff;
				text-align: left;
				border: 0px;
			}
			
			.error_element {
				background-color: #e57373;
				border-radius: 10px;
				padding: 4px;
				display: none;
			}
			
			button {
				background-color: #4eae46;
				border: 1px solid #2A8387;
				border-radius: 4px;
				box-shadow: rgba(0, 0, 0, 0.12) 0 1px 1px;
				cursor: pointer;
				display: block;
				line-height: 100%;
				outline: 0;
				padding: 11px 15px 12px;
				text-align: center;
				transition: box-shadow .05s ease-in-out, opacity .05s ease-in-out;
				user-select: none;
				-webkit-user-select: none;
				touch-action: manipulation;
				font-family: 'IBM Plex Sans', 'Source Sans Pro', sans-serif;
			}
			
			button:hover {
				box-shadow: rgba(255, 255, 255, 0.3) 0 0 2px inset, rgba(0, 0, 0, 0.4) 0 1px 2px;
				text-decoration: none;
				transition-duration: .15s, .15s;
			}
			
			button:active {
				box-shadow: rgba(0, 0, 0, 0.15) 0 2px 4px inset, rgba(0, 0, 0, 0.4) 0 1px 1px;
			}
			
			button:disabled {
				cursor: not-allowed;
				opacity: .6;
			}
			
			button:disabled:active {
				pointer-events: none;
			}
			
			button:disabled:hover {
				box-shadow: none;
			}
			
			.half_width_td {
				vertical-align: baseline;
				width: 50%;
			}
			
			#scads_bar {
				width: 100%;
				margin: 0;
				padding: 0;
				user-select: none;
				user-drag: none;
				-webkit-user-drag: none;
				user-select: none;
				-moz-user-select: none;
				-webkit-user-select: none;
				-ms-user-select: none;
				display: -webkit-box;
			}
			
			.tab {
				display: inline-block;
				padding: 0px;
				margin: 0px;
				font-size: 16px;
				font-weight: bold;
				text-align: center;
				border-radius: 25px;
				text-decoration: none !important;
				transition: background-color 0.3s, color 0.3s;
				color: unset !important;
			}
			
			.tooltipster-base {
				border: 1px solid black;
				position: absolute;
				border-radius: 8px;
				padding: 2px;
				color: white;
				background-color: #61686f;
				width: 70%;
				min-width: 200px;
				pointer-events: none;
			}
			
			td {
				padding-top: 3px;
				padding-bottom: 3px;
			}
			
			.left_side {
				text-align: right;
			}
			
			.right_side {
				text-align: left;
			}
			
			.spinner {
				border: 8px solid rgba(0, 0, 0, 0.1);
				border-left: 8px solid #3498db;
				border-radius: 50%;
				width: 50px;
				height: 50px;
				animation: spin 1s linear infinite;
			}
			
			@keyframes spin {
				0% {
					transform: rotate(0deg);
				}
			
				100% {
					transform: rotate(360deg);
				}
			}
			
			#spinner-overlay {
				-webkit-text-stroke: 1px black;
				white !important;
				position: fixed;
				top: 0;
				left: 0;
				width: 100%;
				height: 100%;
				display: flex;
				justify-content: center;
				align-items: center;
				z-index: 9999;
			}
			
			#spinner-container {
				text-align: center;
				color: #fff;
				display: contents;
			}
			
			#spinner-text {
				font-size: 3vw;
				margin-left: 10px;
			}
			
			a, a:visited, a:active, a:hover, a:link {
				color: #007bff;
				text-decoration: none;
			}
			
			.copy-container {
				display: inline-block;
				position: relative;
				cursor: pointer;
				margin-left: 10px;
				color: blue;
			}
			
			.copy-container:hover {
				text-decoration: underline;
			}
			
			.clipboard-icon {
				position: absolute;
				top: 5px;
				right: 5px;
				font-size: 1.5em;
			}
			
			#main_tab {
				overflow: scroll;
				width: max-content;
			}
			
			.ui-tabs .ui-tabs-nav li {
				user-select: none;
			}
			
			.stacktrace_table {
				background-color: black !important;
				color: white !important;
			}
			
			#breadcrumb {
				user-select: none;
			}
			
			#statusBar {
				user-select: none;
			}
			
			.error_line {
				background-color: red !important;
				color: white !important;
			}
			
			.header_table {
				border: 0px !important;
				padding: 0px !important;
				width: revert !important;
				min-width: revert !important;
			}
			
			.img_auto_width {
				max-width: revert !important;
			}
			
			#main_dir_or_plot_view {
				display: inline-grid;
			}
			
			#refresh_button {
				width: 300px;
			}
			
			._share_link {
				color: black !important;
			}
			
			#footer_element {
				height: 30px;
				background-color: #f8f9fa;
				padding: 0px;
				text-align: center;
				border-top: 1px solid #dee2e6;
				width: 100%;
				box-sizing: border-box;
				position: fixed;
				bottom: 0;
				z-index: 2;
				margin-left: -9px;
				z-index: 99;
			}
			
			.switch {
				position: relative;
				display: inline-block;
				width: 50px;
				height: 26px;
			}
			
			.switch input {
				opacity: 0;
				width: 0;
				height: 0;
			}
			
			.slider {
				position: absolute;
				cursor: pointer;
				top: 0;
				left: 0;
				right: 0;
				bottom: 0;
				background-color: #ccc;
				transition: .4s;
				border-radius: 26px;
			}
			
			.slider:before {
				position: absolute;
				content: "";
				height: 20px;
				width: 20px;
				left: 3px;
				bottom: 3px;
				background-color: white;
				transition: .4s;
				border-radius: 50%;
			}
			
			input:checked + .slider {
				background-color: #444;
			}
			
			input:checked + .slider:before {
				transform: translateX(24px);
			}
			
			.mode-text {
				position: absolute;
				top: 5px;
				left: 65px;
				font-size: 14px;
				color: black;
				transition: .4s;
				width: 65px;
				display: block;
				font-size: 0.7rem;
				text-align: center;
			}
			
			input:checked + .slider .mode-text {
				content: "Dark Mode";
				color: white;
			}
			
			#mainContent {
				height: fit-content;
				min-height: 100%;
			}
			
			li {
				text-align: left;
			}
			
			#share_path {
				margin-bottom: 20px;
				margin-top: 20px;
			}
			
			#sortForm {
				margin-bottom: 20px;
			}
			
			.share_folder_buttons {
				margin-top: 10px;
				margin-bottom: 10px;
			}
			
			.nav_tab_button {
				margin: 10px;
			}
			
			.header_table {
				margin: 10px;
			}
			
			.no_border {
				border: unset !important;
			}
			
			.gui_table {
				padding: 5px !important;
			}
			
			.gui_parameter_row {
			}
			
			.gui_parameter_row_cell {
				border: unset !important;
			}
			
			.gui_param_table {
				width: 95%;
				margin: unset !important;
			}
			
			table td, table tr,
			.parameterRow table {
				padding: 2px !important;
			}
			
			.parameterRow table {
				margin: 0px;
				border: unset;
			}
			
			.parameterRow > td {
				border: 0px !important;
			}
			
			.parameter_config_table td, .parameter_config_table tr, #config_table th, #config_table td, #hidden_config_table th, #hidden_config_table td {
				border: 0px !important;
			}
			
			.green_text {
				color: green;
			}
			
			.remove_parameter {
				white-space: pre;
			}
			
			select {
				appearance: none;
				-webkit-appearance: none;
				-moz-appearance: none;
				background-color: #fff;
				color: #222;
				padding: 5px 30px 5px 5px;
				border: 1px solid #555;
				border-radius: 5px;
				cursor: pointer;
				outline: none;
				transition: all 0.3s ease;
				background:
					url("data:image/svg+xml;charset=UTF-8,%3Csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 10 6'%3E%3Cpath fill='%23888' d='M0 0l5 6 5-6z'/%3E%3C/svg%3E")
					no-repeat right 10px center,
				linear-gradient(180deg, #fff, #ecebe5 86%, #d8d0c4);
				background-size: 12px, auto;
			}
			
			select:hover {
				border-color: #888;
			}
			
			select:focus {
				border-color: #4caf50;
				box-shadow: 0 0 5px rgba(76, 175, 80, 0.5);
			}
			
			select::-ms-expand {
				display: none;
			}
			
			input, textarea {
				border-radius: 5px;
			}
			
			#search {
				width: 200px;
				max-width: 70%;
				background-image: url(images/search.svg);
				background-repeat: no-repeat;
				background-size: auto 40px;
				height: 40px;
				line-height: 40px;
				padding-left: 40px;
				box-sizing: border-box;
			}
			
			input[type="checkbox"] {
				appearance: none;
				-webkit-appearance: none;
				-moz-appearance: none;
				width: 25px;
				height: 25px;
				border: 2px solid #3498db;
				border-radius: 5px;
				background-color: #fff;
				position: relative;
				cursor: pointer;
				transition: all 0.3s ease;
				width: 25px !important;
			}
			
			input[type="checkbox"]:checked {
				background-color: #3498db;
				border-color: #2980b9;
			}
			
			input[type="checkbox"]:checked::before {
				content: '✔';
				position: absolute;
				left: 4px;
				top: 2px;
				color: #fff;
			}
			
			input[type="checkbox"]:hover {
				border-color: #2980b9;
				background-color: #3caffc;
			}
			
			.toc {
				margin-bottom: 20px;
			}
			
			.toc li {
				margin-bottom: 5px;
			}
			
			.toc a {
				text-decoration: none;
				color: #007bff;
			}
			
			.toc a:hover {
				text-decoration: underline;
			}
			
			.table-container {
				width: 100%;
				overflow-x: auto;
			}
			
			.section-header {
				background-color: #1d6f9a !important;
				color: white;
			}
			
			.warning {
				color: red;
			}
			
			.li_list a {
				text-decoration: none;
			}
			
			.gridjs-td {
				white-space: nowrap;
			}
			
			th, td {
				border: 1px solid gray !important;
			}
			
			.no_border {
				border: 0px !important;
			}
			
			.no_break {
			
			}
			
			img {
				user-select: none;
				pointer-events: none;
			}
			
			#config_table, #hidden_config_table {
				user-select: none;
			}
			
			.copy_clipboard_button {
				margin-bottom: 10px;
			}
			
			.badge_table {
				background-color: unset !important;
			}
			
			.make_markable {
				user-select: text;
			}
			
			.header-container {
				display: flex;
				flex-wrap: wrap;
				align-items: center;
				justify-content: space-between;
				gap: 1rem;
				padding: 10px;
				background: var(--header-bg, #fff);
				border-bottom: 1px solid #ccc;
			}
			
			.header-logo-group {
				display: flex;
				gap: 1rem;
				align-items: center;
				flex: 1 1 auto;
				min-width: 200px;
			}
			
			.logo-img {
				max-height: 45px;
				height: auto;
				width: auto;
				object-fit: contain;
				pointer-events: unset;
			}
			
			.header-badges {
				flex-direction: column;
				gap: 5px;
				align-items: flex-start;
				flex: 0 1 auto;
				margin-top: auto;
				margin-bottom: auto;
			}
			
			.badge-img {
				height: auto;
				max-width: 130px;
				margin-top: 3px;
			}
			
			.header-tabs {
				margin-top: 10px;
				display: flex;
				flex-wrap: wrap;
				gap: 10px;
				flex: 2 1 100%;
				justify-content: center;
			}
			
			.nav-tab {
				display: inline-block;
				text-decoration: none;
				padding: 8px 16px;
				border-radius: 20px;
				background: linear-gradient(to right, #4a90e2, #357ABD);
				color: white;
				font-weight: bold;
				white-space: nowrap;
				transition: background 0.2s ease-in-out, transform 0.2s;
				box-shadow: 0 2px 4px rgba(0,0,0,0.2);
			}
			
			.nav-tab:hover {
				background: linear-gradient(to right, #5aa0f2, #4a90e2);
				transform: translateY(-2px);
			}
			
			.current-tag {
				padding-left: 10px;
				font-size: 0.9rem;
				color: #666;
			}
			
			.header-theme-toggle {
				flex: 1 1 auto;
				align-items: center;
				margin-top: 20px;
				min-width: 120px;
			}
			
			.switch {
				position: relative;
				display: inline-block;
				width: 60px;
				height: 30px;
			}
			
			.switch input {
				display: none;
			}
			
			.slider {
				position: absolute;
				top: 0; left: 0; right: 0; bottom: 0;
				background-color: #ccc;
				border-radius: 34px;
				cursor: pointer;
			}
			
			.slider::before {
				content: "";
				position: absolute;
				height: 24px;
				width: 24px;
				left: 3px;
				bottom: 3px;
				background-color: white;
				transition: .4s;
				border-radius: 50%;
			}
			
			input:checked + .slider {
				background-color: #2196F3;
			}
			
			input:checked + .slider::before {
				transform: translateX(30px);
			}
			
			@media (max-width: 768px) {
				.header-logo-group,
				.header-badges,
				.header-theme-toggle {
					justify-content: center;
					flex: 1 1 100%;
					text-align: center;
					width: inherit;
				}
			
				.logo-img {
					max-height: 50px;
					pointer-events: unset;
				}
			
				.badge-img {
					max-width: 100px;
				}
			
				.hide_on_mobile {
					display: none;
				}
			
				.nav-tab {
					font-size: 0.9rem;
					padding: 6px 12px;
				}
			
				.header_button {
					white-space: pre;
					font-size: 2em;
				}
			}
			
			.header_button {
				white-space: pre;
				margin-top: 20px;
				margin: 5px;
			}
			
			.line_break_anywhere {
				line-break: anywhere;
			}
			
			.responsive-container {
				display: flex;
				flex-wrap: wrap;
				justify-content: space-between;
				gap: 20px;
			}
			
			.responsive-container .half {
				flex: 1 1 48%;
				box-sizing: border-box;
				min-width: 500px;
			}
			
			.config-section table {
				width: 100%;
				border-collapse: collapse;
			}
			
			@media (max-width: 768px) {
				.responsive-container .half {
					flex: 1 1 100%;
				}
			}
			
			@keyframes spin {
				0% {
					transform: rotate(0deg);
				}
			
				100% {
					transform: rotate(360deg);
				}
			}
			
			.rotate {
				animation: spin 2s linear infinite;
				display: inline-block;
			}
			
			input::placeholder {
				font-family: 'IBM Plex Sans', 'Source Sans Pro', sans-serif;
			}
			
			.gridjs-th-content {
				overflow: visible !important;
			}
			
			.error_text {
				color: red;
			}
			
			h1, h2, h3, h4, h5, h6 {
				margin-top: 1em;
				font-weight: bold;
				color: #333;
				border-left: 5px solid #ccc;
				padding-left: 0.5em;
			}
			
			.no_cursive {
				font-style: normal;	
			}
			
			.caveat {
				background-color: #fff8b3;
				border: 1px solid #f2d600;
				padding: 1em 1em 1em 70px;
				position: relative;
				font-family: sans-serif;
				color: #665500;
				margin: 1em 0;
				border-radius: 4px;
			}
			
			.caveat h1, .caveat h2, .caveat h3, .caveat h4 {
				margin-top: 0;
				margin-bottom: 0.5em;
				font-weight: bold;
			}
			
			.caveat::before {
				content: "⚠️";
				font-size: 50px;
				line-height: 1;
				position: absolute;
				left: 10px;
				top: 50%;
				transform: translateY(-50%);
				pointer-events: none;
				user-select: none;
			}
			
			.caveat.warning::before { content: "⚠️"; }
			.caveat.stop::before { content: "🛑"; }
			.caveat.exclamation::before { content: "❗"; }
			.caveat.alarm::before { content: "🚨"; }
			.caveat.tip::before { content: "💡"; }
			
			.tutorial_icon {
				display: inline-block;
				font-size: 1.3em;
				line-height: 1;
				vertical-align: middle;
				transform: translateY(-10%);
				padding: 0.2em 0;
			}
			
			.highlight {
				background-color: yellow;
				font-weight: bold;
			}
			
			#searchResults li {
				opacity: 0;
				transform: translateY(8px);
				animation: fadeInUp 0.3s ease-out forwards;
				animation-delay: 0.05s;
				list-style: none;
				margin-bottom: 5px;
			}
			
			@keyframes fadeInUp {
				to {
					opacity: 1;
					transform: translateY(0);
				}
			}
			
			.search_headline {
				font-weight: bold;
				margin-top: 1em;
				margin-bottom: 0.3em;
				color: #444;
			}
			
			.search_share_path {
				color: black;
				display: block ruby;
				margin-top: 20px;
			}
			
			@media print {
				#scads_bar {
					display: none !important;
				}
			}
			

			/*! XP.css v0.2.6 - https: //botoxparty.github.io/XP.css/ */
			body{
				color: #222
			}
			
			.surface{
				background: #ece9d8
			}
			
			u{
				text-decoration: none;
				border-bottom: .5px solid #222
			}
			
			a{
				color: #00f
			}
			
			a: focus{
				outline: 1px dotted #00f
			}
			
			code,code *{
				font-family: monospace
			}
			
			pre{
				display: block;
				padding: 12px 8px;
				background-color: #000;
				color: silver;
				font-size: 1rem;
				margin: 0;
				overflow: scroll;
			}
			
			summary: focus{
				outline: 1px dotted #000
			}
			
			: :-webkit-scrollbar{
				width: 16px
			}
			
			: :-webkit-scrollbar: horizontal{
				height: 17px
			}
			
			: :-webkit-scrollbar-track{
				background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='2' height='2' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M1 0H0v1h1v1h1V1H1V0z' fill='silver'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M2 0H1v1H0v1h1V1h1V0z' fill='%23fff'/%3E%3C/svg%3E")
			}
			
			: :-webkit-scrollbar-thumb{
				background-color: #dfdfdf;
				box-shadow: inset -1px -1px #0a0a0a,inset 1px 1px #fff,inset -2px -2px grey,inset 2px 2px #dfdfdf
			}
			
			: :-webkit-scrollbar-button: horizontal: end: increment,: :-webkit-scrollbar-button: horizontal: start: decrement,: :-webkit-scrollbar-button: vertical: end: increment,: :-webkit-scrollbar-button: vertical: start: decrement{
				display: block
			}
			
			: :-webkit-scrollbar-button: vertical: start{
				background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='16' height='17' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 0H0v16h1V1h14V0z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M2 1H1v14h1V2h12V1H2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M16 17H0v-1h15V0h1v17z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 1h-1v14H1v1h14V1z' fill='gray'/%3E%3Cpath fill='silver' d='M2 2h12v13H2z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 6H7v1H6v1H5v1H4v1h7V9h-1V8H9V7H8V6z' fill='%23000'/%3E%3C/svg%3E")
			}
			
			: :-webkit-scrollbar-button: vertical: end{
				background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='16' height='17' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 0H0v16h1V1h14V0z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M2 1H1v14h1V2h12V1H2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M16 17H0v-1h15V0h1v17z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 1h-1v14H1v1h14V1z' fill='gray'/%3E%3Cpath fill='silver' d='M2 2h12v13H2z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M11 6H4v1h1v1h1v1h1v1h1V9h1V8h1V7h1V6z' fill='%23000'/%3E%3C/svg%3E")
			}
			
			: :-webkit-scrollbar-button: horizontal: start{
				width: 16px;
				background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='16' height='17' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 0H0v16h1V1h14V0z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M2 1H1v14h1V2h12V1H2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M16 17H0v-1h15V0h1v17z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 1h-1v14H1v1h14V1z' fill='gray'/%3E%3Cpath fill='silver' d='M2 2h12v13H2z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 4H8v1H7v1H6v1H5v1h1v1h1v1h1v1h1V4z' fill='%23000'/%3E%3C/svg%3E")
			}
			
			: :-webkit-scrollbar-button: horizontal: end{
				width: 16px;
				background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='16' height='17' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 0H0v16h1V1h14V0z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M2 1H1v14h1V2h12V1H2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M16 17H0v-1h15V0h1v17z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 1h-1v14H1v1h14V1z' fill='gray'/%3E%3Cpath fill='silver' d='M2 2h12v13H2z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M7 4H6v7h1v-1h1V9h1V8h1V7H9V6H8V5H7V4z' fill='%23000'/%3E%3C/svg%3E")
			}
			
			button{
				border: none;
				background: #ece9d8;
				box-shadow: inset -1px -1px #0a0a0a,inset 1px 1px #fff,inset -2px -2px grey,inset 2px 2px #dfdfdf;
				border-radius: 0;
				min-width: 75px;
				min-height: 23px;
				padding: 0 12px
			}
			
			button: not(: disabled).active,button: not(: disabled): active{
				box-shadow: inset -1px -1px #fff,inset 1px 1px #0a0a0a,inset -2px -2px #dfdfdf,inset 2px 2px grey
			}
			
			button.focused,button: focus{
				outline: 1px dotted #000;
				outline-offset: -4px
			}
			
			label{
				display: inline-flex;
				align-items: center
			}
			
			textarea{
				padding: 3px 4px;
				border: none;
				background-color: #fff;
				box-sizing: border-box;
				-webkit-appearance: none;
				-moz-appearance: none;
				appearance: none;
				border-radius: 0
			}
			
			textarea: focus{
				outline: none
			}
			
			select: focus option{
				color: #000;
				background-color: #fff
			}
			
			.vertical-bar{
				width: 4px;
				height: 20px;
				background: silver;
				box-shadow: inset -1px -1px #0a0a0a,inset 1px 1px #fff,inset -2px -2px grey,inset 2px 2px #dfdfdf
			}
			
			&: disabled,&: disabled+label{
				color: grey;
				text-shadow: 1px 1px 0 #fff
			}
			
			input[type=radio]+label{
				line-height: 13px;
				position: relative;
				margin-left: 19px
			}
			
			input[type=radio]+label: before{
				content: "";
				position: absolute;
				top: 0;
				left: -19px;
				display: inline-block;
				width: 13px;
				height: 13px;
				margin-right: 6px;
				background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='12' height='12' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 0H4v1H2v1H1v2H0v4h1v2h1V8H1V4h1V2h2V1h4v1h2V1H8V0z' fill='gray'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 1H4v1H2v2H1v4h1v1h1V8H2V4h1V3h1V2h4v1h2V2H8V1z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 3h1v1H9V3zm1 5V4h1v4h-1zm-2 2V9h1V8h1v2H8zm-4 0v1h4v-1H4zm0 0V9H2v1h2z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M11 2h-1v2h1v4h-1v2H8v1H4v-1H2v1h2v1h4v-1h2v-1h1V8h1V4h-1V2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M4 2h4v1h1v1h1v4H9v1H8v1H4V9H3V8H2V4h1V3h1V2z' fill='%23fff'/%3E%3C/svg%3E")
			}
			
			input[type=radio]: active+label: before{
				background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='12' height='12' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 0H4v1H2v1H1v2H0v4h1v2h1V8H1V4h1V2h2V1h4v1h2V1H8V0z' fill='gray'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 1H4v1H2v2H1v4h1v1h1V8H2V4h1V3h1V2h4v1h2V2H8V1z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 3h1v1H9V3zm1 5V4h1v4h-1zm-2 2V9h1V8h1v2H8zm-4 0v1h4v-1H4zm0 0V9H2v1h2z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M11 2h-1v2h1v4h-1v2H8v1H4v-1H2v1h2v1h4v-1h2v-1h1V8h1V4h-1V2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M4 2h4v1h1v1h1v4H9v1H8v1H4V9H3V8H2V4h1V3h1V2z' fill='silver'/%3E%3C/svg%3E")
			}
			
			input[type=radio]: checked+label: after{
				content: "";
				display: block;
				width: 5px;
				height: 5px;
				top: 5px;
				left: -14px;
				position: absolute;
				background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='4' height='4' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M3 0H1v1H0v2h1v1h2V3h1V1H3V0z' fill='%23000'/%3E%3C/svg%3E")
			}
			
			input[type=radio][disabled]+label: before{
				background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='12' height='12' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 0H4v1H2v1H1v2H0v4h1v2h1V8H1V4h1V2h2V1h4v1h2V1H8V0z' fill='gray'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 1H4v1H2v2H1v4h1v1h1V8H2V4h1V3h1V2h4v1h2V2H8V1z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 3h1v1H9V3zm1 5V4h1v4h-1zm-2 2V9h1V8h1v2H8zm-4 0v1h4v-1H4zm0 0V9H2v1h2z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M11 2h-1v2h1v4h-1v2H8v1H4v-1H2v1h2v1h4v-1h2v-1h1V8h1V4h-1V2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M4 2h4v1h1v1h1v4H9v1H8v1H4V9H3V8H2V4h1V3h1V2z' fill='silver'/%3E%3C/svg%3E")
			}
			
			input[type=radio][disabled]: checked+label: after{
				background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='4' height='4' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M3 0H1v1H0v2h1v1h2V3h1V1H3V0z' fill='gray'/%3E%3C/svg%3E")
			}
			
			input[type=email],input[type=password]{
				padding: 3px 4px;
				border: 1px solid #7f9db9;
				background-color: #fff;
				box-sizing: border-box;
				-webkit-appearance: none;
				-moz-appearance: none;
				appearance: none;
				border-radius: 0;
				height: 21px;
				line-height: 2
			}
			
			input[type=email]: focus,input[type=password]: focus{
				outline: none
			}
			
			input[type=range]{
				-webkit-appearance: none;
				width: 100%;
				background: transparent
			}
			
			input[type=range]: focus{
				outline: none
			}
			
			input[type=range]: :-webkit-slider-thumb{
				-webkit-appearance: none;
				background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='11' height='21' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0v16h2v2h2v2h1v-1H3v-2H1V1h9V0z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M1 1v15h1v1h1v1h1v1h2v-1h1v-1h1v-1h1V1z' fill='%23C0C7C8'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 1h1v15H8v2H6v2H5v-1h2v-2h2z' fill='%2387888F'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M10 0h1v16H9v2H7v2H5v1h1v-2h2v-2h2z' fill='%23000'/%3E%3C/svg%3E")
			}
			
			input[type=range]: :-moz-range-thumb{
				background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='11' height='21' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0v16h2v2h2v2h1v-1H3v-2H1V1h9V0z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M1 1v15h1v1h1v1h1v1h2v-1h1v-1h1v-1h1V1z' fill='%23C0C7C8'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 1h1v15H8v2H6v2H5v-1h2v-2h2z' fill='%2387888F'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M10 0h1v16H9v2H7v2H5v1h1v-2h2v-2h2z' fill='%23000'/%3E%3C/svg%3E")
			}
			
			input[type=range]: :-webkit-slider-runnable-track{
				background: #000;
				border-right: 1px solid grey;
				border-bottom: 1px solid grey;
				box-shadow: 1px 0 0 #fff,1px 1px 0 #fff,0 1px 0 #fff,-1px 0 0 #a9a9a9,-1px -1px 0 #a9a9a9,0 -1px 0 #a9a9a9,-1px 1px 0 #fff,1px -1px #a9a9a9
			}
			
			input[type=range]: :-moz-range-track{
				background: #000;
				border-right: 1px solid grey;
				border-bottom: 1px solid grey;
				box-shadow: 1px 0 0 #fff,1px 1px 0 #fff,0 1px 0 #fff,-1px 0 0 #a9a9a9,-1px -1px 0 #a9a9a9,0 -1px 0 #a9a9a9,-1px 1px 0 #fff,1px -1px #a9a9a9
			}
			
			input[type=range].has-box-indicator: :-webkit-slider-thumb{
				background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='11' height='21' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0v20h1V1h9V0z' fill='%23fff'/%3E%3Cpath fill='%23C0C7C8' d='M1 1h8v18H1z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 1h1v19H1v-1h8z' fill='%2387888F'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M10 0h1v21H0v-1h10z' fill='%23000'/%3E%3C/svg%3E")
			}
			
			input[type=range].has-box-indicator: :-moz-range-thumb{
				background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='11' height='21' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0v20h1V1h9V0z' fill='%23fff'/%3E%3Cpath fill='%23C0C7C8' d='M1 1h8v18H1z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 1h1v19H1v-1h8z' fill='%2387888F'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M10 0h1v21H0v-1h10z' fill='%23000'/%3E%3C/svg%3E")
			}
			
			.is-vertical{
				display: inline-block;
				width: 4px;
				height: 150px;
				transform: translateY(50%)
			}
			
			.is-vertical>input[type=range]{
				width: 150px;
				height: 4px;
				margin: 0 16px 0 10px;
				transform-origin: left;
				transform: rotate(270deg) translateX(calc(-50% + 8px))
			}
			
			.is-vertical>input[type=range]: :-webkit-slider-runnable-track{
				border-left: 1px solid grey;
				border-bottom: 1px solid grey;
				box-shadow: -1px 0 0 #fff,-1px 1px 0 #fff,0 1px 0 #fff,1px 0 0 #a9a9a9,1px -1px 0 #a9a9a9,0 -1px 0 #a9a9a9,1px 1px 0 #fff,-1px -1px #a9a9a9
			}
			
			.is-vertical>input[type=range]: :-moz-range-track{
				border-left: 1px solid grey;
				border-bottom: 1px solid grey;
				box-shadow: -1px 0 0 #fff,-1px 1px 0 #fff,0 1px 0 #fff,1px 0 0 #a9a9a9,1px -1px 0 #a9a9a9,0 -1px 0 #a9a9a9,1px 1px 0 #fff,-1px -1px #a9a9a9
			}
			
			.is-vertical>input[type=range]: :-webkit-slider-thumb{
				transform: translateY(-8px) scaleX(-1)
			}
			
			.is-vertical>input[type=range]: :-moz-range-thumb{
				transform: translateY(2px) scaleX(-1)
			}
			
			.is-vertical>input[type=range].has-box-indicator: :-webkit-slider-thumb{
				transform: translateY(-10px) scaleX(-1)
			}
			
			.is-vertical>input[type=range].has-box-indicator: :-moz-range-thumb{
				transform: translateY(0) scaleX(-1)
			}
			
			.window{
				font-size: 11px;
				box-shadow: inset -1px -1px #0a0a0a,inset 1px 1px #dfdfdf,inset -2px -2px grey,inset 2px 2px #fff;
				background: #ece9d8;
				padding: 3px
			}
			
			.window fieldset{
				margin-bottom: 9px
			}
			
			.title-bar{
				background: #000;
				padding: 3px 2px 3px 3px;
				display: flex;
				justify-content: space-between;
				align-items: center
			}
			
			.title-bar-text{
				font-weight: 700;
				color: #fff;
				letter-spacing: 0;
				margin-right: 24px
			}
			
			.title-bar-controls button{
				padding: 0;
				display: block;
				min-width: 16px;
				min-height: 14px
			}
			
			.title-bar-controls button: focus{
				outline: none
			}
			
			.window-body{
				margin: 8px
			}
			
			.window-body pre{
				margin: -8px
			}
			
			.status-bar{
				margin: 0 1px;
				display: flex;
				gap: 1px
			}
			
			.status-bar-field{
				box-shadow: inset -1px -1px #dfdfdf,inset 1px 1px grey;
				flex-grow: 1;
				padding: 2px 3px;
				margin: 0
			}
			
			ul.tree-view{
				display: block;
				background: #fff;
				padding: 6px;
				margin: 0
			}
			
			ul.tree-view li{
				list-style-type: none;
				margin-top: 3px
			}
			
			ul.tree-view a{
				text-decoration: none;
				color: #000
			}
			
			ul.tree-view a: focus{
				background-color: #2267cb;
				color: #fff
			}
			
			ul.tree-view ul{
				margin-top: 3px;
				margin-left: 16px;
				padding-left: 16px;
				border-left: 1px dotted grey
			}
			
			ul.tree-view ul>li{
				position: relative
			}
			
			ul.tree-view ul>li: before{
				content: "";
				display: block;
				position: absolute;
				left: -16px;
				top: 6px;
				width: 12px;
				border-bottom: 1px dotted grey
			}
			
			ul.tree-view ul>li: last-child: after{
				content: "";
				display: block;
				position: absolute;
				left: -20px;
				top: 7px;
				bottom: 0;
				width: 8px;
				background: #fff
			}
			
			ul.tree-view ul details>summary: before{
				margin-left: -22px;
				position: relative;
				z-index: 1
			}
			
			ul.tree-view details{
				margin-top: 0
			}
			
			ul.tree-view details>summary: before{
				text-align: center;
				display: block;
				float: left;
				content: "+";
				border: 1px solid grey;
				width: 8px;
				height: 9px;
				line-height: 9px;
				margin-right: 5px;
				padding-left: 1px;
				background-color: #fff
			}
			
			ul.tree-view details[open] summary{
				margin-bottom: 0
			}
			
			ul.tree-view details[open]>summary: before{
				content: "-"
			}
			
			fieldset{
				border-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='5' height='5' fill='gray' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0h5v5H0V2h2v1h1V2H0' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0h4v4H0V1h1v2h2V1H0'/%3E%3C/svg%3E") 2;
				padding: 10px;
				padding-block-start: 8px;
				margin: 0
			}
			
			legend{
				background: #ece9d8
			}
			
			menu[role=tablist]{
				position: relative;
				margin: 0 0 -2px;
				text-indent: 0;
				list-style-type: none;
				display: flex;
				padding-left: 3px
			}
			
			menu[role=tablist] button{
				z-index: 1;
				display: block;
				color: #222;
				text-decoration: none;
				min-width: unset
			}
			
			menu[role=tablist] button[aria-selected=true]{
				padding-bottom: 2px;margin-top: -2px;background-color: #ece9d8;position: relative;z-index: 8;margin-left: -3px;margin-bottom: 1px
			}
			
			menu[role=tablist] button: focus{
				outline: 1px dotted #222;outline-offset: -4px
			}
			
			menu[role=tablist].justified button{
				flex-grow: 1;text-align: center
			}
			
			[role=tabpanel]{
				padding: 14px;clear: both;background: linear-gradient(180deg,#fcfcfe,#f4f3ee);border: 1px solid #919b9c;position: relative;z-index: 2;margin-bottom: 9px
			}
			
			: :-webkit-scrollbar{
				width: 17px
			}
			
			: :-webkit-scrollbar-corner{
				background: #dfdfdf
			}
			
			: :-webkit-scrollbar-track: vertical{
				background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 17 1' shape-rendering='crispEdges'%3E%3Cpath stroke='%23eeede5' d='M0 0h1m15 0h1'/%3E%3Cpath stroke='%23f3f1ec' d='M1 0h1'/%3E%3Cpath stroke='%23f4f1ec' d='M2 0h1'/%3E%3Cpath stroke='%23f4f3ee' d='M3 0h1'/%3E%3Cpath stroke='%23f5f4ef' d='M4 0h1'/%3E%3Cpath stroke='%23f6f5f0' d='M5 0h1'/%3E%3Cpath stroke='%23f7f7f3' d='M6 0h1'/%3E%3Cpath stroke='%23f9f8f4' d='M7 0h1'/%3E%3Cpath stroke='%23f9f9f7' d='M8 0h1'/%3E%3Cpath stroke='%23fbfbf8' d='M9 0h1'/%3E%3Cpath stroke='%23fbfbf9' d='M10 0h2'/%3E%3Cpath stroke='%23fdfdfa' d='M12 0h1'/%3E%3Cpath stroke='%23fefefb' d='M13 0h3'/%3E%3C/svg%3E")
			}
			
			: :-webkit-scrollbar-track: horizontal{
				background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 1 17' shape-rendering='crispEdges'%3E%3Cpath stroke='%23eeede5' d='M0 0h1M0 16h1'/%3E%3Cpath stroke='%23f3f1ec' d='M0 1h1'/%3E%3Cpath stroke='%23f4f1ec' d='M0 2h1'/%3E%3Cpath stroke='%23f4f3ee' d='M0 3h1'/%3E%3Cpath stroke='%23f5f4ef' d='M0 4h1'/%3E%3Cpath stroke='%23f6f5f0' d='M0 5h1'/%3E%3Cpath stroke='%23f7f7f3' d='M0 6h1'/%3E%3Cpath stroke='%23f9f8f4' d='M0 7h1'/%3E%3Cpath stroke='%23f9f9f7' d='M0 8h1'/%3E%3Cpath stroke='%23fbfbf8' d='M0 9h1'/%3E%3Cpath stroke='%23fbfbf9' d='M0 10h1m-1 1h1'/%3E%3Cpath stroke='%23fdfdfa' d='M0 12h1'/%3E%3Cpath stroke='%23fefefb' d='M0 13h1m-1 1h1m-1 1h1'/%3E%3C/svg%3E")
			}
			
			: :-webkit-scrollbar-thumb{
				background-position: 50%;
				background-repeat: no-repeat;
				background-color: #c8d6fb;
				background-size: 7px;
				border: 1px solid #fff;
				border-radius: 2px;
				box-shadow: inset -3px 0 #bad1fc,inset 1px 1px #b7caf5
			}
			
			: :-webkit-scrollbar-thumb: vertical{
				background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 7 8' shape-rendering='crispEdges'%3E%3Cpath stroke='%23eef4fe' d='M0 0h6M0 2h6M0 4h6M0 6h6'/%3E%3Cpath stroke='%23bad1fc' d='M6 0h1M6 2h1M6 4h1'/%3E%3Cpath stroke='%23c8d6fb' d='M0 1h1M0 3h1M0 5h1M0 7h1'/%3E%3Cpath stroke='%238cb0f8' d='M1 1h6M1 3h6M1 5h6M1 7h6'/%3E%3Cpath stroke='%23bad3fc' d='M6 6h1'/%3E%3C/svg%3E")
			}
			
			: :-webkit-scrollbar-thumb: horizontal{
				background-size: 8px;background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 8 7' shape-rendering='crispEdges'%3E%3Cpath stroke='%23eef4fe' d='M0 0h1m1 0h1m1 0h1m1 0h1M0 1h1m1 0h1m1 0h1m1 0h1M0 2h1m1 0h1m1 0h1m1 0h1M0 3h1m1 0h1m1 0h1m1 0h1M0 4h1m1 0h1m1 0h1m1 0h1M0 5h1m1 0h1m1 0h1m1 0h1'/%3E%3Cpath stroke='%23c8d6fb' d='M1 0h1m1 0h1m1 0h1m1 0h1'/%3E%3Cpath stroke='%238cb0f8' d='M1 1h1m1 0h1m1 0h1m1 0h1M1 2h1m1 0h1m1 0h1m1 0h1M1 3h1m1 0h1m1 0h1m1 0h1M1 4h1m1 0h1m1 0h1m1 0h1M1 5h1m1 0h1m1 0h1m1 0h1M1 6h1m1 0h1m1 0h1m1 0h1'/%3E%3Cpath stroke='%23bad1fc' d='M0 6h1m1 0h1'/%3E%3Cpath stroke='%23bad3fc' d='M4 6h1m1 0h1'/%3E%3C/svg%3E")
			}
			
			: :-webkit-scrollbar-button: vertical: start{
				height: 17px;
				background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 17 17' shape-rendering='crispEdges'%3E%3Cpath stroke='%23eeede5' d='M0 0h1m15 0h1M0 1h1M0 2h1M0 3h1M0 4h1M0 5h1M0 6h1M0 7h1M0 8h1M0 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m15 0h1M0 16h1m15 0h1'/%3E%3Cpath stroke='%23fdfdfa' d='M1 0h1'/%3E%3Cpath stroke='%23fff' d='M2 0h14M1 1h1m13 0h1M1 2h1m13 0h1M1 3h1m13 0h1M1 4h1m13 0h1M1 5h1m13 0h1M1 6h1m13 0h1M1 7h1m13 0h1M1 8h1m13 0h1M1 9h1m13 0h1M1 10h1m13 0h1M1 11h1m13 0h1M1 12h1m13 0h1M1 13h1m13 0h1M1 14h1m13 0h1M2 15h13'/%3E%3Cpath stroke='%23e6eefc' d='M2 1h1'/%3E%3Cpath stroke='%23d0dffc' d='M3 1h1M2 2h1'/%3E%3Cpath stroke='%23cad8f9' d='M4 1h1M2 3h1'/%3E%3Cpath stroke='%23c4d2f7' d='M5 1h1'/%3E%3Cpath stroke='%23c0d0f7' d='M6 1h1'/%3E%3Cpath stroke='%23bdcef7' d='M7 1h1M2 6h1'/%3E%3Cpath stroke='%23bbcdf5' d='M8 1h1'/%3E%3Cpath stroke='%23b8cbf6' d='M9 1h1M2 7h1'/%3E%3Cpath stroke='%23b7caf5' d='M10 1h1M2 8h1'/%3E%3Cpath stroke='%23b5c8f7' d='M11 1h1'/%3E%3Cpath stroke='%23b3c7f5' d='M12 1h1'/%3E%3Cpath stroke='%23afc5f4' d='M13 1h1'/%3E%3Cpath stroke='%23dce6f9' d='M14 1h1'/%3E%3Cpath stroke='%23dfe2e1' d='M16 1h1'/%3E%3Cpath stroke='%23e1eafe' d='M3 2h1'/%3E%3Cpath stroke='%23dae6fe' d='M4 2h1M3 3h1'/%3E%3Cpath stroke='%23d4e1fc' d='M5 2h1M3 4h1'/%3E%3Cpath stroke='%23d1e0fd' d='M6 2h1M4 4h1'/%3E%3Cpath stroke='%23d0ddfc' d='M7 2h1M3 5h1'/%3E%3Cpath stroke='%23cedbfd' d='M8 2h1M6 3h1'/%3E%3Cpath stroke='%23cad9fd' d='M9 2h1M7 3h1M5 5h1'/%3E%3Cpath stroke='%23c8d8fb' d='M10 2h1'/%3E%3Cpath stroke='%23c5d6fc' d='M11 2h1m-8 8h1m1 0h1'/%3E%3Cpath stroke='%23c2d3fc' d='M12 2h1m-2 1h1m-9 7h1m0 1h1'/%3E%3Cpath stroke='%23bccefa' d='M13 2h1m-1 2h1m-9 9h2'/%3E%3Cpath stroke='%23b9c9f3' d='M14 2h1M5 14h3'/%3E%3Cpath stroke='%23cfd7dd' d='M16 2h1'/%3E%3Cpath stroke='%23d8e3fc' d='M4 3h1'/%3E%3Cpath stroke='%23d1defd' d='M5 3h1'/%3E%3Cpath stroke='%23c9d8fc' d='M8 3h1M6 4h2M5 6h2M3 7h1'/%3E%3Cpath stroke='%23c5d5fc' d='M9 3h1M3 9h1m3 0h1'/%3E%3Cpath stroke='%23c5d3fc' d='M10 3h1'/%3E%3Cpath stroke='%23bed0fc' d='M12 3h1M9 4h1m-7 7h1m0 1h1'/%3E%3Cpath stroke='%23bccdfa' d='M13 3h1'/%3E%3Cpath stroke='%23baccf4' d='M14 3h1'/%3E%3Cpath stroke='%23bdcbda' d='M16 3h1'/%3E%3Cpath stroke='%23c4d4f7' d='M2 4h1'/%3E%3Cpath stroke='%23cddbfc' d='M5 4h1M3 6h1'/%3E%3Cpath stroke='%23c8d5fb' d='M8 4h1'/%3E%3Cpath stroke='%23bbcefd' d='M10 4h3M9 5h1'/%3E%3Cpath stroke='%23bcccf3' d='M14 4h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23b1c2d5' d='M16 4h1'/%3E%3Cpath stroke='%23bed0f8' d='M2 5h1'/%3E%3Cpath stroke='%23ceddfd' d='M4 5h1'/%3E%3Cpath stroke='%23c8d6fb' d='M6 5h2M3 8h2'/%3E%3Cpath stroke='%234d6185' d='M8 5h1M7 6h3M6 7h5M5 8h3m1 0h3M4 9h3m3 0h3m-8 1h1m5 0h1'/%3E%3Cpath stroke='%23bacdfc' d='M10 5h1m1 0h2M3 12h1'/%3E%3Cpath stroke='%23b9cdfb' d='M11 5h1m-2 1h1m1 0h2m-1 1h1'/%3E%3Cpath stroke='%23a8bbd4' d='M16 5h1'/%3E%3Cpath stroke='%23cddafc' d='M4 6h1'/%3E%3Cpath stroke='%23b7cdfc' d='M11 6h1m0 1h1'/%3E%3Cpath stroke='%23a4b8d3' d='M16 6h1'/%3E%3Cpath stroke='%23cad8fd' d='M4 7h2'/%3E%3Cpath stroke='%23b6cefb' d='M11 7h1m0 1h1'/%3E%3Cpath stroke='%23bacbf4' d='M14 7h1'/%3E%3Cpath stroke='%23a0b5d3' d='M16 7h1m-1 1h1m-1 5h1'/%3E%3Cpath stroke='%23c1d3fb' d='M8 8h1'/%3E%3Cpath stroke='%23b6cdfb' d='M13 8h1m-5 5h1'/%3E%3Cpath stroke='%23b9cbf3' d='M14 8h1'/%3E%3Cpath stroke='%23b4c8f6' d='M2 9h1'/%3E%3Cpath stroke='%23c2d5fc' d='M8 9h1m-1 1h1m-3 1h2'/%3E%3Cpath stroke='%23bdd3fb' d='M9 9h1m-2 3h1'/%3E%3Cpath stroke='%23b5cdfa' d='M13 9h1'/%3E%3Cpath stroke='%23b5c9f3' d='M14 9h1'/%3E%3Cpath stroke='%239fb5d2' d='M16 9h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23b1c7f6' d='M2 10h1'/%3E%3Cpath stroke='%23c3d5fd' d='M7 10h1'/%3E%3Cpath stroke='%23bad4fc' d='M9 10h1m-1 1h1'/%3E%3Cpath stroke='%23b2cffb' d='M10 10h1m1 0h1m-2 2h1'/%3E%3Cpath stroke='%23b1cbfa' d='M13 10h1'/%3E%3Cpath stroke='%23b3c8f5' d='M14 10h1m-6 4h2'/%3E%3Cpath stroke='%23adc3f6' 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			}
			
			: :-webkit-scrollbar-button: vertical: end{
				height: 17px;
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			}
			
			: :-webkit-scrollbar-button: horizontal: start{
				width: 17px;
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15h1'/%3E%3Cpath stroke='%23aec4e5' d='M15 15h1'/%3E%3Cpath stroke='%23edf1f3' d='M0 16h1'/%3E%3Cpath stroke='%23aac0e1' d='M1 16h1'/%3E%3Cpath stroke='%2394b1d9' d='M2 16h1'/%3E%3Cpath stroke='%2388a7d8' d='M3 16h1'/%3E%3Cpath stroke='%2383a4d3' d='M4 16h1'/%3E%3Cpath stroke='%237da0d4' d='M5 16h1m4 0h3'/%3E%3Cpath stroke='%237e9fd2' d='M6 16h1'/%3E%3Cpath stroke='%237c9fd3' d='M7 16h3'/%3E%3Cpath stroke='%2382a4d6' d='M13 16h1'/%3E%3Cpath stroke='%2394b0dd' d='M14 16h1'/%3E%3Cpath stroke='%23ecf2f7' d='M15 16h1'/%3E%3C/svg%3E")
			}
			
			: :-webkit-scrollbar-button: horizontal: end{
				width: 17px;
				background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 17 17' shape-rendering='crispEdges'%3E%3Cpath stroke='%23eeede5' d='M0 0h17m-1 1h1m-1 14h1m-1 1h1'/%3E%3Cpath stroke='%23fdfdfa' d='M0 1h1'/%3E%3Cpath stroke='%23fff' d='M1 1h15M0 2h1m14 0h1M0 3h1m14 0h1M0 4h1m14 0h1M0 5h1m14 0h1M0 6h1m14 0h1M0 7h1m14 0h1M0 8h1m14 0h1M0 9h1m14 0h1M0 10h1m14 0h1M0 11h1m14 0h1M0 12h1m14 0h1M0 13h1m14 0h1M0 14h1m14 0h1M1 15h14'/%3E%3Cpath stroke='%23e6eefc' d='M1 2h1'/%3E%3Cpath stroke='%23d0dffc' d='M2 2h1M1 3h1'/%3E%3Cpath stroke='%23cad8f9' d='M3 2h1M1 4h1'/%3E%3Cpath stroke='%23c4d2f7' d='M4 2h1'/%3E%3Cpath stroke='%23c0d0f7' d='M5 2h1'/%3E%3Cpath stroke='%23bdcef7' d='M6 2h1M1 7h1'/%3E%3Cpath stroke='%23bbcdf5' d='M7 2h2'/%3E%3Cpath stroke='%23b8cbf6' d='M9 2h1M1 8h1'/%3E%3Cpath stroke='%23b7caf5' d='M10 2h1'/%3E%3Cpath stroke='%23b5c8f7' d='M11 2h1'/%3E%3Cpath stroke='%23b3c7f5' d='M12 2h1'/%3E%3Cpath stroke='%23afc5f4' d='M13 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			}
			
			.window{
				box-shadow: inset -1px -1px #00138c,inset 1px 1px #0831d9,inset -2px -2px #001ea0,inset 2px 2px #166aee,inset -3px -3px #003bda,inset 3px 3px #0855dd;
				border-top-left-radius: 8px;
				border-top-right-radius: 8px;
				padding: 0 0 3px;
				-webkit-font-smoothing: antialiased
			}
			
			.title-bar{
				background: linear-gradient(180deg,#0997ff,#0053ee 8%,#0050ee 40%,#06f 88%,#06f 93%,#005bff 95%,#003dd7 96%,#003dd7);
				padding: 3px 5px 3px 3px;
				border-top: 1px solid #0831d9;
				border-left: 1px solid #0831d9;
				border-right: 1px solid #001ea0;
				border-top-left-radius: 8px;
				border-top-right-radius: 7px;
				font-size: 13px;
				text-shadow: 1px 1px #0f1089;
				height: 21px
			}
			
			.title-bar-text{
				padding-left: 3px
			}
			
			.title-bar-controls{
				display: flex
			}
			
			.title-bar-controls button{
				min-width: 21px;
				min-height: 21px;
				margin-left: 2px;
				background-repeat: no-repeat;
				background-position: 50%;
				box-shadow: none;
				background-color: #0050ee;
				transition: background .1s;
				border: none
			}
			
			.title-bar-controls button: active,.title-bar-controls button: focus,.title-bar-controls button: hover{
				box-shadow: none!important
			}
			
			.title-bar-controls button[aria-label=Minimize]{
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stroke='%239e3217' d='M2 10h1'/%3E%3Cpath stroke='%23b4381a' d='M3 10h1'/%3E%3Cpath stroke='%23df9a87' d='M10 10h1m-2 1h1m-2 2h1'/%3E%3Cpath stroke='%23c6441f' d='M13 10h1m3 0h1m-8 3h1m-1 3h1'/%3E%3Cpath stroke='%23c74520' d='M14 10h2m-6 4h1m-1 1h1m7 2h1m-7 1h1m4 0h1'/%3E%3Cpath stroke='%23c7451f' d='M16 10h1m1 2h1'/%3E%3Cpath stroke='%237b2711' d='M1 11h1'/%3E%3Cpath stroke='%23a13217' d='M2 11h1'/%3E%3Cpath stroke='%23b7391a' d='M3 11h1'/%3E%3Cpath stroke='%23e09b88' d='M11 11h1'/%3E%3Cpath stroke='%23e29d89' d='M12 11h1'/%3E%3Cpath stroke='%23c94621' d='M13 11h1m-3 2h1'/%3E%3Cpath stroke='%23ca4721' d='M14 11h1m2 1h1m-7 2h1m-1 1h1m0 2h1m2 1h1'/%3E%3Cpath stroke='%23ca4821' d='M15 11h1m1 6h1'/%3E%3Cpath stroke='%23c94620' d='M16 11h1m1 3h1m-8 2h1m6 0h1'/%3E%3Cpath stroke='%23c84620' d='M17 11h1m0 2h1'/%3E%3Cpath stroke='%23a53418' d='M2 12h1'/%3E%3Cpath stroke='%23b83a1b' d='M3 12h1'/%3E%3Cpath stroke='%23e19d89' d='M11 12h1'/%3E%3Cpath stroke='%23e39e89' d='M12 12h1'/%3E%3Cpath stroke='%23e0947c' d='M13 12h1'/%3E%3Cpath stroke='%23cc4a22' d='M14 12h1m-3 2h1m4 0h1m-6 1h1'/%3E%3Cpath stroke='%23cd4a22' d='M15 12h1m0 1h1m0 2h1m-5 1h1m1 1h1'/%3E%3Cpath stroke='%23cb4922' d='M16 12h1m0 1h1m-5 4h1'/%3E%3Cpath stroke='%23c3411e' d='M19 12h1m-1 1h1m-1 4h1m-8 2h2m3 0h1'/%3E%3Cpath stroke='%23a93618' d='M2 13h1'/%3E%3Cpath stroke='%23dd9987' d='M7 13h1m-2 2h1'/%3E%3Cpath stroke='%23e39f8a' d='M12 13h1'/%3E%3Cpath stroke='%23e59f8b' d='M13 13h1'/%3E%3Cpath stroke='%23e5a08b' d='M14 13h1m-2 1h1'/%3E%3Cpath stroke='%23ce4c23' d='M15 13h1m0 3h1'/%3E%3Cpath stroke='%23882b13' d='M1 14h1'/%3E%3Cpath stroke='%23e6a08b' d='M14 14h1'/%3E%3Cpath stroke='%23e6a18b' d='M15 14h1m-2 1h1'/%3E%3Cpath stroke='%23ce4b23' d='M16 14h1m-4 1h1'/%3E%3Cpath stroke='%238b2c14' d='M1 15h1m-1 1h1'/%3E%3Cpath stroke='%23ac3619' d='M2 15h1'/%3E%3Cpath stroke='%23d76b48' d='M15 15h1'/%3E%3Cpath stroke='%23cf4c23' d='M16 15h1m-2 1h1'/%3E%3Cpath stroke='%23c94721' d='M18 15h1m-3 3h1'/%3E%3Cpath stroke='%23bb3c1b' d='M3 16h1'/%3E%3Cpath stroke='%23bf3e1d' d='M6 16h1'/%3E%3Cpath stroke='%23cb4821' d='M12 16h1'/%3E%3Cpath stroke='%23cd4b23' d='M14 16h1'/%3E%3Cpath stroke='%23cc4922' d='M17 16h1m-4 1h1m1 0h1'/%3E%3Cpath stroke='%238d2d14' d='M1 17h1'/%3E%3Cpath stroke='%23bc3c1b' d='M3 17h1m-1 1h1'/%3E%3Cpath stroke='%23c84520' d='M11 17h1m1 1h1'/%3E%3Cpath stroke='%23ae3719' d='M2 18h1'/%3E%3Cpath stroke='%23c94720' d='M14 18h1'/%3E%3Cpath stroke='%23c95839' d='M19 18h1'/%3E%3Cpath stroke='%23a7bdf0' d='M0 19h1m0 1h1'/%3E%3Cpath stroke='%23ead7d3' d='M1 19h1'/%3E%3Cpath stroke='%23b34e35' d='M2 19h1'/%3E%3Cpath stroke='%23c03e1c' d='M8 19h1'/%3E%3Cpath stroke='%23c9583a' d='M18 19h1'/%3E%3Cpath stroke='%23f3dbd4' d='M19 19h1'/%3E%3Cpath stroke='%23a7bcef' d='M20 19h1m-2 1h1'/%3E%3C/svg%3E")
			}
			
			.status-bar{
				margin: 0 3px;
				box-shadow: inset 0 1px 2px grey;
				padding: 2px 1px;
				gap: 0
			}
			
			.status-bar-field{
				-webkit-font-smoothing: antialiased;
				box-shadow: none;
				padding: 1px 2px;
				border-right: 1px solid rgba(208,206,191,.75);
				border-left: 1px solid hsla(0,0%,100%,.75)
			}
			
			.status-bar-field: first-of-type{
				border-left: none
			}
			
			.status-bar-field: last-of-type{
				border-right: none
			}
			
			button{
				-webkit-font-smoothing: antialiased;
				box-sizing: border-box;
				border: 1px solid #003c74;
				background: linear-gradient(180deg,#fff,#ecebe5 86%,#d8d0c4);
				box-shadow: none;
				border-radius: 3px
			}
			
			button: not(: disabled).active,button: not(: disabled): active{
				box-shadow: none;
				background: linear-gradient(180deg,#cdcac3,#e3e3db 8%,#e5e5de 94%,#f2f2f1)
			}
			
			button: not(: disabled): hover{
				box-shadow: inset -1px 1px #fff0cf,inset 1px 2px #fdd889,inset -2px 2px #fbc761,inset 2px -2px #e5a01a
			}
			
			button.focused,button: focus{
				box-shadow: inset -1px 1px #cee7ff,inset 1px 2px #98b8ea,inset -2px 2px #bcd4f6,inset 1px -1px #89ade4,inset 2px -2px #89ade4
			}
			
			button: :-moz-focus-inner{
				border: 0
			}
			
			input,label,option,select,textarea{
				-webkit-font-smoothing: antialiased
			}
			
			input[type=radio]{
				appearance: none;
				-webkit-appearance: none;
				-moz-appearance: none;
				margin: 0;
				background: 0;
				position: fixed;
				opacity: 0;
				border: none
			}
			
			input[type=radio]+label{
				line-height: 16px
			}
			
			input[type=radio]+label: before{
				background: linear-gradient(135deg,#dcdcd7,#fff);
				border-radius: 50%;
				border: 1px solid #1d5281
			}
			
			input[type=radio]: not([disabled]): not(: active)+label: hover: before{
				box-shadow: inset -2px -2px #f8b636,inset 2px 2px #fedf9c
			}
			
			input[type=radio]: active+label: before{
				background: linear-gradient(135deg,#b0b0a7,#e3e1d2)
			}
			
			input[type=radio]: checked+label: after{
				background: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 5 5' shape-rendering='crispEdges'%3E%3Cpath stroke='%23a9dca6' d='M1 0h1M0 1h1'/%3E%3Cpath stroke='%234dbf4a' d='M2 0h1M0 2h1'/%3E%3Cpath stroke='%23a0d29e' d='M3 0h1M0 3h1'/%3E%3Cpath stroke='%2355d551' d='M1 1h1'/%3E%3Cpath stroke='%2343c33f' d='M2 1h1'/%3E%3Cpath stroke='%2329a826' d='M3 1h1'/%3E%3Cpath stroke='%239acc98' d='M4 1h1M1 4h1'/%3E%3Cpath stroke='%2342c33f' d='M1 2h1'/%3E%3Cpath stroke='%2338b935' d='M2 2h1'/%3E%3Cpath stroke='%2321a121' d='M3 2h1'/%3E%3Cpath stroke='%23269623' d='M4 2h1'/%3E%3Cpath stroke='%232aa827' d='M1 3h1'/%3E%3Cpath stroke='%2322a220' d='M2 3h1'/%3E%3Cpath stroke='%23139210' d='M3 3h1'/%3E%3Cpath stroke='%2398c897' d='M4 3h1'/%3E%3Cpath stroke='%23249624' d='M2 4h1'/%3E%3Cpath stroke='%2398c997' d='M3 4h1'/%3E%3C/svg%3E")
			}
			
			input[type=radio]: focus+label{
				outline: 1px dotted #000
			}
			
			input[type=radio][disabled]+label: before{
				border: 1px solid #cac8bb;
				background: #fff
			}
			
			input[type=radio][disabled]: checked+label: after{
				background: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 5 5' shape-rendering='crispEdges'%3E%3Cpath stroke='%23e8e6da' d='M1 0h1M0 1h1'/%3E%3Cpath stroke='%23d2ceb5' d='M2 0h1M0 2h1'/%3E%3Cpath stroke='%23e5e3d4' d='M3 0h1M0 3h1'/%3E%3Cpath stroke='%23d7d3bd' d='M1 1h1'/%3E%3Cpath stroke='%23d0ccb2' d='M2 1h1M1 2h1'/%3E%3Cpath stroke='%23c7c2a2' d='M3 1h1M1 3h1'/%3E%3Cpath stroke='%23e2dfd0' d='M4 1h1M1 4h1'/%3E%3Cpath stroke='%23cdc8ac' d='M2 2h1'/%3E%3Cpath stroke='%23c5bf9f' d='M3 2h1M2 3h1'/%3E%3Cpath stroke='%23c3bd9c' d='M4 2h1'/%3E%3Cpath stroke='%23bfb995' d='M3 3h1'/%3E%3Cpath stroke='%23e2dfcf' d='M4 3h1M3 4h1'/%3E%3Cpath stroke='%23c4be9d' d='M2 4h1'/%3E%3C/svg%3E")
			}
			
			input[type=email],input[type=password],textarea: :selection{
				background: #2267cb;
				color: #fff
			}
			
			input[type=range]: :-webkit-slider-thumb{
				height: 21px;
				width: 11px;
				background: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 11 21' shape-rendering='crispEdges'%3E%3Cpath stroke='%23becbd3' d='M1 0h1M0 1h1'/%3E%3Cpath stroke='%23b6c5cd' d='M2 0h1M0 2h1'/%3E%3Cpath stroke='%23b5c4cd' d='M3 0h5M0 3h1M0 4h1M0 5h1M0 6h1M0 7h1M0 8h1M0 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23afbfc8' d='M8 0h1M0 14h1'/%3E%3Cpath stroke='%239fb2be' d='M9 0h1M0 15h1'/%3E%3Cpath stroke='%23a6d1b1' d='M1 1h1'/%3E%3Cpath stroke='%236fd16e' d='M2 1h1M1 2h1'/%3E%3Cpath stroke='%2367ce65' d='M3 1h1M1 3h1'/%3E%3Cpath stroke='%2366ce64' d='M4 1h3'/%3E%3Cpath stroke='%2362cd61' d='M7 1h1'/%3E%3Cpath stroke='%2345c343' d='M8 1h1M7 2h1'/%3E%3Cpath stroke='%2363ac76' d='M9 1h1M2 16h1m0 1h1m0 1h1'/%3E%3Cpath stroke='%23879aa6' d='M10 1h1'/%3E%3Cpath stroke='%2363cd62' d='M2 2h1'/%3E%3Cpath stroke='%2349c547' d='M3 2h1M2 3h1'/%3E%3Cpath stroke='%2347c446' d='M4 2h3'/%3E%3Cpath stroke='%2321b71f' d='M8 2h1'/%3E%3Cpath stroke='%231da41c' d='M9 2h1'/%3E%3Cpath stroke='%237d8e99' d='M10 2h1'/%3E%3Cpath stroke='%2325b923' d='M3 3h1'/%3E%3Cpath stroke='%2321b81f' d='M4 3h4M2 15h1'/%3E%3Cpath stroke='%231ea71c' d='M8 3h1'/%3E%3Cpath stroke='%231b9619' d='M9 3h1'/%3E%3Cpath stroke='%23778892' d='M10 3h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f7f7f4' d='M1 4h1M1 5h1M1 6h1M1 7h1M1 8h1M1 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f5f5f2' d='M2 4h1M2 5h1M2 6h1M2 7h1M2 8h1M2 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f3f3ef' d='M3 4h5M3 5h5M3 6h5M3 7h5M3 8h5M3 9h5m-5 1h5m-5 1h5m-5 1h5m-5 1h4m-4 1h3m-2 1h1'/%3E%3Cpath stroke='%23dcdcd9' d='M8 4h1M8 5h1M8 6h1M8 7h1M8 8h1M8 9h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23c3c3c0' d='M9 4h1M9 5h1M9 6h1M9 7h1M9 8h1M9 9h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f1f1ed' d='M7 13h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%23dbdbd8' d='M8 13h1'/%3E%3Cpath stroke='%23c4c4c1' d='M9 13h1'/%3E%3Cpath stroke='%234bc549' d='M1 14h1'/%3E%3Cpath stroke='%23f4f4f1' d='M2 14h1'/%3E%3Cpath stroke='%23e6e6e2' d='M7 14h1m-2 1h1'/%3E%3Cpath stroke='%23cececa' d='M8 14h1'/%3E%3Cpath stroke='%231a9319' d='M9 14h1'/%3E%3Cpath stroke='%23788993' d='M10 14h1'/%3E%3Cpath stroke='%2369b17b' d='M1 15h1'/%3E%3Cpath stroke='%23f2f2ee' d='M3 15h1m0 1h1'/%3E%3Cpath stroke='%23d0d0cc' d='M7 15h1m-2 1h1'/%3E%3Cpath stroke='%231a9118' d='M8 15h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%234c845a' d='M9 15h1'/%3E%3Cpath stroke='%2372838d' d='M10 15h1'/%3E%3Cpath stroke='%2391a6b2' d='M1 16h1m0 1h1m0 1h1m0 1h1'/%3E%3Cpath stroke='%2321b61f' d='M3 16h1m0 1h1'/%3E%3Cpath stroke='%23e7e7e3' d='M5 16h1'/%3E%3Cpath stroke='%234b8259' d='M8 16h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%236e7e88' d='M9 16h1m-2 1h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%23d7d7d4' d='M5 17h1'/%3E%3Cpath stroke='%231da21b' d='M5 18h1'/%3E%3Cpath stroke='%23589868' d='M5 19h1'/%3E%3Cpath stroke='%2380929e' d='M5 20h1'/%3E%3C/svg%3E");
				transform: translateY(-8px)
			}
			
			input[type=range]: :-moz-range-thumb{
				height: 21px;
				width: 11px;
				border: 0;
				border-radius: 0;
				background: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 11 21' shape-rendering='crispEdges'%3E%3Cpath stroke='%23becbd3' d='M1 0h1M0 1h1'/%3E%3Cpath stroke='%23b6c5cd' d='M2 0h1M0 2h1'/%3E%3Cpath stroke='%23b5c4cd' d='M3 0h5M0 3h1M0 4h1M0 5h1M0 6h1M0 7h1M0 8h1M0 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23afbfc8' d='M8 0h1M0 14h1'/%3E%3Cpath stroke='%239fb2be' d='M9 0h1M0 15h1'/%3E%3Cpath stroke='%23a6d1b1' d='M1 1h1'/%3E%3Cpath stroke='%236fd16e' d='M2 1h1M1 2h1'/%3E%3Cpath stroke='%2367ce65' d='M3 1h1M1 3h1'/%3E%3Cpath stroke='%2366ce64' d='M4 1h3'/%3E%3Cpath stroke='%2362cd61' d='M7 1h1'/%3E%3Cpath stroke='%2345c343' d='M8 1h1M7 2h1'/%3E%3Cpath stroke='%2363ac76' d='M9 1h1M2 16h1m0 1h1m0 1h1'/%3E%3Cpath stroke='%23879aa6' d='M10 1h1'/%3E%3Cpath stroke='%2363cd62' d='M2 2h1'/%3E%3Cpath stroke='%2349c547' d='M3 2h1M2 3h1'/%3E%3Cpath stroke='%2347c446' d='M4 2h3'/%3E%3Cpath stroke='%2321b71f' d='M8 2h1'/%3E%3Cpath stroke='%231da41c' d='M9 2h1'/%3E%3Cpath stroke='%237d8e99' d='M10 2h1'/%3E%3Cpath stroke='%2325b923' d='M3 3h1'/%3E%3Cpath stroke='%2321b81f' d='M4 3h4M2 15h1'/%3E%3Cpath stroke='%231ea71c' d='M8 3h1'/%3E%3Cpath stroke='%231b9619' d='M9 3h1'/%3E%3Cpath stroke='%23778892' d='M10 3h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f7f7f4' d='M1 4h1M1 5h1M1 6h1M1 7h1M1 8h1M1 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f5f5f2' d='M2 4h1M2 5h1M2 6h1M2 7h1M2 8h1M2 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f3f3ef' d='M3 4h5M3 5h5M3 6h5M3 7h5M3 8h5M3 9h5m-5 1h5m-5 1h5m-5 1h5m-5 1h4m-4 1h3m-2 1h1'/%3E%3Cpath stroke='%23dcdcd9' d='M8 4h1M8 5h1M8 6h1M8 7h1M8 8h1M8 9h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23c3c3c0' d='M9 4h1M9 5h1M9 6h1M9 7h1M9 8h1M9 9h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f1f1ed' d='M7 13h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%23dbdbd8' d='M8 13h1'/%3E%3Cpath stroke='%23c4c4c1' d='M9 13h1'/%3E%3Cpath stroke='%234bc549' d='M1 14h1'/%3E%3Cpath stroke='%23f4f4f1' d='M2 14h1'/%3E%3Cpath stroke='%23e6e6e2' d='M7 14h1m-2 1h1'/%3E%3Cpath stroke='%23cececa' d='M8 14h1'/%3E%3Cpath stroke='%231a9319' d='M9 14h1'/%3E%3Cpath stroke='%23788993' d='M10 14h1'/%3E%3Cpath stroke='%2369b17b' d='M1 15h1'/%3E%3Cpath stroke='%23f2f2ee' d='M3 15h1m0 1h1'/%3E%3Cpath stroke='%23d0d0cc' d='M7 15h1m-2 1h1'/%3E%3Cpath stroke='%231a9118' d='M8 15h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%234c845a' d='M9 15h1'/%3E%3Cpath stroke='%2372838d' d='M10 15h1'/%3E%3Cpath stroke='%2391a6b2' d='M1 16h1m0 1h1m0 1h1m0 1h1'/%3E%3Cpath stroke='%2321b61f' d='M3 16h1m0 1h1'/%3E%3Cpath stroke='%23e7e7e3' d='M5 16h1'/%3E%3Cpath stroke='%234b8259' d='M8 16h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%236e7e88' d='M9 16h1m-2 1h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%23d7d7d4' d='M5 17h1'/%3E%3Cpath stroke='%231da21b' d='M5 18h1'/%3E%3Cpath stroke='%23589868' d='M5 19h1'/%3E%3Cpath stroke='%2380929e' d='M5 20h1'/%3E%3C/svg%3E");
				transform: translateY(2px)
			}
			
			input[type=range]: :-webkit-slider-runnable-track{
				width: 100%;
				height: 2px;
				box-sizing: border-box;
				background: #ecebe4;
				border-right: 1px solid #f3f2ea;
				border-bottom: 1px solid #f3f2ea;
				border-radius: 2px;
				box-shadow: 1px 0 0 #fff,1px 1px 0 #fff,0 1px 0 #fff,-1px 0 0 #9d9c99,-1px -1px 0 #9d9c99,0 -1px 0 #9d9c99,-1px 1px 0 #fff,1px -1px #9d9c99
			}
			
			input[type=range]: :-moz-range-track{
				width: 100%;
				height: 2px;
				box-sizing: border-box;
				background: #ecebe4;
				border-right: 1px solid #f3f2ea;
				border-bottom: 1px solid #f3f2ea;
				border-radius: 2px;
				box-shadow: 1px 0 0 #fff,1px 1px 0 #fff,0 1px 0 #fff,-1px 0 0 #9d9c99,-1px -1px 0 #9d9c99,0 -1px 0 #9d9c99,-1px 1px 0 #fff,1px -1px #9d9c99
			}
			
			input[type=range].has-box-indicator: :-webkit-slider-thumb{
				background: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 11 22' shape-rendering='crispEdges'%3E%3Cpath stroke='%23f2f1e7' d='M0 0h1m9 0h1M0 21h1m9 0h1'/%3E%3Cpath stroke='%23879aa6' d='M1 0h1m8 20h1'/%3E%3Cpath stroke='%237d8e99' d='M2 0h1m7 19h1'/%3E%3Cpath stroke='%23778892' d='M3 0h5m2 3h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23788993' d='M8 0h1m1 2h1'/%3E%3Cpath stroke='%2372838d' d='M9 0h1m0 1h1'/%3E%3Cpath stroke='%239fb2be' d='M0 1h1m8 20h1'/%3E%3Cpath stroke='%2363af76' d='M1 1h1m7 19h1'/%3E%3Cpath stroke='%231eab1c' d='M2 1h1m6 18h1'/%3E%3Cpath stroke='%231c9d1a' d='M3 1h1'/%3E%3Cpath stroke='%231b9a1a' d='M4 1h3m1 0h1m0 1h1'/%3E%3Cpath stroke='%231b9b1a' d='M7 1h1'/%3E%3Cpath stroke='%234d875b' d='M9 1h1'/%3E%3Cpath stroke='%23afbfc8' d='M0 2h1m7 19h1'/%3E%3Cpath stroke='%2346ca44' d='M1 2h1m5 17h1m0 1h1'/%3E%3Cpath stroke='%2322be20' d='M2 2h1m5 17h1'/%3E%3Cpath stroke='%231faf1d' d='M3 2h1'/%3E%3Cpath stroke='%231fae1d' d='M4 2h3'/%3E%3Cpath stroke='%231fad1d' d='M7 2h1'/%3E%3Cpath stroke='%231da11b' d='M8 2h1'/%3E%3Cpath stroke='%23b5c4cd' d='M0 3h1M0 4h1M0 5h1M0 6h1M0 7h1M0 8h1M0 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m2 3h5'/%3E%3Cpath stroke='%23f7f7f4' d='M1 3h1M1 4h1M1 5h1M1 6h1M1 7h1M1 8h1M1 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f5f5f2' d='M2 3h1M2 4h1M2 5h1M2 6h1M2 7h1M2 8h1M2 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f3f3ef' d='M3 3h4M3 4h5M3 5h5M3 6h5M3 7h5M3 8h5M3 9h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5'/%3E%3Cpath stroke='%23f1f1ed' d='M7 3h1'/%3E%3Cpath stroke='%23dbdbd8' d='M8 3h1'/%3E%3Cpath stroke='%23c4c4c1' d='M9 3h1'/%3E%3Cpath stroke='%23ddddd9' d='M8 4h1M8 18h1'/%3E%3Cpath stroke='%23c6c6c3' d='M9 4h1M9 18h1'/%3E%3Cpath stroke='%23dcdcd9' d='M8 5h1M8 6h1M8 7h1M8 8h1M8 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23c3c3c0' d='M9 5h1M9 6h1M9 7h1M9 8h1M9 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23b6c5cd' d='M0 19h1m1 2h1'/%3E%3Cpath stroke='%2370d66f' d='M1 19h1m0 1h1'/%3E%3Cpath stroke='%2364d362' d='M2 19h1'/%3E%3Cpath stroke='%234acb48' d='M3 19h1'/%3E%3Cpath stroke='%2348cb46' d='M4 19h3'/%3E%3Cpath stroke='%23becbd3' d='M0 20h1m0 1h1'/%3E%3Cpath stroke='%23a6d2b1' d='M1 20h1'/%3E%3Cpath stroke='%2367d466' d='M3 20h1'/%3E%3Cpath stroke='%2366d465' d='M4 20h3'/%3E%3Cpath stroke='%2363d362' d='M7 20h1'/%3E%3C/svg%3E");transform: translateY(-10px)
			}
			
			input[type=range].has-box-indicator: :-moz-range-thumb{
				background: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 11 22' shape-rendering='crispEdges'%3E%3Cpath stroke='%23f2f1e7' d='M0 0h1m9 0h1M0 21h1m9 0h1'/%3E%3Cpath stroke='%23879aa6' d='M1 0h1m8 20h1'/%3E%3Cpath stroke='%237d8e99' d='M2 0h1m7 19h1'/%3E%3Cpath stroke='%23778892' d='M3 0h5m2 3h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23788993' d='M8 0h1m1 2h1'/%3E%3Cpath stroke='%2372838d' d='M9 0h1m0 1h1'/%3E%3Cpath stroke='%239fb2be' d='M0 1h1m8 20h1'/%3E%3Cpath stroke='%2363af76' d='M1 1h1m7 19h1'/%3E%3Cpath stroke='%231eab1c' d='M2 1h1m6 18h1'/%3E%3Cpath stroke='%231c9d1a' d='M3 1h1'/%3E%3Cpath stroke='%231b9a1a' d='M4 1h3m1 0h1m0 1h1'/%3E%3Cpath stroke='%231b9b1a' d='M7 1h1'/%3E%3Cpath stroke='%234d875b' d='M9 1h1'/%3E%3Cpath stroke='%23afbfc8' d='M0 2h1m7 19h1'/%3E%3Cpath stroke='%2346ca44' d='M1 2h1m5 17h1m0 1h1'/%3E%3Cpath stroke='%2322be20' d='M2 2h1m5 17h1'/%3E%3Cpath stroke='%231faf1d' d='M3 2h1'/%3E%3Cpath stroke='%231fae1d' d='M4 2h3'/%3E%3Cpath stroke='%231fad1d' d='M7 2h1'/%3E%3Cpath stroke='%231da11b' d='M8 2h1'/%3E%3Cpath stroke='%23b5c4cd' d='M0 3h1M0 4h1M0 5h1M0 6h1M0 7h1M0 8h1M0 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m2 3h5'/%3E%3Cpath stroke='%23f7f7f4' d='M1 3h1M1 4h1M1 5h1M1 6h1M1 7h1M1 8h1M1 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f5f5f2' d='M2 3h1M2 4h1M2 5h1M2 6h1M2 7h1M2 8h1M2 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f3f3ef' d='M3 3h4M3 4h5M3 5h5M3 6h5M3 7h5M3 8h5M3 9h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5'/%3E%3Cpath stroke='%23f1f1ed' d='M7 3h1'/%3E%3Cpath stroke='%23dbdbd8' d='M8 3h1'/%3E%3Cpath stroke='%23c4c4c1' d='M9 3h1'/%3E%3Cpath stroke='%23ddddd9' d='M8 4h1M8 18h1'/%3E%3Cpath stroke='%23c6c6c3' d='M9 4h1M9 18h1'/%3E%3Cpath stroke='%23dcdcd9' d='M8 5h1M8 6h1M8 7h1M8 8h1M8 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23c3c3c0' d='M9 5h1M9 6h1M9 7h1M9 8h1M9 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23b6c5cd' d='M0 19h1m1 2h1'/%3E%3Cpath stroke='%2370d66f' d='M1 19h1m0 1h1'/%3E%3Cpath stroke='%2364d362' d='M2 19h1'/%3E%3Cpath stroke='%234acb48' d='M3 19h1'/%3E%3Cpath stroke='%2348cb46' d='M4 19h3'/%3E%3Cpath stroke='%23becbd3' d='M0 20h1m0 1h1'/%3E%3Cpath stroke='%23a6d2b1' d='M1 20h1'/%3E%3Cpath stroke='%2367d466' d='M3 20h1'/%3E%3Cpath stroke='%2366d465' d='M4 20h3'/%3E%3Cpath stroke='%2363d362' d='M7 20h1'/%3E%3C/svg%3E");transform: translateY(0)
			}
			
			.is-vertical>input[type=range]: :-webkit-slider-runnable-track{
				border-left: 1px solid #f3f2ea;
				border-right: 0;
				border-bottom: 1px solid #f3f2ea;
				box-shadow: -1px 0 0 #fff,-1px 1px 0 #fff,0 1px 0 #fff,1px 0 0 #9d9c99,1px -1px 0 #9d9c99,0 -1px 0 #9d9c99,1px 1px 0 #fff,-1px -1px #9d9c99
			}
			
			.is-vertical>input[type=range]: :-moz-range-track{
				border-left: 1px solid #f3f2ea;
				border-right: 0;
				border-bottom: 1px solid #f3f2ea;
				box-shadow: -1px 0 0 #fff,-1px 1px 0 #fff,0 1px 0 #fff,1px 0 0 #9d9c99,1px -1px 0 #9d9c99,0 -1px 0 #9d9c99,1px 1px 0 #fff,-1px -1px #9d9c99
			}
			
			fieldset{
				box-shadow: none;
				background: #fff;
				border: 1px solid #d0d0bf;
				border-radius: 4px;
				padding-top: 10px
			}
			
			legend{
				background: transparent;
				color: #0046d5
			}
			
			.field-row{
				display: flex;
				align-items: center
			}
			
			.field-row>*+*{
				margin-left: 6px
			}
			
			[class^=field-row]+[class^=field-row]{
				margin-top: 6px
			}
			
			.field-row-stacked{
				display: flex;
				flex-direction: column
			}
			
			.field-row-stacked *+*{
				margin-top: 6px
			}
			
			menu[role=tablist] button{
				background: linear-gradient(180deg,#fff,#fafaf9 26%,#f0f0ea 95%,#ecebe5);
				margin-left: -1px;
				margin-right: 2px;
				border-radius: 0;
				border-color: #91a7b4;
				border-top-right-radius: 3px;
				border-top-left-radius: 3px;
				padding: 0 12px 3px
			}
			
			menu[role=tablist] button: hover{
				box-shadow: unset;
				border-top: 1px solid #e68b2c;
				box-shadow: inset 0 2px #ffc73c
			}
			
			menu[role=tablist] button[aria-selected=true]{
				border-color: #919b9c;
				margin-right: -1px;
				border-bottom: 1px solid transparent;
				border-top: 1px solid #e68b2c;
				box-shadow: inset 0 2px #ffc73c
			}
			
			menu[role=tablist] button[aria-selected=true]: first-of-type: before{
				content: "";
				display: block;
				position: absolute;
				z-index: -1;
				top: 100%;
				left: -1px;
				height: 2px;
				width: 0;
				border-left: 1px solid #919b9c
			}
			
			[role=tabpanel]{
				box-shadow: inset 1px 1px #fcfcfe,inset -1px -1px #fcfcfe,1px 2px 2px 0 rgba(208,206,191,.75)
			}
			
			ul.tree-view{
				-webkit-font-smoothing: auto;
				border: 1px solid #7f9db9;
				padding: 2px 5px
			}
			
			@keyframes sliding{
				0%{
					transform: translateX(-30px)
				}
			
				to{
					transform: translateX(100%)
				}
			}
			
			progress{
				box-sizing: border-box;
				appearance: none;
				-webkit-appearance: none;
				-moz-appearance: none;
				height: 14px;
				border: 1px solid #686868;
				border-radius: 4px;
				padding: 1px 2px 1px 0;
				overflow: hidden;
				background-color: #fff;
				-webkit-box-shadow: inset 0 0 1px 0 #686868;
				-moz-box-shadow: inset 0 0 1px 0 #686868
			}
			
			progress,progress: not([value]){
				box-shadow: inset 0 0 1px 0 #686868
			}
			
			progress: not([value]){
				-moz-box-shadow: inset 0 0 1px 0 #686868;
				-webkit-box-shadow: inset 0 0 1px 0 #686868;
				height: 14px
			}
			
			progress[value]: :-webkit-progress-bar{
				background-color: transparent
			}
			
			progress[value]: :-webkit-progress-value{
				border-radius: 2px;
				background: repeating-linear-gradient(90deg,#fff 0,#fff 2px,transparent 0,transparent 10px),linear-gradient(180deg,#acedad 0,#7be47d 14%,#4cda50 28%,#2ed330 42%,#42d845 57%,#76e275 71%,#8fe791 85%,#fff)
			}
			
			progress[value]: :-moz-progress-bar{
				border-radius: 2px;
				background: repeating-linear-gradient(90deg,#fff 0,#fff 2px,transparent 0,transparent 10px),linear-gradient(180deg,#acedad 0,#7be47d 14%,#4cda50 28%,#2ed330 42%,#42d845 57%,#76e275 71%,#8fe791 85%,#fff)
			}
			
			progress: not([value]): :-webkit-progress-bar{
				width: 100%;
				background: repeating-linear-gradient(90deg,transparent 0,transparent 8px,#fff 0,#fff 10px,transparent 0,transparent 18px,#fff 0,#fff 20px,transparent 0,transparent 28px,#fff 0,#fff),linear-gradient(180deg,#acedad 0,#7be47d 14%,#4cda50 28%,#2ed330 42%,#42d845 57%,#76e275 71%,#8fe791 85%,#fff);
				animation: sliding 2s linear 0s infinite
			}
			
			progress: not([value]): :-webkit-progress-bar: not([value]){
				animation: sliding 2s linear 0s infinite;
				background: repeating-linear-gradient(90deg,transparent 0,transparent 8px,#fff 0,#fff 10px,transparent 0,transparent 18px,#fff 0,#fff 20px,transparent 0,transparent 28px,#fff 0,#fff),linear-gradient(180deg,#acedad 0,#7be47d 14%,#4cda50 28%,#2ed330 42%,#42d845 57%,#76e275 71%,#8fe791 85%,#fff)
			}
			
			progress: not([value]){
				position: relative
			}
			
			progress: not([value]): before{
				box-sizing: border-box;
				content: "";
				position: absolute;
				top: 0;
				left: 0;
				width: 100%;
				height: 100%;
				background-color: #fff;
				-webkit-box-shadow: inset 0 0 1px 0 #686868;
				-moz-box-shadow: inset 0 0 1px 0 #686868
			}
			
			progress: not([value]): before,progress: not([value]): before: not([value]){
				box-shadow: inset 0 0 1px 0 #686868
			}
			
			progress: not([value]): before: not([value]){
				-moz-box-shadow: inset 0 0 1px 0 #686868;
				-webkit-box-shadow: inset 0 0 1px 0 #686868
			}
			
			progress: not([value]): after{
				box-sizing: border-box;
				content: "";
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			];
			var tab_main_worker_cpu_ram_csv_json = [
			    [
			        1746613817,
			        622.0859375,
			        14
			    ],
			    [
			        1746613821,
			        622.34375,
			        14
			    ],
			    [
			        1746613824,
			        622.34375,
			        14
			    ],
			    [
			        1746613824,
			        622.34375,
			        16.7
			    ],
			    [
			        1746613824,
			        622.34375,
			        13.3
			    ],
			    [
			        1746613824,
			        622.34375,
			        13.6
			    ],
			    [
			        1746613824,
			        622.34375,
			        16.7
			    ],
			    [
			        1746615675,
			        647.9921875,
			        14.1
			    ],
			    [
			        1746615675,
			        647.9921875,
			        14.1
			    ],
			    [
			        1746615675,
			        647.9921875,
			        14.6
			    ],
			    [
			        1746615675,
			        647.9921875,
			        13
			    ],
			    [
			        1746619675,
			        708.21875,
			        12.8
			    ],
			    [
			        1746619675,
			        708.21875,
			        7.2
			    ],
			    [
			        1746619675,
			        708.21875,
			        7.5
			    ],
			    [
			        1746619675,
			        708.21875,
			        3.8
			    ],
			    [
			        1746628462,
			        726.45703125,
			        7.7
			    ],
			    [
			        1746628462,
			        726.45703125,
			        9.1
			    ],
			    [
			        1746628462,
			        726.45703125,
			        8.7
			    ],
			    [
			        1746628462,
			        726.45703125,
			        13.3
			    ],
			    [
			        1746633243,
			        752.13671875,
			        11.6
			    ],
			    [
			        1746633243,
			        752.13671875,
			        17.4
			    ],
			    [
			        1746633243,
			        752.13671875,
			        21.1
			    ],
			    [
			        1746633243,
			        752.13671875,
			        21.7
			    ],
			    [
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			        765.0546875,
			        20.4
			    ],
			    [
			        1746637730,
			        765.0546875,
			        21.2
			    ],
			    [
			        1746637730,
			        765.0546875,
			        23.5
			    ],
			    [
			        1746637730,
			        765.0546875,
			        23.3
			    ],
			    [
			        1746642681,
			        786.328125,
			        18.1
			    ],
			    [
			        1746642681,
			        786.328125,
			        15.4
			    ],
			    [
			        1746642681,
			        786.328125,
			        16.7
			    ],
			    [
			        1746642681,
			        786.328125,
			        17.4
			    ]
			];
			var tab_main_worker_cpu_ram_headers_json = [
			    "timestamp",
			    "ram_usage_mb",
			    "cpu_usage_percent"
			];
			
			"use strict";
			
			function add_default_layout_data (layout, no_height = 0) {
				layout["width"] = get_graph_width();
				if (!no_height) {
					layout["height"] = get_graph_height();
				}
				layout["paper_bgcolor"] = 'rgba(0,0,0,0)';
				layout["plot_bgcolor"] = 'rgba(0,0,0,0)';
			
				return layout;
			}
			
			function get_marker_size() {
				return 12;
			}
			
			function get_text_color() {
				return theme == "dark" ? "white" : "black";
			}
			
			function get_font_size() {
				return 14;
			}
			
			function get_graph_height() {
				return 800;
			}
			
			function get_font_data() {
				return {
					size: get_font_size(),
					color: get_text_color()
				}
			}
			
			function get_axis_title_data(name, axis_type = "") {
				if(axis_type) {
					return {
						text: name,
						type: axis_type,
						font: get_font_data()
					};
				}
			
				return {
					text: name,
					font: get_font_data()
				};
			}
			
			function get_graph_width() {
				var width = document.body.clientWidth || window.innerWidth || document.documentElement.clientWidth;
				return Math.max(800, Math.floor(width * 0.9));
			}
			
			function createTable(data, headers, table_name) {
				if (!$("#" + table_name).length) {
					console.error("#" + table_name + " not found");
					return;
				}
			
				new gridjs.Grid({
					columns: headers,
					data: data,
					search: true,
					sort: true,
					ellipsis: false
				}).render(document.getElementById(table_name));
			
				if (typeof apply_theme_based_on_system_preferences === 'function') {
					apply_theme_based_on_system_preferences();
				}
			
				colorize_table_entries();
			
				add_colorize_to_gridjs_table();
			}
			
			function download_as_file(id, filename) {
				var text = $("#" + id).text();
				var blob = new Blob([text], {
					type: "text/plain"
				});
				var link = document.createElement("a");
				link.href = URL.createObjectURL(blob);
				link.download = filename;
				document.body.appendChild(link);
				link.click();
				document.body.removeChild(link);
			}
			
			function copy_to_clipboard_from_id (id) {
				var text = $("#" + id).text();
			
				copy_to_clipboard(text);
			}
			
			function copy_to_clipboard(text) {
				if (!navigator.clipboard) {
					let textarea = document.createElement("textarea");
					textarea.value = text;
					document.body.appendChild(textarea);
					textarea.select();
					try {
						document.execCommand("copy");
					} catch (err) {
						console.error("Copy failed:", err);
					}
					document.body.removeChild(textarea);
					return;
				}
			
				navigator.clipboard.writeText(text).then(() => {
					console.log("Text copied to clipboard");
				}).catch(err => {
					console.error("Failed to copy text:", err);
				});
			}
			
			function filterNonEmptyRows(data) {
				var new_data = [];
				for (var row_idx = 0; row_idx <  data.length; row_idx++) {
					var line = data[row_idx];
			
					var line_has_empty_data = false;
			
					for (var col_idx = 0; col_idx < line.length; col_idx++) {
						var col_header_name = tab_results_headers_json[col_idx];
						var single_data_point = line[col_idx];
			
						if(single_data_point === "" && !special_col_names.includes(col_header_name)) {
							line_has_empty_data = true;
							continue;
						}
					}
			
					if(!line_has_empty_data) {
						new_data.push(line);
					}
				}
			
				return new_data;
			}
			
			function make_text_in_parallel_plot_nicer() {
				$(".parcoords g > g > text").each(function() {
					if (theme == "dark") {
						$(this)
							.css("text-shadow", "unset")
							.css("font-size", "0.9em")
							.css("fill", "white")
							.css("stroke", "black")
							.css("stroke-width", "2px")
							.css("paint-order", "stroke fill");
					} else {
						$(this)
							.css("text-shadow", "unset")
							.css("font-size", "0.9em")
							.css("fill", "black")
							.css("stroke", "unset")
							.css("stroke-width", "unset")
							.css("paint-order", "stroke fill");
					}
				});
			}
			
			function createParallelPlot(dataArray, headers, resultNames, ignoreColumns = []) {
				if ($("#parallel-plot").data("loaded") == "true") {
					return;
				}
			
				dataArray = filterNonEmptyRows(dataArray);
				const ignoreSet = new Set(ignoreColumns);
				const numericalCols = [];
				const categoricalCols = [];
				const categoryMappings = {};
			
				headers.forEach((header, colIndex) => {
					if (ignoreSet.has(header)) return;
			
					const values = dataArray.map(row => row[colIndex]);
					if (values.every(val => !isNaN(parseFloat(val)))) {
						numericalCols.push({ name: header, index: colIndex });
					} else {
						categoricalCols.push({ name: header, index: colIndex });
						const uniqueValues = [...new Set(values)];
						categoryMappings[header] = Object.fromEntries(uniqueValues.map((val, i) => [val, i]));
					}
				});
			
				const dimensions = [];
			
				numericalCols.forEach(col => {
					dimensions.push({
						label: col.name,
						values: dataArray.map(row => parseFloat(row[col.index])),
						range: [
							Math.min(...dataArray.map(row => parseFloat(row[col.index]))),
							Math.max(...dataArray.map(row => parseFloat(row[col.index])))
						]
					});
				});
			
				categoricalCols.forEach(col => {
					dimensions.push({
						label: col.name,
						values: dataArray.map(row => categoryMappings[col.name][row[col.index]]),
						tickvals: Object.values(categoryMappings[col.name]),
						ticktext: Object.keys(categoryMappings[col.name])
					});
				});
			
				let colorScale = null;
				let colorValues = null;
			
				if (resultNames.length > 1) {
					let selectBox = '<select id="result-select" style="margin-bottom: 10px;">';
					selectBox += '<option value="none">No color</option>';
					var k = 0;
					resultNames.forEach(resultName => {
						var minMax = result_min_max[k];
						if(minMax === undefined) {
							minMax = "min [automatically chosen]"
						}
						selectBox += `<option value="${resultName}">${resultName} (${minMax})</option>`;
						k = k + 1;
					});
					selectBox += '</select>';
					$("#parallel-plot").before(selectBox);
			
					$("#result-select").change(function() {
						const selectedResult = $(this).val();
						if (selectedResult === "none") {
							colorValues = null;
							colorScale = null;
						} else {
							const resultCol = numericalCols.find(col => col.name.toLowerCase() === selectedResult.toLowerCase());
							colorValues = dataArray.map(row => parseFloat(row[resultCol.index]));
			
							let minResult = Math.min(...colorValues);
							let maxResult = Math.max(...colorValues);
			
							var _result_min_max_idx = result_names.indexOf(selectedResult);
			
							let invertColor = false;
							if (result_min_max.length > _result_min_max_idx) {
								invertColor = result_min_max[_result_min_max_idx] === "max";
							}
			
							colorScale = invertColor
								? [[0, 'red'], [1, 'green']]
								: [[0, 'green'], [1, 'red']];
						}
						updatePlot();
					});
				} else {
					let invertColor = false;
					if (Object.keys(result_min_max).length == 1) {
						invertColor = result_min_max[0] === "max";
					}
			
					colorScale = invertColor
						? [[0, 'red'], [1, 'green']]
						: [[0, 'green'], [1, 'red']];
			
					const resultCol = numericalCols.find(col => col.name.toLowerCase() === resultNames[0].toLowerCase());
					colorValues = dataArray.map(row => parseFloat(row[resultCol.index]));
				}
			
				function updatePlot() {
					const trace = {
						type: 'parcoords',
						dimensions: dimensions,
						line: colorValues ? { color: colorValues, colorscale: colorScale } : {},
						unselected: {
							line: {
								color: get_text_color(),
								opacity: 0
							}
						},
					};
			
					dimensions.forEach(dim => {
						if (!dim.line) {
							dim.line = {};
						}
						if (!dim.line.color) {
							dim.line.color = 'rgba(169,169,169, 0.01)';
						}
					});
			
					Plotly.newPlot('parallel-plot', [trace], add_default_layout_data({}));
			
					make_text_in_parallel_plot_nicer();
				}
			
				updatePlot();
			
				$("#parallel-plot").data("loaded", "true");
			
				make_text_in_parallel_plot_nicer();
			}
			
			function plotWorkerUsage() {
				if($("#workerUsagePlot").data("loaded") == "true") {
					return;
				}
				var data = tab_worker_usage_csv_json;
				if (!Array.isArray(data) || data.length === 0) {
					console.error("Invalid or empty data provided.");
					return;
				}
			
				let timestamps = [];
				let desiredWorkers = [];
				let realWorkers = [];
			
				for (let i = 0; i < data.length; i++) {
					let entry = data[i];
			
					if (!Array.isArray(entry) || entry.length < 3) {
						console.warn("Skipping invalid entry:", entry);
						continue;
					}
			
					let unixTime = parseFloat(entry[0]);
					let desired = parseInt(entry[1], 10);
					let real = parseInt(entry[2], 10);
			
					if (isNaN(unixTime) || isNaN(desired) || isNaN(real)) {
						console.warn("Skipping invalid numerical values:", entry);
						continue;
					}
			
					timestamps.push(new Date(unixTime * 1000).toISOString());
					desiredWorkers.push(desired);
					realWorkers.push(real);
				}
			
				let trace1 = {
					x: timestamps,
					y: desiredWorkers,
					mode: 'lines+markers',
					name: 'Desired Workers',
					line: {
						color: 'blue'
					}
				};
			
				let trace2 = {
					x: timestamps,
					y: realWorkers,
					mode: 'lines+markers',
					name: 'Real Workers',
					line: {
						color: 'red'
					}
				};
			
				let layout = {
					title: "Worker Usage Over Time",
					xaxis: {
						title: get_axis_title_data("Time", "date")
					},
					yaxis: {
						title: get_axis_title_data("Number of Workers")
					},
					legend: {
						x: 0,
						y: 1
					}
				};
			
				Plotly.newPlot('workerUsagePlot', [trace1, trace2], add_default_layout_data(layout));
				$("#workerUsagePlot").data("loaded", "true");
			}
			
			function plotCPUAndRAMUsage() {
				if($("#mainWorkerCPURAM").data("loaded") == "true") {
					return;
				}
				var timestamps = tab_main_worker_cpu_ram_csv_json.map(row => new Date(row[0] * 1000));
				var ramUsage = tab_main_worker_cpu_ram_csv_json.map(row => row[1]);
				var cpuUsage = tab_main_worker_cpu_ram_csv_json.map(row => row[2]);
			
				var trace1 = {
					x: timestamps,
					y: cpuUsage,
					mode: 'lines+markers',
					marker: {
						size: get_marker_size(),
					},
					name: 'CPU Usage (%)',
					type: 'scatter',
					yaxis: 'y1'
				};
			
				var trace2 = {
					x: timestamps,
					y: ramUsage,
					mode: 'lines+markers',
					marker: {
						size: get_marker_size(),
					},
					name: 'RAM Usage (MB)',
					type: 'scatter',
					yaxis: 'y2'
				};
			
				var layout = {
					title: 'CPU and RAM Usage Over Time',
					xaxis: {
						title: get_axis_title_data("Timestamp", "date"),
						tickmode: 'array',
						tickvals: timestamps.filter((_, index) => index % Math.max(Math.floor(timestamps.length / 10), 1) === 0),
						ticktext: timestamps.filter((_, index) => index % Math.max(Math.floor(timestamps.length / 10), 1) === 0).map(t => t.toLocaleString()),
						tickangle: -45
					},
					yaxis: {
						title: get_axis_title_data("CPU Usage (%)"),
						rangemode: 'tozero'
					},
					yaxis2: {
						title: get_axis_title_data("RAM Usage (MB)"),
						overlaying: 'y',
						side: 'right',
						rangemode: 'tozero'
					},
					legend: {
						x: 0.1,
						y: 0.9
					}
				};
			
				var data = [trace1, trace2];
				Plotly.newPlot('mainWorkerCPURAM', data, add_default_layout_data(layout));
				$("#mainWorkerCPURAM").data("loaded", "true");
			}
			
			function plotScatter2d() {
				if ($("#plotScatter2d").data("loaded") == "true") {
					return;
				}
			
				var plotDiv = document.getElementById("plotScatter2d");
			
				var minInput = document.getElementById("minValue");
				var maxInput = document.getElementById("maxValue");
			
				if (!minInput || !maxInput) {
					minInput = document.createElement("input");
					minInput.id = "minValue";
					minInput.type = "number";
					minInput.placeholder = "Min Value";
					minInput.step = "any";
			
					maxInput = document.createElement("input");
					maxInput.id = "maxValue";
					maxInput.type = "number";
					maxInput.placeholder = "Max Value";
					maxInput.step = "any";
			
					var inputContainer = document.createElement("div");
					inputContainer.style.marginBottom = "10px";
					inputContainer.appendChild(minInput);
					inputContainer.appendChild(maxInput);
					plotDiv.appendChild(inputContainer);
				}
			
				var resultSelect = document.getElementById("resultSelect");
				if (result_names.length > 1 && !resultSelect) {
					resultSelect = document.createElement("select");
					resultSelect.id = "resultSelect";
					resultSelect.style.marginBottom = "10px";
			
					var sortedResults = [...result_names].sort();
					sortedResults.forEach(result => {
						var option = document.createElement("option");
						option.value = result;
						option.textContent = result;
						resultSelect.appendChild(option);
					});
			
					var selectContainer = document.createElement("div");
					selectContainer.style.marginBottom = "10px";
					selectContainer.appendChild(resultSelect);
					plotDiv.appendChild(selectContainer);
				}
			
				minInput.addEventListener("input", updatePlots);
				maxInput.addEventListener("input", updatePlots);
				if (resultSelect) {
					resultSelect.addEventListener("change", updatePlots);
				}
			
				updatePlots();
			
				async function updatePlots() {
					var minValue = parseFloat(minInput.value);
					var maxValue = parseFloat(maxInput.value);
					if (isNaN(minValue)) minValue = -Infinity;
					if (isNaN(maxValue)) maxValue = Infinity;
			
					while (plotDiv.children.length > 2) {
						plotDiv.removeChild(plotDiv.lastChild);
					}
			
					var selectedResult = resultSelect ? resultSelect.value : result_names[0];
			
					var resultIndex = tab_results_headers_json.findIndex(header =>
						header.toLowerCase() === selectedResult.toLowerCase()
					);
					var resultValues = tab_results_csv_json.map(row => row[resultIndex]);
			
					var minResult = Math.min(...resultValues.filter(value => value !== null && value !== ""));
					var maxResult = Math.max(...resultValues.filter(value => value !== null && value !== ""));
			
					if (minValue !== -Infinity) minResult = Math.max(minResult, minValue);
					if (maxValue !== Infinity) maxResult = Math.min(maxResult, maxValue);
			
					var invertColor = result_min_max[result_names.indexOf(selectedResult)] === "max";
			
					var numericColumns = tab_results_headers_json.filter(col =>
						!special_col_names.includes(col) && !result_names.includes(col) &&
						tab_results_csv_json.every(row => !isNaN(parseFloat(row[tab_results_headers_json.indexOf(col)])))
					);
			
					if (numericColumns.length < 2) {
						console.error("Not enough columns for Scatter-Plots");
						return;
					}
			
					for (let i = 0; i < numericColumns.length; i++) {
						for (let j = i + 1; j < numericColumns.length; j++) {
							let xCol = numericColumns[i];
							let yCol = numericColumns[j];
			
							let xIndex = tab_results_headers_json.indexOf(xCol);
							let yIndex = tab_results_headers_json.indexOf(yCol);
			
							let data = tab_results_csv_json.map(row => ({
								x: parseFloat(row[xIndex]),
								y: parseFloat(row[yIndex]),
								result: row[resultIndex] !== "" ? parseFloat(row[resultIndex]) : null
							}));
			
							data = data.filter(d => d.result >= minResult && d.result <= maxResult);
			
							let layoutTitle = `${xCol} (x) vs ${yCol} (y), result: ${selectedResult}`;
							let layout = {
								title: layoutTitle,
								xaxis: {
									title: get_axis_title_data(xCol)
								},
								yaxis: {
									title: get_axis_title_data(yCol)
								},
								showlegend: false
							};
							let subDiv = document.createElement("div");
			
							let spinnerContainer = document.createElement("div");
							spinnerContainer.style.display = "flex";
							spinnerContainer.style.alignItems = "center";
							spinnerContainer.style.justifyContent = "center";
							spinnerContainer.style.width = layout.width + "px";
							spinnerContainer.style.height = layout.height + "px";
							spinnerContainer.style.position = "relative";
			
							let spinner = document.createElement("div");
							spinner.className = "spinner";
							spinner.style.width = "40px";
							spinner.style.height = "40px";
			
							let loadingText = document.createElement("span");
							loadingText.innerText = `Loading ${layoutTitle}`;
							loadingText.style.marginLeft = "10px";
			
							spinnerContainer.appendChild(spinner);
							spinnerContainer.appendChild(loadingText);
			
							plotDiv.appendChild(spinnerContainer);
			
							await new Promise(resolve => setTimeout(resolve, 50));
			
							let colors = data.map(d => {
								if (d.result === null) {
									return 'rgb(0, 0, 0)';
								} else {
									let norm = (d.result - minResult) / (maxResult - minResult);
									if (invertColor) {
										norm = 1 - norm;
									}
									return `rgb(${Math.round(255 * norm)}, ${Math.round(255 * (1 - norm))}, 0)`;
								}
							});
			
							let trace = {
								x: data.map(d => d.x),
								y: data.map(d => d.y),
								mode: 'markers',
								marker: {
									size: get_marker_size(),
									color: data.map(d => d.result !== null ? d.result : null),
									colorscale: invertColor ? [
										[0, 'red'],
										[1, 'green']
									] : [
										[0, 'green'],
										[1, 'red']
									],
									colorbar: {
										title: 'Result',
										tickvals: [minResult, maxResult],
										ticktext: [`${minResult}`, `${maxResult}`]
									},
									symbol: data.map(d => d.result === null ? 'x' : 'circle'),
								},
								text: data.map(d => d.result !== null ? `Result: ${d.result}` : 'No result'),
								type: 'scatter',
								showlegend: false
							};
			
							try {
								plotDiv.replaceChild(subDiv, spinnerContainer);
							} catch (err) {
								//
							}
							Plotly.newPlot(subDiv, [trace], add_default_layout_data(layout));
						}
					}
				}
			
				$("#plotScatter2d").data("loaded", "true");
			}
			
			function plotScatter3d() {
				if ($("#plotScatter3d").data("loaded") == "true") {
					return;
				}
			
				var plotDiv = document.getElementById("plotScatter3d");
				if (!plotDiv) {
					console.error("Div element with id 'plotScatter3d' not found");
					return;
				}
				plotDiv.innerHTML = "";
			
				var minInput3d = document.getElementById("minValue3d");
				var maxInput3d = document.getElementById("maxValue3d");
			
				if (!minInput3d || !maxInput3d) {
					minInput3d = document.createElement("input");
					minInput3d.id = "minValue3d";
					minInput3d.type = "number";
					minInput3d.placeholder = "Min Value";
					minInput3d.step = "any";
			
					maxInput3d = document.createElement("input");
					maxInput3d.id = "maxValue3d";
					maxInput3d.type = "number";
					maxInput3d.placeholder = "Max Value";
					maxInput3d.step = "any";
			
					var inputContainer3d = document.createElement("div");
					inputContainer3d.style.marginBottom = "10px";
					inputContainer3d.appendChild(minInput3d);
					inputContainer3d.appendChild(maxInput3d);
					plotDiv.appendChild(inputContainer3d);
				}
			
				var select3d = document.getElementById("select3dScatter");
				if (result_names.length > 1 && !select3d) {
					if (!select3d) {
						select3d = document.createElement("select");
						select3d.id = "select3dScatter";
						select3d.style.marginBottom = "10px";
						select3d.innerHTML = result_names.map(name => `<option value="${name}">${name}</option>`).join("");
			
						select3d.addEventListener("change", updatePlots3d);
			
						plotDiv.appendChild(select3d);
					}
				}
			
				minInput3d.addEventListener("input", updatePlots3d);
				maxInput3d.addEventListener("input", updatePlots3d);
			
				updatePlots3d();
			
				async function updatePlots3d() {
					var selectedResult = select3d ? select3d.value : result_names[0];
					var minValue3d = parseFloat(minInput3d.value);
					var maxValue3d = parseFloat(maxInput3d.value);
			
					if (isNaN(minValue3d)) minValue3d = -Infinity;
					if (isNaN(maxValue3d)) maxValue3d = Infinity;
			
					while (plotDiv.children.length > 2) {
						plotDiv.removeChild(plotDiv.lastChild);
					}
			
					var resultIndex = tab_results_headers_json.findIndex(header =>
						header.toLowerCase() === selectedResult.toLowerCase()
					);
					var resultValues = tab_results_csv_json.map(row => row[resultIndex]);
			
					var minResult = Math.min(...resultValues.filter(value => value !== null && value !== ""));
					var maxResult = Math.max(...resultValues.filter(value => value !== null && value !== ""));
			
					if (minValue3d !== -Infinity) minResult = Math.max(minResult, minValue3d);
					if (maxValue3d !== Infinity) maxResult = Math.min(maxResult, maxValue3d);
			
					var invertColor = result_min_max[result_names.indexOf(selectedResult)] === "max";
			
					var numericColumns = tab_results_headers_json.filter(col =>
						!special_col_names.includes(col) && !result_names.includes(col) &&
						tab_results_csv_json.every(row => !isNaN(parseFloat(row[tab_results_headers_json.indexOf(col)])))
					);
			
					if (numericColumns.length < 3) {
						console.error("Not enough columns for 3D scatter plots");
						return;
					}
			
					for (let i = 0; i < numericColumns.length; i++) {
						for (let j = i + 1; j < numericColumns.length; j++) {
							for (let k = j + 1; k < numericColumns.length; k++) {
								let xCol = numericColumns[i];
								let yCol = numericColumns[j];
								let zCol = numericColumns[k];
			
								let xIndex = tab_results_headers_json.indexOf(xCol);
								let yIndex = tab_results_headers_json.indexOf(yCol);
								let zIndex = tab_results_headers_json.indexOf(zCol);
			
								let data = tab_results_csv_json.map(row => ({
									x: parseFloat(row[xIndex]),
									y: parseFloat(row[yIndex]),
									z: parseFloat(row[zIndex]),
									result: row[resultIndex] !== "" ? parseFloat(row[resultIndex]) : null
								}));
			
								data = data.filter(d => d.result >= minResult && d.result <= maxResult);
			
								let layoutTitle = `${xCol} (x) vs ${yCol} (y) vs ${zCol} (z), result: ${selectedResult}`;
								let layout = {
									title: layoutTitle,
									scene: {
										xaxis: {
											title: get_axis_title_data(xCol)
										},
										yaxis: {
											title: get_axis_title_data(yCol)
										},
										zaxis: {
											title: get_axis_title_data(zCol)
										}
									},
									showlegend: false
								};
			
								let spinnerContainer = document.createElement("div");
								spinnerContainer.style.display = "flex";
								spinnerContainer.style.alignItems = "center";
								spinnerContainer.style.justifyContent = "center";
								spinnerContainer.style.width = layout.width + "px";
								spinnerContainer.style.height = layout.height + "px";
								spinnerContainer.style.position = "relative";
			
								let spinner = document.createElement("div");
								spinner.className = "spinner";
								spinner.style.width = "40px";
								spinner.style.height = "40px";
			
								let loadingText = document.createElement("span");
								loadingText.innerText = `Loading ${layoutTitle}`;
								loadingText.style.marginLeft = "10px";
			
								spinnerContainer.appendChild(spinner);
								spinnerContainer.appendChild(loadingText);
			
								plotDiv.appendChild(spinnerContainer);
			
								await new Promise(resolve => setTimeout(resolve, 50));
			
								let colors = data.map(d => {
									if (d.result === null) {
										return 'rgb(0, 0, 0)';
									} else {
										let norm = (d.result - minResult) / (maxResult - minResult);
										if (invertColor) {
											norm = 1 - norm;
										}
										return `rgb(${Math.round(255 * norm)}, ${Math.round(255 * (1 - norm))}, 0)`;
									}
								});
			
								let trace = {
									x: data.map(d => d.x),
									y: data.map(d => d.y),
									z: data.map(d => d.z),
									mode: 'markers',
									marker: {
										size: get_marker_size(),
										color: data.map(d => d.result !== null ? d.result : null),
										colorscale: invertColor ? [
											[0, 'red'],
											[1, 'green']
										] : [
											[0, 'green'],
											[1, 'red']
										],
										colorbar: {
											title: 'Result',
											tickvals: [minResult, maxResult],
											ticktext: [`${minResult}`, `${maxResult}`]
										},
									},
									text: data.map(d => d.result !== null ? `Result: ${d.result}` : 'No result'),
									type: 'scatter3d',
									showlegend: false
								};
			
								let subDiv = document.createElement("div");
								try {
									plotDiv.replaceChild(subDiv, spinnerContainer);
								} catch (err) {
									//
								}
								Plotly.newPlot(subDiv, [trace], add_default_layout_data(layout));
							}
						}
					}
				}
			
				$("#plotScatter3d").data("loaded", "true");
			}
			
			async function plot_worker_cpu_ram() {
				if($("#worker_cpu_ram_pre").data("loaded") == "true") {
					return;
				}
			
				const logData = $("#worker_cpu_ram_pre").text();
				const regex = /^Unix-Timestamp: (\d+), Hostname: ([\w-]+), CPU: ([\d.]+)%, RAM: ([\d.]+) MB \/ ([\d.]+) MB$/;
			
				const hostData = {};
			
				logData.split("\n").forEach(line => {
					line = line.trim();
					const match = line.match(regex);
					if (match) {
						const timestamp = new Date(parseInt(match[1]) * 1000);
						const hostname = match[2];
						const cpu = parseFloat(match[3]);
						const ram = parseFloat(match[4]);
			
						if (!hostData[hostname]) {
							hostData[hostname] = { timestamps: [], cpuUsage: [], ramUsage: [] };
						}
			
						hostData[hostname].timestamps.push(timestamp);
						hostData[hostname].cpuUsage.push(cpu);
						hostData[hostname].ramUsage.push(ram);
					}
				});
			
				if (!Object.keys(hostData).length) {
					console.log("No valid data found");
					return;
				}
			
				const container = document.getElementById("cpuRamWorkerChartContainer");
				container.innerHTML = "";
			
				var i = 1;
			
				Object.entries(hostData).forEach(([hostname, { timestamps, cpuUsage, ramUsage }], index) => {
					const chartId = `workerChart_${index}`;
					const chartDiv = document.createElement("div");
					chartDiv.id = chartId;
					chartDiv.style.marginBottom = "40px";
					container.appendChild(chartDiv);
			
					const cpuTrace = {
						x: timestamps,
						y: cpuUsage,
						mode: "lines+markers",
						name: "CPU Usage (%)",
						yaxis: "y1",
						line: {
							color: "red"
						}
					};
			
					const ramTrace = {
						x: timestamps,
						y: ramUsage,
						mode: "lines+markers",
						name: "RAM Usage (MB)",
						yaxis: "y2",
						line: {
							color: "blue"
						}
					};
			
					const layout = {
						title: `Worker CPU and RAM Usage - ${hostname}`,
						xaxis: {
							title: get_axis_title_data("Timestamp", "date")
						},
						yaxis: {
							title: get_axis_title_data("CPU Usage (%)"),
							side: "left",
							color: "red"
						},
						yaxis2: {
							title: get_axis_title_data("RAM Usage (MB)"),
							side: "right",
							overlaying: "y",
							color: "blue"
						},
						showlegend: true
					};
			
					Plotly.newPlot(chartId, [cpuTrace, ramTrace], add_default_layout_data(layout));
					i++;
				});
			
				$("#plot_worker_cpu_ram_button").remove();
				$("#worker_cpu_ram_pre").data("loaded", "true");
			}
			
			function load_log_file(log_nr, filename) {
				var pre_id = `single_run_${log_nr}_pre`;
			
				if (!$("#" + pre_id).data("loaded")) {
					const params = new URLSearchParams(window.location.search);
			
					const user_id = params.get('user_id');
					const experiment_name = params.get('experiment_name');
					const run_nr = params.get('run_nr');
			
					var url = `get_log?user_id=${user_id}&experiment_name=${experiment_name}&run_nr=${run_nr}&filename=${filename}`;
			
					fetch(url)
						.then(response => response.json())
						.then(data => {
							if (data.data) {
								$("#" + pre_id).html(data.data);
								$("#" + pre_id).data("loaded", true);
							} else {
								log(`No 'data' key found in response.`);
							}
			
							$("#spinner_log_" + log_nr).remove();
						})
						.catch(error => {
							log(`Error loading log: ${error}`);
							$("#spinner_log_" + log_nr).remove();
						});
				}
			}
			
			function load_debug_log () {
				var pre_id = `here_debuglogs_go`;
			
				if (!$("#" + pre_id).data("loaded")) {
					const params = new URLSearchParams(window.location.search);
			
					const user_id = params.get('user_id');
					const experiment_name = params.get('experiment_name');
					const run_nr = params.get('run_nr');
			
					var url = `get_debug_log?user_id=${user_id}&experiment_name=${experiment_name}&run_nr=${run_nr}`;
			
					fetch(url)
						.then(response => response.json())
						.then(data => {
							$("#debug_log_spinner").remove();
			
							if (data.data) {
								try {
									$("#" + pre_id).html(data.data);
								} catch (err) {
									$("#" + pre_id).text(`Error loading data: ${err}`);
								}
			
								$("#" + pre_id).data("loaded", true);
			
								if (typeof apply_theme_based_on_system_preferences === 'function') {
									apply_theme_based_on_system_preferences();
								}
							} else {
								log(`No 'data' key found in response.`);
							}
						})
						.catch(error => {
							log(`Error loading log: ${error}`);
							$("#debug_log_spinner").remove();
						});
				}
			}
			
			function plotBoxplot() {
				if ($("#plotBoxplot").data("loaded") == "true") {
					return;
				}
				var numericColumns = tab_results_headers_json.filter(col =>
					!special_col_names.includes(col) && !result_names.includes(col) &&
					tab_results_csv_json.every(row => !isNaN(parseFloat(row[tab_results_headers_json.indexOf(col)])))
				);
			
				if (numericColumns.length < 1) {
					console.error("Not enough numeric columns for Boxplot");
					return;
				}
			
				var resultIndex = tab_results_headers_json.findIndex(function(header) {
					return result_names.includes(header.toLowerCase());
				});
				var resultValues = tab_results_csv_json.map(row => row[resultIndex]);
				var minResult = Math.min(...resultValues.filter(value => value !== null && value !== ""));
				var maxResult = Math.max(...resultValues.filter(value => value !== null && value !== ""));
			
				var plotDiv = document.getElementById("plotBoxplot");
				plotDiv.innerHTML = "";
			
				let traces = numericColumns.map(col => {
					let index = tab_results_headers_json.indexOf(col);
					let data = tab_results_csv_json.map(row => parseFloat(row[index]));
			
					return {
						y: data,
						type: 'box',
						name: col,
						boxmean: 'sd',
						marker: {
							color: 'rgb(0, 255, 0)'
						},
					};
				});
			
				let layout = {
					title: 'Boxplot of Numerical Columns',
					xaxis: {
						title: get_axis_title_data("Columns")
					},
					yaxis: {
						title: get_axis_title_data("Value")
					},
					showlegend: false
				};
			
				Plotly.newPlot(plotDiv, traces, add_default_layout_data(layout));
				$("#plotBoxplot").data("loaded", "true");
			}
			
			function plotHeatmap() {
				if ($("#plotHeatmap").data("loaded") === "true") {
					return;
				}
			
				var numericColumns = tab_results_headers_json.filter(col => {
					if (special_col_names.includes(col) || result_names.includes(col)) {
						return false;
					}
					let index = tab_results_headers_json.indexOf(col);
					return tab_results_csv_json.every(row => {
						let value = parseFloat(row[index]);
						return !isNaN(value) && isFinite(value);
					});
				});
			
				if (numericColumns.length < 2) {
					console.error("Not enough valid numeric columns for Heatmap");
					return;
				}
			
				var columnData = numericColumns.map(col => {
					let index = tab_results_headers_json.indexOf(col);
					return tab_results_csv_json.map(row => parseFloat(row[index]));
				});
			
				var dataMatrix = numericColumns.map((_, i) =>
					numericColumns.map((_, j) => {
						let values = columnData[i].map((val, index) => (val + columnData[j][index]) / 2);
						return values.reduce((a, b) => a + b, 0) / values.length;
					})
				);
			
				var trace = {
					z: dataMatrix,
					x: numericColumns,
					y: numericColumns,
					colorscale: 'Viridis',
					type: 'heatmap'
				};
			
				var layout = {
					xaxis: {
						title: get_axis_title_data("Columns")
					},
					yaxis: {
						title: get_axis_title_data("Columns")
					},
					showlegend: false
				};
			
				var plotDiv = document.getElementById("plotHeatmap");
				plotDiv.innerHTML = "";
			
				Plotly.newPlot(plotDiv, [trace], add_default_layout_data(layout));
				$("#plotHeatmap").data("loaded", "true");
			}
			
			function plotHistogram() {
				if ($("#plotHistogram").data("loaded") == "true") {
					return;
				}
			
				var numericColumns = tab_results_headers_json.filter(col =>
					!special_col_names.includes(col) && !result_names.includes(col) &&
					tab_results_csv_json.every(row => !isNaN(parseFloat(row[tab_results_headers_json.indexOf(col)])))
				);
			
				if (numericColumns.length < 1) {
					console.error("Not enough columns for Histogram");
					return;
				}
			
				var plotDiv = document.getElementById("plotHistogram");
				plotDiv.innerHTML = "";
			
				const colorPalette = ['#ff9999', '#66b3ff', '#99ff99', '#ffcc99', '#c2c2f0', '#ffb3e6'];
			
				let traces = numericColumns.map((col, index) => {
					let data = tab_results_csv_json.map(row => parseFloat(row[tab_results_headers_json.indexOf(col)]));
			
					return {
						x: data,
						type: 'histogram',
						name: col,
						opacity: 0.7,
						marker: {
							color: colorPalette[index % colorPalette.length]
						},
						autobinx: true
					};
				});
			
				let layout = {
					title: 'Histogram of Numerical Columns',
					xaxis: {
						title: get_axis_title_data("Value")
					},
					yaxis: {
						title: get_axis_title_data("Frequency")
					},
					showlegend: true,
					barmode: 'overlay'
				};
			
				Plotly.newPlot(plotDiv, traces, add_default_layout_data(layout));
				$("#plotHistogram").data("loaded", "true");
			}
			
			function plotViolin() {
				if ($("#plotViolin").data("loaded") == "true") {
					return;
				}
				var numericColumns = tab_results_headers_json.filter(col =>
					!special_col_names.includes(col) && !result_names.includes(col) &&
					tab_results_csv_json.every(row => !isNaN(parseFloat(row[tab_results_headers_json.indexOf(col)])))
				);
			
				if (numericColumns.length < 1) {
					console.error("Not enough columns for Violin Plot");
					return;
				}
			
				var plotDiv = document.getElementById("plotViolin");
				plotDiv.innerHTML = "";
			
				let traces = numericColumns.map(col => {
					let index = tab_results_headers_json.indexOf(col);
					let data = tab_results_csv_json.map(row => parseFloat(row[index]));
			
					return {
						y: data,
						type: 'violin',
						name: col,
						box: {
							visible: true
						},
						line: {
							color: 'rgb(0, 255, 0)'
						},
						marker: {
							color: 'rgb(0, 255, 0)'
						},
						meanline: {
							visible: true
						},
					};
				});
			
				let layout = {
					title: 'Violin Plot of Numerical Columns',
					yaxis: {
						title: get_axis_title_data("Value")
					},
					xaxis: {
						title: get_axis_title_data("Columns")
					},
					showlegend: false
				};
			
				Plotly.newPlot(plotDiv, traces, add_default_layout_data(layout));
				$("#plotViolin").data("loaded", "true");
			}
			
			function plotExitCodesPieChart() {
				if ($("#plotExitCodesPieChart").data("loaded") == "true") {
					return;
				}
			
				var exitCodes = tab_job_infos_csv_json.map(row => row[tab_job_infos_headers_json.indexOf("exit_code")]);
			
				var exitCodeCounts = exitCodes.reduce(function(counts, exitCode) {
					counts[exitCode] = (counts[exitCode] || 0) + 1;
					return counts;
				}, {});
			
				var labels = Object.keys(exitCodeCounts);
				var values = Object.values(exitCodeCounts);
			
				var plotDiv = document.getElementById("plotExitCodesPieChart");
				plotDiv.innerHTML = "";
			
				var trace = {
					labels: labels,
					values: values,
					type: 'pie',
					hoverinfo: 'label+percent',
					textinfo: 'label+value',
					marker: {
						colors: ['#ff9999','#66b3ff','#99ff99','#ffcc99','#c2c2f0']
					}
				};
			
				var layout = {
					title: 'Exit Code Distribution',
					showlegend: true
				};
			
				Plotly.newPlot(plotDiv, [trace], add_default_layout_data(layout));
				$("#plotExitCodesPieChart").data("loaded", "true");
			}
			
			function plotResultEvolution() {
				if ($("#plotResultEvolution").data("loaded") == "true") {
					return;
				}
			
				result_names.forEach(resultName => {
					var relevantColumns = tab_results_headers_json.filter(col =>
						!special_col_names.includes(col) && !col.startsWith("OO_Info") && col.toLowerCase() !== resultName.toLowerCase()
					);
			
					var xColumnIndex = tab_results_headers_json.indexOf("trial_index");
					var resultIndex = tab_results_headers_json.indexOf(resultName);
			
					let data = tab_results_csv_json.map(row => ({
						x: row[xColumnIndex],
						y: parseFloat(row[resultIndex])
					}));
			
					data.sort((a, b) => a.x - b.x);
			
					let xData = data.map(item => item.x);
					let yData = data.map(item => item.y);
			
					let trace = {
						x: xData,
						y: yData,
						mode: 'lines+markers',
						name: resultName,
						line: {
							shape: 'linear'
						},
						marker: {
							size: get_marker_size()
						}
					};
			
					let layout = {
						title: `Evolution of ${resultName} over time`,
						xaxis: {
							title: get_axis_title_data("Trial-Index")
						},
						yaxis: {
							title: get_axis_title_data(resultName)
						},
						showlegend: true
					};
			
					let subDiv = document.createElement("div");
					document.getElementById("plotResultEvolution").appendChild(subDiv);
			
					Plotly.newPlot(subDiv, [trace], add_default_layout_data(layout));
				});
			
				$("#plotResultEvolution").data("loaded", "true");
			}
			
			function plotResultPairs() {
				if ($("#plotResultPairs").data("loaded") == "true") {
					return;
				}
			
				var plotDiv = document.getElementById("plotResultPairs");
				plotDiv.innerHTML = "";
			
				for (let i = 0; i < result_names.length; i++) {
					for (let j = i + 1; j < result_names.length; j++) {
						let xName = result_names[i];
						let yName = result_names[j];
			
						let xIndex = tab_results_headers_json.indexOf(xName);
						let yIndex = tab_results_headers_json.indexOf(yName);
			
						let data = tab_results_csv_json
							.filter(row => row[xIndex] !== "" && row[yIndex] !== "")
							.map(row => ({
								x: parseFloat(row[xIndex]),
								y: parseFloat(row[yIndex]),
								status: row[tab_results_headers_json.indexOf("trial_status")]
							}));
			
						let colors = data.map(d => d.status === "COMPLETED" ? 'green' : (d.status === "FAILED" ? 'red' : 'gray'));
			
						let trace = {
							x: data.map(d => d.x),
							y: data.map(d => d.y),
							mode: 'markers',
							marker: {
								size: get_marker_size(),
								color: colors
							},
							text: data.map(d => `Status: ${d.status}`),
							type: 'scatter',
							showlegend: false
						};
			
						let layout = {
							xaxis: {
								title: get_axis_title_data(xName)
							},
							yaxis: {
								title: get_axis_title_data(yName)
							},
							showlegend: false
						};
			
						let subDiv = document.createElement("div");
						plotDiv.appendChild(subDiv);
			
						Plotly.newPlot(subDiv, [trace], add_default_layout_data(layout));
					}
				}
			
				$("#plotResultPairs").data("loaded", "true");
			}
			
			function add_up_down_arrows_for_scrolling () {
				const upArrow = document.createElement('div');
				const downArrow = document.createElement('div');
			
				const style = document.createElement('style');
				style.innerHTML = `
					.scroll-arrow {
						position: fixed;
						right: 10px;
						z-index: 100;
						cursor: pointer;
						font-size: 25px;
						display: none;
						background-color: green;
						color: white;
						padding: 5px;
						outline: 2px solid white;
						box-shadow: 0 0 10px rgba(0, 0, 0, 0.5);
						transition: background-color 0.3s, transform 0.3s;
					}
					.scroll-arrow:hover {
						background-color: darkgreen;
						transform: scale(1.1);
					}
					#up-arrow {
						top: 10px;
					}
					#down-arrow {
						bottom: 10px;
					}
				`;
				document.head.appendChild(style);
			
				upArrow.id = "up-arrow";
				upArrow.classList.add("scroll-arrow");
				upArrow.classList.add("invert_in_dark_mode");
				upArrow.innerHTML = "&#8593;";
			
				downArrow.id = "down-arrow";
				downArrow.classList.add("scroll-arrow");
				downArrow.classList.add("invert_in_dark_mode");
				downArrow.innerHTML = "&#8595;";
			
				document.body.appendChild(upArrow);
				document.body.appendChild(downArrow);
			
				function checkScrollPosition() {
					const scrollPosition = window.scrollY;
					const pageHeight = document.documentElement.scrollHeight;
					const windowHeight = window.innerHeight;
			
					if (scrollPosition > 0) {
						upArrow.style.display = "block";
					} else {
						upArrow.style.display = "none";
					}
			
					if (scrollPosition + windowHeight < pageHeight) {
						downArrow.style.display = "block";
					} else {
						downArrow.style.display = "none";
					}
				}
			
				window.addEventListener("scroll", checkScrollPosition);
			
				upArrow.addEventListener("click", function () {
					window.scrollTo({ top: 0, behavior: 'smooth' });
				});
			
				downArrow.addEventListener("click", function () {
					window.scrollTo({ top: document.documentElement.scrollHeight, behavior: 'smooth' });
				});
			
				checkScrollPosition();
			
				if (typeof apply_theme_based_on_system_preferences === 'function') {
					apply_theme_based_on_system_preferences();
				}
			}
			
			function plotGPUUsage() {
				if ($("#tab_gpu_usage").data("loaded") === "true") {
					return;
				}
			
				Object.keys(gpu_usage).forEach(node => {
					const nodeData = gpu_usage[node];
			
					var timestamps = [];
					var gpuUtilizations = [];
					var temperatures = [];
			
					nodeData.forEach(entry => {
						try {
							var timestamp = new Date(entry[0]* 1000);
							var utilization = parseFloat(entry[1]);
							var temperature = parseFloat(entry[2]);
			
							if (!isNaN(timestamp) && !isNaN(utilization) && !isNaN(temperature)) {
								timestamps.push(timestamp);
								gpuUtilizations.push(utilization);
								temperatures.push(temperature);
							} else {
								console.warn("Invalid data point:", entry);
							}
						} catch (error) {
							console.error("Error processing GPU data entry:", error, entry);
						}
					});
			
					var trace1 = {
						x: timestamps,
						y: gpuUtilizations,
						mode: 'lines+markers',
						marker: {
							size: get_marker_size(),
						},
						name: 'GPU Utilization (%)',
						type: 'scatter',
						yaxis: 'y1'
					};
			
					var trace2 = {
						x: timestamps,
						y: temperatures,
						mode: 'lines+markers',
						marker: {
							size: get_marker_size(),
						},
						name: 'GPU Temperature (°C)',
						type: 'scatter',
						yaxis: 'y2'
					};
			
					var layout = {
						title: 'GPU Usage Over Time - ' + node,
						xaxis: {
							title: get_axis_title_data("Timestamp", "date"),
							tickmode: 'array',
							tickvals: timestamps.filter((_, index) => index % Math.max(Math.floor(timestamps.length / 10), 1) === 0),
							ticktext: timestamps.filter((_, index) => index % Math.max(Math.floor(timestamps.length / 10), 1) === 0).map(t => t.toLocaleString()),
							tickangle: -45
						},
						yaxis: {
							title: get_axis_title_data("GPU Utilization (%)"),
							overlaying: 'y',
							rangemode: 'tozero'
						},
						yaxis2: {
							title: get_axis_title_data("GPU Temperature (°C)"),
							overlaying: 'y',
							side: 'right',
							position: 0.85,
							rangemode: 'tozero'
						},
						legend: {
							x: 0.1,
							y: 0.9
						}
					};
			
					var divId = 'gpu_usage_plot_' + node;
			
					if (!document.getElementById(divId)) {
						var div = document.createElement('div');
						div.id = divId;
						div.className = 'gpu-usage-plot';
						document.getElementById('tab_gpu_usage').appendChild(div);
					}
			
					var plotData = [trace1, trace2];
			
					Plotly.newPlot(divId, plotData, add_default_layout_data(layout));
				});
			
				$("#tab_gpu_usage").data("loaded", "true");
			}
			
			function plotResultsDistributionByGenerationMethod() {
				if ("true" === $("#plotResultsDistributionByGenerationMethod").data("loaded")) {
					return;
				}
			
				var res_col = result_names[0];
				var gen_method_col = "generation_node";
			
				var data = {};
			
				tab_results_csv_json.forEach(row => {
					var gen_method = row[tab_results_headers_json.indexOf(gen_method_col)];
					var result = row[tab_results_headers_json.indexOf(res_col)];
			
					if (!data[gen_method]) {
						data[gen_method] = [];
					}
					data[gen_method].push(result);
				});
			
				var traces = Object.keys(data).map(method => {
					return {
						y: data[method],
						type: 'box',
						name: method,
						boxpoints: 'outliers',
						jitter: 0.5,
						pointpos: 0
					};
				});
			
				var layout = {
					title: 'Distribution of Results by Generation Method',
					yaxis: {
						title: get_axis_title_data(res_col)
					},
					xaxis: {
						title: get_axis_title_data("Generation Method")
					},
					boxmode: 'group'
				};
			
				Plotly.newPlot("plotResultsDistributionByGenerationMethod", traces, add_default_layout_data(layout));
				$("#plotResultsDistributionByGenerationMethod").data("loaded", "true");
			}
			
			function plotJobStatusDistribution() {
				if ($("#plotJobStatusDistribution").data("loaded") === "true") {
					return;
				}
			
				var status_col = "trial_status";
				var status_counts = {};
			
				tab_results_csv_json.forEach(row => {
					var status = row[tab_results_headers_json.indexOf(status_col)];
					if (status) {
						status_counts[status] = (status_counts[status] || 0) + 1;
					}
				});
			
				var statuses = Object.keys(status_counts);
				var counts = Object.values(status_counts);
			
				var colors = statuses.map((status, i) =>
					status === "FAILED" ? "#FF0000" : `hsl(${30 + ((i * 137) % 330)}, 70%, 50%)`
				);
			
				var trace = {
					x: statuses,
					y: counts,
					type: 'bar',
					marker: { color: colors }
				};
			
				var layout = {
					title: 'Distribution of Job Status',
					xaxis: { title: 'Trial Status' },
					yaxis: { title: 'Nr. of jobs' }
				};
			
				Plotly.newPlot("plotJobStatusDistribution", [trace], add_default_layout_data(layout));
				$("#plotJobStatusDistribution").data("loaded", "true");
			}
			
			function _colorize_table_entries_by_generation_method () {
				document.querySelectorAll('[data-column-id="generation_node"]').forEach(el => {
					let text = el.textContent.toLowerCase();
					let color = text.includes("manual") ? "green" :
						text.includes("sobol") ? "orange" :
						text.includes("saasbo") ? "pink" :
						text.includes("uniform") ? "lightblue" :
						text.includes("legacy_gpei") ? "sienna" :
						text.includes("bo_mixed") ? "aqua" :
						text.includes("randomforest") ? "darkseagreen" :
						text.includes("external_generator") ? "purple" :
						text.includes("botorch") ? "yellow" : "";
					if (color !== "") {
						el.style.backgroundColor = color;
					}
					el.classList.add("invert_in_dark_mode");
				});
			}
			
			function _colorize_table_entries_by_trial_status () {
				document.querySelectorAll('[data-column-id="trial_status"]').forEach(el => {
					let color = el.textContent.includes("COMPLETED") ? "lightgreen" :
						el.textContent.includes("RUNNING") ? "orange" :
						el.textContent.includes("FAILED") ? "red" :
						el.textContent.includes("ABANDONED") ? "yellow" : "";
					if (color) el.style.backgroundColor = color;
					el.classList.add("invert_in_dark_mode");
				});
			}
			
			function _colorize_table_entries_by_run_time() {
				let cells = [...document.querySelectorAll('[data-column-id="run_time"]')];
				if (cells.length === 0) return;
			
				let values = cells.map(el => parseFloat(el.textContent)).filter(v => !isNaN(v));
				if (values.length === 0) return;
			
				let min = Math.min(...values);
				let max = Math.max(...values);
				let range = max - min || 1;
			
				cells.forEach(el => {
					let value = parseFloat(el.textContent);
					if (isNaN(value)) return;
			
					let ratio = (value - min) / range;
					let red = Math.round(255 * ratio);
					let green = Math.round(255 * (1 - ratio));
			
					el.style.backgroundColor = `rgb(${red}, ${green}, 0)`;
					el.classList.add("invert_in_dark_mode");
				});
			}
			
			function _colorize_table_entries_by_results() {
				result_names.forEach((name, index) => {
					let minMax = result_min_max[index];
					let selector_query = `[data-column-id="${name}"]`;
					let cells = [...document.querySelectorAll(selector_query)];
					if (cells.length === 0) return;
			
					let values = cells.map(el => parseFloat(el.textContent)).filter(v => v > 0 && !isNaN(v));
					if (values.length === 0) return;
			
					let logValues = values.map(v => Math.log(v));
					let logMin = Math.min(...logValues);
					let logMax = Math.max(...logValues);
					let logRange = logMax - logMin || 1;
			
					cells.forEach(el => {
						let value = parseFloat(el.textContent);
						if (isNaN(value) || value <= 0) return;
			
						let logValue = Math.log(value);
						let ratio = (logValue - logMin) / logRange;
						if (minMax === "max") ratio = 1 - ratio;
			
						let red = Math.round(255 * ratio);
						let green = Math.round(255 * (1 - ratio));
			
						el.style.backgroundColor = `rgb(${red}, ${green}, 0)`;
						el.classList.add("invert_in_dark_mode");
					});
				});
			}
			
			function _colorize_table_entries_by_generation_node_or_hostname() {
				["hostname", "generation_node"].forEach(element => {
					let selector_query = '[data-column-id="' + element + '"]:not(.gridjs-th)';
					let cells = [...document.querySelectorAll(selector_query)];
					if (cells.length === 0) return;
			
					let uniqueValues = [...new Set(cells.map(el => el.textContent.trim()))];
					let colorMap = {};
			
					uniqueValues.forEach((value, index) => {
						let hue = Math.round((360 / uniqueValues.length) * index);
						colorMap[value] = `hsl(${hue}, 70%, 60%)`;
					});
			
					cells.forEach(el => {
						let value = el.textContent.trim();
						if (colorMap[value]) {
							el.style.backgroundColor = colorMap[value];
							el.classList.add("invert_in_dark_mode");
						}
					});
				});
			}
			
			function colorize_table_entries () {
				setTimeout(() => {
					if (typeof result_names !== "undefined" && Array.isArray(result_names) && result_names.length > 0) {
						_colorize_table_entries_by_trial_status();
						_colorize_table_entries_by_results();
						_colorize_table_entries_by_run_time();
						_colorize_table_entries_by_generation_method();
						_colorize_table_entries_by_generation_node_or_hostname();
						if (typeof apply_theme_based_on_system_preferences === 'function') {
							apply_theme_based_on_system_preferences();
						}
					}
				}, 300);
			}
			
			function add_colorize_to_gridjs_table () {
				let searchInput = document.querySelector(".gridjs-search-input");
				if (searchInput) {
					searchInput.addEventListener("input", colorize_table_entries);
				}
			}
			
			function updatePreWidths() {
				var width = window.innerWidth * 0.95;
				var pres = document.getElementsByTagName('pre');
				for (var i = 0; i < pres.length; i++) {
					pres[i].style.width = width + 'px';
				}
			}
			
			function demo_mode(nr_sec = 3) {
				let i = 0;
				let tabs = $('menu[role="tablist"] > button');
			
				setInterval(() => {
					tabs.attr('aria-selected', 'false').removeClass('active');
			
					let tab = tabs.eq(i % tabs.length);
					tab.attr('aria-selected', 'true').addClass('active');
			
					tab.trigger('click');
			
					i++;
				}, nr_sec * 1000);
			}
			
			function resizePlotlyCharts() {
				const plotlyElements = document.querySelectorAll('.js-plotly-plot');
			
				if (plotlyElements.length) {
					const windowWidth = window.innerWidth;
					const windowHeight = window.innerHeight;
			
					const newWidth = windowWidth * 0.9;
					const newHeight = windowHeight * 0.9;
			
					plotlyElements.forEach(function(element, index) {
						const layout = {
							width: newWidth,
							height: newHeight,
							plot_bgcolor: 'rgba(0, 0, 0, 0)',
							paper_bgcolor: 'rgba(0, 0, 0, 0)',
						};
			
						Plotly.relayout(element, layout)
					});
				}
			
				make_text_in_parallel_plot_nicer();
				apply_theme_based_on_system_preferences();
			}
			
			window.addEventListener('load', updatePreWidths);
			window.addEventListener('resize', updatePreWidths);
			
			$(document).ready(function() {
				colorize_table_entries();
			
				add_up_down_arrows_for_scrolling();
			
				add_colorize_to_gridjs_table();
			});
			
			window.addEventListener('resize', function() {
				resizePlotlyCharts();
			});
			
			"use strict";
			
			function get_row_by_index(idx) {
				if (!Object.keys(window).includes("tab_results_csv_json")) {
					error("tab_results_csv_json is not defined");
					return;
				}
			
				if (!Object.keys(window).includes("tab_results_headers_json")) {
					error("tab_results_headers_json is not defined");
					return;
				}
			
			
				var trial_index_col_idx = tab_results_headers_json.indexOf("trial_index");
			
				if(trial_index_col_idx == -1) {
					error(`"trial_index" could not be found in tab_results_headers_json. Cannot continue`);
			
					return null;
				}
			
				for (var i = 0; i < tab_results_csv_json.length; i++) {
					var row = tab_results_csv_json[i];
					var trial_index = row[trial_index_col_idx];
			
					if (trial_index == idx) {
						return row;
					}
				}
			
				return null;
			}
			
			function load_pareto_graph_from_idxs () {
				if (!Object.keys(window).includes("pareto_idxs")) {
					error("pareto_idxs is not defined");
					return;
				}
			
				if (!Object.keys(window).includes("tab_results_csv_json")) {
					error("tab_results_csv_json is not defined");
					return;
				}
			
				if (!Object.keys(window).includes("tab_results_headers_json")) {
					error("tab_results_headers_json is not defined");
					return;
				}
			
				if(pareto_idxs === null) {
					var err_msg = "pareto_idxs is null. Cannot plot or create tables from empty data. This can be caused by a defective <tt>pareto_idxs.json</tt> file. Please try reloading, or re-calculating the pareto-front and re-submitting if this problem persists.";
					$("#pareto_from_idxs_table").html(`<div class="caveat alarm">${err_msg}</div>`);
					return;	
				}
			
				var table = get_pareto_table_data_from_idx();
			
				var html_tables = createParetoTablesFromData(table);
			
				$("#pareto_from_idxs_table").html(html_tables);
			
				renderParetoFrontPlots(table);
			
				apply_theme_based_on_system_preferences();
			}
			
			function renderParetoFrontPlots(data) {
				try {
					let container = document.getElementById("pareto_front_idxs_plot_container");
					if (!container) {
						console.error("DIV with id 'pareto_front_idxs_plot_container' not found.");
						return;
					}
			
					container.innerHTML = "";
			
					if(data === undefined || data === null) {
						var err_msg = "There was an error getting the data for Pareto-Fronts. See the developer's console to see further details.";
						$("#pareto_from_idxs_table").html(`<div class="caveat alarm">${err_msg}</div>`);
						return;
					}
			
					Object.keys(data).forEach((key, idx) => {
						if (!key.startsWith("Pareto front for ")) return;
			
						let label = key.replace("Pareto front for ", "");
						let [xKey, yKey] = label.split("/");
			
						if (!xKey || !yKey) {
							console.warn("Could not extract two objectives from key:", key);
							return;
						}
			
						let entries = data[key];
						let x = [];
						let y = [];
						let hoverTexts = [];
			
						entries.forEach((entry) => {
							let results = entry.results || {};
							let values = entry.values || {};
			
							let xVal = (results[xKey] || [])[0];
							let yVal = (results[yKey] || [])[0];
			
							if (xVal === undefined || yVal === undefined) {
								console.warn("Missing values for", xKey, yKey, "in", entry);
								return;
							}
			
							x.push(xVal);
							y.push(yVal);
			
							let hoverInfo = [];
			
							if ("trial_index" in values) {
								hoverInfo.push(`<b>Trial Index:</b> ${values.trial_index[0]}`);
							}
			
							Object.keys(values)
								.filter(k => k !== "trial_index")
								.sort()
								.forEach(k => {
									hoverInfo.push(`<b>${k}:</b> ${values[k][0]}`);
								});
			
							Object.keys(results)
								.sort()
								.forEach(k => {
									hoverInfo.push(`<b>${k}:</b> ${results[k][0]}`);
								});
			
							hoverTexts.push(hoverInfo.join("<br>"));
						});
			
						let wrapper = document.createElement("div");
						wrapper.style.marginBottom = "30px";
			
						let titleEl = document.createElement("h3");
						titleEl.textContent = `Pareto Front: ${xKey} (${getMinMaxByResultName(xKey)}) vs ${yKey} (${getMinMaxByResultName(yKey)})`;
						wrapper.appendChild(titleEl);
			
						let divId = `pareto_plot_${idx}`;
						let plotDiv = document.createElement("div");
						plotDiv.id = divId;
						plotDiv.style.width = "100%";
						plotDiv.style.height = "400px";
			
						wrapper.appendChild(plotDiv);
						container.appendChild(wrapper);
			
						let trace = {
							x: x,
							y: y,
							text: hoverTexts,
							hoverinfo: "text",
							mode: "markers",
							type: "scatter",
							marker: {
								size: 8,
								color: 'rgb(31, 119, 180)',
								line: {
									width: 1,
									color: 'black'
								}
							},
							name: label
						};
			
						let layout = {
							xaxis: { title: { text: xKey } },
							yaxis: { title: { text: yKey } },
							margin: { t: 10, l: 60, r: 20, b: 50 },
							hovermode: "closest",
							showlegend: false
						};
			
						Plotly.newPlot(divId, [trace], add_default_layout_data(layout, 1));
					});
				} catch (e) {
					console.error("Error while rendering Pareto front plots:", e);
				}
			}
			
			function createParetoTablesFromData(data) {
				try {
					var container = document.createElement("div");
			
					var parsedData;
					try {
						parsedData = typeof data === "string" ? JSON.parse(data) : data;
					} catch (e) {
						console.error("JSON parsing failed:", e);
						return container;
					}
			
					for (var sectionTitle in parsedData) {
						if (!parsedData.hasOwnProperty(sectionTitle)) {
							continue;
						}
			
						var sectionData = parsedData[sectionTitle];
						var heading = document.createElement("h2");
						heading.textContent = sectionTitle;
						container.appendChild(heading);
			
						var table = document.createElement("table");
						table.style.borderCollapse = "collapse";
						table.style.marginBottom = "2em";
						table.style.width = "100%";
			
						var thead = document.createElement("thead");
						var headerRow = document.createElement("tr");
			
						var allValueKeys = new Set();
						var allResultKeys = new Set();
			
						sectionData.forEach(entry => {
							var values = entry.values || {};
							var results = entry.results || {};
			
							Object.keys(values).forEach(key => {
								allValueKeys.add(key);
							});
			
							Object.keys(results).forEach(key => {
								allResultKeys.add(key);
							});
						});
			
						var sortedValueKeys = Array.from(allValueKeys).sort();
						var sortedResultKeys = Array.from(allResultKeys).sort();
			
						if (sortedValueKeys.includes("trial_index")) {
							sortedValueKeys = sortedValueKeys.filter(k => k !== "trial_index");
							sortedValueKeys.unshift("trial_index");
						}
			
						var allColumns = [...sortedValueKeys, ...sortedResultKeys];
			
						allColumns.forEach(col => {
							var th = document.createElement("th");
							th.textContent = col;
							th.style.border = "1px solid black";
							th.style.padding = "4px";
							headerRow.appendChild(th);
						});
			
						thead.appendChild(headerRow);
						table.appendChild(thead);
			
						var tbody = document.createElement("tbody");
			
						sectionData.forEach(entry => {
							var tr = document.createElement("tr");
			
							allColumns.forEach(col => {
								var td = document.createElement("td");
								td.style.border = "1px solid black";
								td.style.padding = "4px";
			
								var value = null;
			
								if (col in entry.values) {
									value = entry.values[col];
								} else if (col in entry.results) {
									value = entry.results[col];
								}
			
								if (Array.isArray(value)) {
									td.textContent = value.join(", ");
								} else {
									td.textContent = value !== null && value !== undefined ? value : "";
								}
			
								tr.appendChild(td);
							});
			
							tbody.appendChild(tr);
						});
			
						table.appendChild(tbody);
						container.appendChild(table);
					}
			
					return container;
				} catch (err) {
					console.error("Unexpected error:", err);
					var errorDiv = document.createElement("div");
					errorDiv.textContent = "Error generating tables.";
					return errorDiv;
				}
			}
			
			function get_pareto_table_data_from_idx () {
				if (!Object.keys(window).includes("pareto_idxs")) {
					error("pareto_idxs is not defined");
					return;
				}
			
				if (!Object.keys(window).includes("tab_results_csv_json")) {
					error("tab_results_csv_json is not defined");
					return;
				}
			
				if (!Object.keys(window).includes("tab_results_headers_json")) {
					error("tab_results_headers_json is not defined");
					return;
				}
			
				var x_keys = Object.keys(pareto_idxs);
			
				var tables = {};
			
				for (var i = 0; i < x_keys.length; i++) {
					var x_key = x_keys[i];
					var y_keys = Object.keys(pareto_idxs[x_key]);
			
					for (var j = 0; j < y_keys.length; j++) {
						var y_key = y_keys[j];
			
						var indices = pareto_idxs[x_key][y_key];
			
						for (var k = 0; k < indices.length; k++) {
							var idx = indices[k];
							var row = get_row_by_index(idx);
			
							if(row === null) {
								error(`Error getting the row for index ${idx}`);
								return;
							}
			
							var row_dict = {
								"results": {},
								"values": {},
							};
			
							for (var l = 0; l < tab_results_headers_json.length; l++) {
								var header = tab_results_headers_json[l];
			
								if (!special_col_names.includes(header) || header == "trial_index") {
									var val = row[l];
			
									if (result_names.includes(header)) {
										if (!Object.keys(row_dict["results"]).includes(header)) {
											row_dict["results"][header] = [];
										}
			
										row_dict["results"][header].push(val);
									} else {
										if (!Object.keys(row_dict["values"]).includes(header)) {
											row_dict["values"][header] = [];
										}
										row_dict["values"][header].push(val);
									}
								}
								
							}
			
							var table_key = `Pareto front for ${x_key}/${y_key}`;
			
							if(!Object.keys(tables).includes(table_key)) {
								tables[table_key] = [];
							}
			
							tables[table_key].push(row_dict);
						}
			
					}
				}
			
				return tables;
			}
			
			function getMinMaxByResultName(resultName) {
				try {
					if (typeof resultName !== "string") {
						error("Parameter resultName must be a string");
						return;
					}
			
					if (!Array.isArray(result_names)) {
						error("Global variable result_names is not an array or undefined");
						return;
					}
					if (!Array.isArray(result_min_max)) {
						error("Global variable result_min_max is not an array or undefined");
						return;
					}
			
					if (result_names.length !== result_min_max.length) {
						error("Global arrays result_names and result_min_max must have the same length");
						return;
					}
			
					var index = result_names.indexOf(resultName);
					if (index === -1) {
						error("Result name '" + resultName + "' not found in result_names");
						return;
					}
			
					var minMaxValue = result_min_max[index];
			
					if (minMaxValue !== "min" && minMaxValue !== "max") {
						error("Value for result name '" + resultName + "' is invalid: expected 'min' or 'max'");
						return;
					}
			
					return minMaxValue;
			
				} catch (e) {
					error("Unexpected error: " + e.message);
				}
			}
			

			$(document).ready(function() {
				colorize_table_entries();;
				plotWorkerUsage();;
				plotCPUAndRAMUsage();;
				createParallelPlot(tab_results_csv_json, tab_results_headers_json, result_names, special_col_names);;
				plotScatter2d();;
				plotScatter3d();
				plotResultsDistributionByGenerationMethod();;
				plotJobStatusDistribution();;
				plotBoxplot();;
				plotViolin();;
				plotHistogram();;
				plotHeatmap();;
				plotResultEvolution();

				colorize_table_entries();
			});
		</script>

					<h1>&nbsp;Overview</h1>
			<button onclick="window.open('https://imageseg.scads.de/omniax/gui?partition=barnard&amp;experiment_name=vergl_botorch&amp;reservation=&amp;account=&amp;mem_gb=10&amp;time=600&amp;worker_timeout=30&amp;max_eval=2000&amp;num_parallel_jobs=50&amp;gpus=0&amp;num_random_steps=50&amp;follow=1&amp;live_share=1&amp;send_anonymized_usage_stats=1&amp;checkout_to_latest_tested_version=1&amp;constraints=&amp;result_names=RESULT%3Dmin&amp;run_program=bash%20%2Fdata%2Fhorse%2Fws%2Fpwinkler-oopt%2Frun.sh%20%25(epochs)%20%25(lr)%20%25(bsz)%20%25(da)%20%25(db)&amp;cpus_per_task=1&amp;nodes_per_job=1&amp;seed=&amp;verbose=0&amp;generate_all_jobs_at_once=0&amp;debug=0&amp;revert_to_random_when_seemingly_exhausted=1&amp;gridsearch=0&amp;model=BOTORCH_MODULAR&amp;external_generator=&amp;n_estimators_randomforest=100&amp;installation_method=clone&amp;run_mode=local&amp;decimalrounding=4&amp;disable_tqdm=0&amp;verbose_tqdm=0&amp;force_local_execution=0&amp;auto_exclude_defective_hosts=0&amp;show_sixel_general=0&amp;show_sixel_trial_index_result=0&amp;show_sixel_scatter=0&amp;show_worker_percentage_table_at_end=0&amp;enforce_sequential_optimization=0&amp;occ=0&amp;occ_type=euclid&amp;no_sleep=0&amp;slurm_use_srun=0&amp;verbose_break_run_search_table=0&amp;abbreviate_job_names=0&amp;main_process_gb=8&amp;max_nr_of_zero_results=50&amp;pareto_front_confidence=1&amp;slurm_signal_delay_s=0&amp;max_failed_jobs=0&amp;exclude=&amp;username=&amp;generation_strategy=&amp;root_venv_dir=&amp;workdir=&amp;parameter_0_name=epochs&amp;parameter_0_type=range&amp;parameter_0_min=10&amp;parameter_0_max=200&amp;parameter_0_number_type=int&amp;parameter_0_log_scale=false&amp;parameter_1_name=lr&amp;parameter_1_type=range&amp;parameter_1_min=0.0001&amp;parameter_1_max=0.01&amp;parameter_1_number_type=float&amp;parameter_1_log_scale=false&amp;parameter_2_name=bsz&amp;parameter_2_type=range&amp;parameter_2_min=4&amp;parameter_2_max=32&amp;parameter_2_number_type=int&amp;parameter_2_log_scale=false&amp;parameter_3_name=da&amp;parameter_3_type=range&amp;parameter_3_min=10&amp;parameter_3_max=100&amp;parameter_3_number_type=int&amp;parameter_3_log_scale=false&amp;parameter_4_name=db&amp;parameter_4_type=range&amp;parameter_4_min=10&amp;parameter_4_max=100&amp;parameter_4_number_type=int&amp;parameter_4_log_scale=false&amp;partition=barnard&amp;num_parameters=5', '_blank')">GUI page with all the settings of this job</button><br><br><h2>Experiment overview:              </h2><table cellspacing="0" cellpadding="5"><thead><tr><th> Setting</th><th>Value           </th></tr></thead><tbody><tr><td> Model for non-random steps</td><td>BOTORCH_MODULAR </td></tr><tr><td> Max. nr. evaluations</td><td>2000            </td></tr><tr><td> Number random steps</td><td>50              </td></tr><tr><td> Nr. of workers (parameter)</td><td>50              </td></tr><tr><td> Main process memory (GB)</td><td>8               </td></tr><tr><td> Worker memory (GB)</td><td>10              </td></tr></tbody></table><h2>Experiment parameters:                       </h2><table cellspacing="0" cellpadding="5"><thead><tr><th> Name</th><th>Type</th><th>Lower bound</th><th>Upper bound</th><th>Type</th><th>Log Scale? </th></tr></thead><tbody><tr><td> epochs</td><td>range</td><td>10</td><td>200</td><td>int</td><td>No         </td></tr><tr><td> lr</td><td>range</td><td>0.0001</td><td>0.01</td><td>float</td><td>No         </td></tr><tr><td> bsz</td><td>range</td><td>4</td><td>32</td><td>int</td><td>No         </td></tr><tr><td> da</td><td>range</td><td>10</td><td>100</td><td>int</td><td>No         </td></tr><tr><td> db</td><td>range</td><td>10</td><td>100</td><td>int</td><td>No         </td></tr></tbody></table><h2>Number of evaluations</h2>
			<table>
			<tbody>
			<tr>
			<th>Failed</th>
			<th>Succeeded</th>
			<th>Running</th>
			<th>Total</th>
			</tr>
			<tr>
			<td>0</td>
			<td>345</td>
			<td>1</td>
			<td>346</td>
			</tr>
			</tbody>
			</table>
			<h2>Result names and types</h2>
			<table>
			<tr><th>name</th><th>min/max</th></tr>
			<tr>
			<td>RESULT</td>
			<td>min</td>
			</tr>
			</table>
			<h2>Last progressbar status</h2>
			<tt>2025-05-07 22:30:19: BoTorchModel, best RESULT: 0.16842105263157892, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job</tt><br>
			<h2>Git-Version</h2>
			<tt>Commit: 239ad60f178b387e77b7a08ec08d8ede567899b7 (6091)
			</tt>
			<h1>&nbsp;Results</h1>
			<div id='tab_results_csv_table'></div>
			<button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("tab_results_csv_table_pre")'> Copy raw data to clipboard</button>
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<pre id='tab_results_csv_table_pre'>trial_index,arm_name,trial_status,generation_method,generation_node,RESULT,epochs,lr,bsz,da,db
0,0_0,COMPLETED,Sobol,SOBOL,0.300000000000000044408920985006,72,0.002159496855735779010515562604,5,10,43
1,1_0,COMPLETED,Sobol,SOBOL,0.247368421052631570766777713288,152,0.008417613819148392351188192606,20,76,63
2,2_0,COMPLETED,Sobol,SOBOL,0.273684210526315752076698117889,187,0.004052058681845665741305673180,11,39,88
3,3_0,COMPLETED,Sobol,SOBOL,0.621052631578947300639015338675,12,0.005219838040601462378353936344,25,93,16
4,4_0,COMPLETED,Sobol,SOBOL,0.305263157894736791853063095914,53,0.003484899180196225632055728738,22,82,25
5,5_0,COMPLETED,Sobol,SOBOL,0.236842105263157853833888566442,169,0.007131449778471143224889416956,8,50,92
6,6_0,COMPLETED,Sobol,SOBOL,0.415789473684210486581491750258,110,0.000292149827815592290271989873,31,65,70
7,7_0,COMPLETED,Sobol,SOBOL,0.268421052631578893610253544466,90,0.009019060893822461108526589157,16,21,44
8,8_0,COMPLETED,Sobol,SOBOL,0.363157894736842123961650941055,104,0.004684118163399399181745508258,31,47,59
9,9_0,COMPLETED,Sobol,SOBOL,0.294736842105263185942476411583,119,0.005856737259868532823048337121,17,85,33
10,10_0,COMPLETED,Sobol,SOBOL,0.289473684210526327476031838160,155,0.001568516799993813215507998393,25,30,14
11,11_0,COMPLETED,Sobol,SOBOL,0.294736842105263185942476411583,45,0.007821812945324928614820869655,10,56,80
12,12_0,COMPLETED,Sobol,SOBOL,0.405263157894736880670905065926,27,0.000885487682744860770192585342,14,67,99
13,13_0,COMPLETED,Sobol,SOBOL,0.268421052631578893610253544466,197,0.009617262384947389622369406936,29,18,27
14,14_0,COMPLETED,Sobol,SOBOL,0.357894736842105265495206367632,137,0.002855278081446886283972785847,6,96,54
15,15_0,COMPLETED,Sobol,SOBOL,0.278947368421052610543142691313,62,0.006497021691780537760996239172,20,36,74
16,16_0,COMPLETED,Sobol,SOBOL,0.347368421052631548562317220785,67,0.003181572284922003657908762264,17,63,20
17,17_0,COMPLETED,Sobol,SOBOL,0.305263157894736791853063095914,130,0.006828149437066168350729533643,32,25,86
18,18_0,COMPLETED,Sobol,SOBOL,0.357894736842105265495206367632,189,0.001216615944355726314229926288,10,80,64
19,19_0,COMPLETED,Sobol,SOBOL,0.336842105263157942651730536454,31,0.009943555924575776805429683236,24,54,38
20,20_0,COMPLETED,Sobol,SOBOL,0.431578947368421061980825470528,36,0.001856138612143695557424316611,27,43,48
21,21_0,COMPLETED,Sobol,SOBOL,0.294736842105263185942476411583,159,0.008114269184414296676166600264,13,92,69
22,22_0,COMPLETED,Sobol,SOBOL,0.331578947368421084185285963031,124,0.004976573886163533806670233872,21,14,93
23,23_0,COMPLETED,Sobol,SOBOL,0.247368421052631570766777713288,97,0.006144359735865146873723396936,6,75,21
24,24_0,COMPLETED,Sobol,SOBOL,0.410526315789473739137349639350,81,0.000579772082529962239257070866,18,100,82
25,25_0,COMPLETED,Sobol,SOBOL,0.363157894736842123961650941055,114,0.009311516690347344110678662332,4,34,10
26,26_0,COMPLETED,Sobol,SOBOL,0.331578947368421084185285963031,175,0.003777355640567839258764371024,27,71,37
27,27_0,COMPLETED,Sobol,SOBOL,0.342105263157894690095872647362,46,0.007419071516860276972737953116,12,17,58
28,28_0,COMPLETED,Sobol,SOBOL,0.315789473684210508785952242761,16,0.004378352442756295453962778197,8,28,76
29,29_0,COMPLETED,Sobol,SOBOL,0.300000000000000044408920985006,181,0.005550966228451580629366102215,23,60,50
30,30_0,COMPLETED,Sobol,SOBOL,0.363157894736842123961650941055,145,0.002490624342858791580995747594,15,46,31
31,31_0,COMPLETED,Sobol,SOBOL,0.278947368421052610543142691313,75,0.008743908096384256367628040607,29,89,98
32,32_0,COMPLETED,Sobol,SOBOL,0.405263157894736880670905065926,80,0.003919512849114836598729549877,25,73,46
33,33_0,COMPLETED,Sobol,SOBOL,0.310526315789473650319507669337,143,0.005072050877008587969896336034,10,13,71
34,34_0,COMPLETED,Sobol,SOBOL,0.342105263157894690095872647362,179,0.002022226462699473151923834635,32,89,89
35,35_0,COMPLETED,Sobol,SOBOL,0.352631578947368407028761794209,20,0.008293810995388775295089622830,16,42,25
36,36_0,COMPLETED,Sobol,SOBOL,0.463157894736842101757190448552,50,0.000100348113849759110476241031,6,53,18
37,37_0,COMPLETED,Sobol,SOBOL,0.268421052631578893610253544466,173,0.008853110256697983154738906819,21,78,88
38,38_0,COMPLETED,Sobol,SOBOL,0.352631578947368407028761794209,114,0.003327125069499015704715949582,14,25,61
39,39_0,COMPLETED,Sobol,SOBOL,0.321052631578947367252396816184,87,0.006950882416497917125342009825,28,61,42
40,40_0,COMPLETED,Sobol,SOBOL,0.478947368421052677156524168822,95,0.001378132767602801428408199058,11,87,72
41,41_0,COMPLETED,Sobol,SOBOL,0.326315789473684225718841389607,128,0.007654519567545503902494807846,26,44,53
42,42_0,COMPLETED,Sobol,SOBOL,0.263157894736842146166111433558,165,0.004527379948645830938513956454,5,58,29
43,43_0,COMPLETED,Sobol,SOBOL,0.284210526315789469009587264736,36,0.005675059061031789524320867457,19,28,99
44,44_0,COMPLETED,Sobol,SOBOL,0.352631578947368407028761794209,30,0.002721653866581618622794147555,30,17,78
45,45_0,COMPLETED,Sobol,SOBOL,0.363157894736842123961650941055,194,0.006350236789230257958283054620,16,70,13
46,46_0,COMPLETED,Sobol,SOBOL,0.410526315789473739137349639350,134,0.000746917662210762616122050606,22,33,35
47,47_0,COMPLETED,Sobol,SOBOL,0.363157894736842123961650941055,65,0.009494835346657782421120330696,7,98,60
48,48_0,COMPLETED,Sobol,SOBOL,0.368421052631578982428095514479,58,0.001034539474360644849618151575,26,23,23
49,49_0,COMPLETED,Sobol,SOBOL,0.226315789473684247923301882111,139,0.009787291585747152217189537282,12,66,93
50,50_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.310526315789473650319507669337,114,0.009191625632155343839091443670,26,49,75
51,51_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.210526315789473672523968161840,122,0.008973844702663847164303412285,8,48,92
52,52_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.273684210526315752076698117889,151,0.009665452023960833041749118877,20,56,96
53,53_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,126,0.008561401127126512175524730708,4,56,100
54,54_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,126,0.010000000000000000208166817117,4,45,98
55,55_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.263157894736842146166111433558,172,0.006149551698917648211162312322,13,19,50
56,56_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,119,0.010000000000000000208166817117,11,97,27
57,57_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,179,0.010000000000000000208166817117,4,33,100
58,58_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.278947368421052610543142691313,196,0.007391579804199998812719307750,18,64,97
59,59_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.284210526315789469009587264736,180,0.008285225795562229170188039973,32,10,100
60,60_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.263157894736842146166111433558,178,0.010000000000000000208166817117,32,46,100
61,61_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.205263157894736814057523588417,172,0.010000000000000000208166817117,4,38,45
62,62_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,200,0.007519436911065424493372244541,4,10,100
63,63_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.352631578947368407028761794209,56,0.010000000000000000208166817117,4,10,100
64,64_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.231578947368421106389746455534,200,0.010000000000000000208166817117,4,60,63
65,65_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.257894736842105287699666860135,168,0.009319292839995364785554698983,32,41,22
66,66_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.199999999999999955591079014994,169,0.010000000000000000208166817117,4,11,14
67,67_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.284210526315789469009587264736,175,0.010000000000000000208166817117,4,55,62
68,68_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,200,0.010000000000000000208166817117,4,21,32
69,69_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,181,0.010000000000000000208166817117,4,31,17
70,70_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.321052631578947367252396816184,170,0.007276118271745541689343728109,4,10,10
71,71_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.336842105263157942651730536454,200,0.010000000000000000208166817117,32,94,100
72,72_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.284210526315789469009587264736,200,0.010000000000000000208166817117,4,89,100
73,73_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.278947368421052610543142691313,200,0.010000000000000000208166817117,32,50,61
74,74_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.342105263157894690095872647362,141,0.009347902986113378401289430997,32,10,30
75,75_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.352631578947368407028761794209,200,0.007619937421204864627655162224,4,57,77
76,76_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.231578947368421106389746455534,200,0.007741583027187160306881175131,32,41,67
77,77_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,200,0.010000000000000000208166817117,4,94,10
78,78_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.205263157894736814057523588417,154,0.010000000000000000208166817117,32,68,99
79,79_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.294736842105263185942476411583,149,0.010000000000000000208166817117,32,38,74
80,80_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.273684210526315752076698117889,200,0.010000000000000000208166817117,32,61,100
81,81_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.310526315789473650319507669337,124,0.010000000000000000208166817117,32,56,100
82,82_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,163,0.008221007450340026348478694729,32,43,99
83,83_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.268421052631578893610253544466,180,0.005539100989525490119358419605,32,12,12
84,84_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.315789473684210508785952242761,200,0.008217068266138187124236758052,32,62,77
85,85_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.321052631578947367252396816184,200,0.006635305364903319562397410181,32,49,14
86,86_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.289473684210526327476031838160,188,0.002849797684903414632384688332,16,10,10
87,87_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.357894736842105265495206367632,129,0.010000000000000000208166817117,4,86,100
88,88_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,200,0.010000000000000000208166817117,32,13,86
89,89_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.210526315789473672523968161840,200,0.005718411287274551002557387847,32,37,93
90,90_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.215789473684210530990412735264,200,0.005890238504006059007400697425,4,28,20
91,91_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.221052631578947389456857308687,198,0.007473330891646649994097817427,10,47,100
92,92_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.263157894736842146166111433558,195,0.006947588586385951281432227233,32,57,96
93,93_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.257894736842105287699666860135,200,0.006999312336574543130796044466,4,47,55
94,94_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,200,0.003862484221283773652699800039,9,12,76
95,95_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.273684210526315752076698117889,148,0.007496572519135360525288636069,32,60,100
96,96_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.252631578947368429233222286712,200,0.006388692916692817642954071999,4,39,83
97,97_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.300000000000000044408920985006,200,0.004015615504888952851103578467,31,13,10
98,98_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,197,0.008814566263303845114474022182,4,48,87
99,99_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,198,0.006395623121673584855761962586,32,19,81
100,100_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.336842105263157942651730536454,199,0.000100000000000000004792173602,6,14,99
101,101_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.336842105263157942651730536454,200,0.003832715794613859080358642117,32,14,100
102,102_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,200,0.005647053488861257866671117256,4,39,100
103,103_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.278947368421052610543142691313,132,0.006992551159871015359348334073,4,44,100
104,104_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.336842105263157942651730536454,197,0.006650613252558020167815033830,31,47,59
105,105_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,178,0.005200489102998382372200492085,4,10,10
106,106_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.273684210526315752076698117889,125,0.006618492573964776005956966998,4,11,68
107,107_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.315789473684210508785952242761,200,0.003405501770698202753523409214,4,10,10
108,108_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.257894736842105287699666860135,198,0.006353666458654739189471083449,16,10,10
109,109_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,200,0.007411690616140210324802595210,8,29,36
110,110_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.357894736842105265495206367632,171,0.007444835264396485081939136563,4,28,58
111,111_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.284210526315789469009587264736,113,0.007303532469567609354543780142,6,10,10
112,112_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.263157894736842146166111433558,185,0.006379777375644118779518532136,12,100,99
113,113_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,131,0.010000000000000000208166817117,32,41,99
114,114_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.405263157894736880670905065926,13,0.009639939004401116770526236621,32,12,100
115,115_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.226315789473684247923301882111,196,0.006964278907844177399222296287,6,79,100
116,116_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,137,0.007201578440295736648069091501,32,10,10
117,117_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.331578947368421084185285963031,196,0.007269895243506473841987869378,32,97,100
118,118_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.205263157894736814057523588417,176,0.007715661976693974355434590962,5,68,100
119,119_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.284210526315789469009587264736,182,0.007126128842221518891464349110,32,13,36
120,120_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,150,0.005608510325837110475910574081,4,37,10
121,121_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,199,0.010000000000000000208166817117,4,58,100
122,122_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,176,0.007544040089995325548688498429,4,54,100
123,123_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.268421052631578893610253544466,200,0.006587876248689402726432806645,24,74,98
124,124_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,200,0.007245983778395012619988335700,32,35,10
125,125_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,199,0.007716978661716038072337919829,32,53,100
126,126_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.215789473684210530990412735264,200,0.010000000000000000208166817117,11,100,28
127,127_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.321052631578947367252396816184,164,0.008732151751778332790521197637,4,61,100
128,128_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.263157894736842146166111433558,200,0.007955268831545597718601925408,4,100,100
129,129_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.331578947368421084185285963031,171,0.010000000000000000208166817117,32,65,36
130,130_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.273684210526315752076698117889,146,0.010000000000000000208166817117,32,96,85
131,131_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,200,0.009247274038975425089481596785,32,100,10
132,132_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.305263157894736791853063095914,170,0.010000000000000000208166817117,15,100,100
133,133_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,139,0.010000000000000000208166817117,4,10,62
134,134_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.305263157894736791853063095914,200,0.005300411505429713371340127992,22,10,60
135,135_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,200,0.009147550775024406582991431947,32,100,100
136,136_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.252631578947368429233222286712,200,0.006276218137709642375110519197,4,14,10
137,137_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.226315789473684247923301882111,200,0.008090331956127596452210681832,4,100,72
138,138_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.215789473684210530990412735264,170,0.008065431311046046200519121783,32,65,100
139,139_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.236842105263157853833888566442,200,0.010000000000000000208166817117,25,72,81
140,140_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.221052631578947389456857308687,200,0.006818927987493387209150252914,4,67,74
141,141_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.215789473684210530990412735264,181,0.009807948852069751921600726519,18,71,100
142,142_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.278947368421052610543142691313,192,0.008778703904754868794779731900,10,78,86
143,143_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.284210526315789469009587264736,200,0.008723836780966809020809726860,20,72,100
144,144_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.357894736842105265495206367632,200,0.010000000000000000208166817117,21,82,100
145,145_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,200,0.008205562673371776319375392461,4,83,97
146,146_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.315789473684210508785952242761,200,0.008188855513530147317569074517,32,71,100
147,147_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.300000000000000044408920985006,194,0.005240123944012948717374733576,32,10,29
148,148_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,149,0.008456781280274027964849459238,4,82,94
149,149_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.278947368421052610543142691313,107,0.010000000000000000208166817117,32,88,100
150,150_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,200,0.009220205928450166121823627918,13,93,100
151,151_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.231578947368421106389746455534,200,0.006636325520254724059932005531,4,53,14
152,152_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.236842105263157853833888566442,16,0.009224157563270178952774536185,4,72,100
153,153_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,131,0.009055002469130544670572469101,4,42,19
154,154_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.226315789473684247923301882111,200,0.005210675979331394307159097679,4,10,35
155,155_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,194,0.006440283186455347461119025354,30,10,94
156,156_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.342105263157894690095872647362,64,0.010000000000000000208166817117,32,66,96
157,157_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.294736842105263185942476411583,200,0.006366795333871817959281447230,32,10,47
158,158_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.263157894736842146166111433558,187,0.006161156915159203724396963509,6,22,60
159,159_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.352631578947368407028761794209,200,0.006093395887556598243539607296,4,10,62
160,160_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.321052631578947367252396816184,200,0.008410195902360365766137206833,19,55,77
161,161_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.421052631578947345047936323681,200,0.000100000000000000004792173602,4,10,10
162,162_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.352631578947368407028761794209,11,0.009195792340030112949067486738,17,63,98
163,163_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.221052631578947389456857308687,200,0.006861979032168725838036760223,4,61,100
164,164_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.321052631578947367252396816184,79,0.004305893255039590014621175840,4,10,97
165,165_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.310526315789473650319507669337,197,0.006910819569921325747352547353,32,81,79
166,166_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.294736842105263185942476411583,200,0.005523384869178977162051946692,13,64,100
167,167_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.205263157894736814057523588417,199,0.007296484055514660359287315572,32,17,100
168,168_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.226315789473684247923301882111,200,0.010000000000000000208166817117,4,100,100
169,169_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.257894736842105287699666860135,146,0.005685671836950514750064211711,25,10,98
170,170_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,200,0.006732117230026759061023433617,32,46,100
171,171_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.226315789473684247923301882111,169,0.005610212921339534884734856490,4,10,91
172,172_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.221052631578947389456857308687,200,0.007191064665225875736365157564,16,34,100
173,173_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.321052631578947367252396816184,200,0.005883680150030681961503820077,14,17,100
174,174_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,194,0.006791375637041745412514348601,5,27,100
175,175_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,151,0.007240478928850010639783896238,4,14,100
176,176_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.236842105263157853833888566442,160,0.007236919143649459158773584733,32,21,100
177,177_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.405263157894736880670905065926,29,0.007337152006347317199919100261,32,10,16
178,178_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.342105263157894690095872647362,11,0.005664558821845147584816970721,4,10,23
179,179_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.321052631578947367252396816184,200,0.007048677748485666395839022158,20,55,95
180,180_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.273684210526315752076698117889,101,0.008653011502511638586288000852,4,100,100
181,181_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,200,0.007186284729407227574171646012,19,21,64
182,182_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.252631578947368429233222286712,194,0.008167460065066396365796030921,25,44,98
183,183_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.352631578947368407028761794209,200,0.005884680410065626192384069526,4,93,97
184,184_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.278947368421052610543142691313,186,0.008263050788502663418499949444,23,98,100
185,185_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.273684210526315752076698117889,199,0.007572659872840815063754771330,14,57,68
186,186_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.210526315789473672523968161840,200,0.010000000000000000208166817117,32,28,100
187,187_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.315789473684210508785952242761,137,0.006198461673078726162644525033,32,10,100
188,188_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.268421052631578893610253544466,162,0.007151458931079012794340687975,28,10,99
189,189_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,200,0.008358907818288859037370031047,32,10,63
190,190_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.278947368421052610543142691313,162,0.008362397414184550084592650876,21,57,99
191,191_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.205263157894736814057523588417,200,0.008014716077195765259189030871,4,73,24
192,192_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,100,0.008622640024968035443730940415,19,95,100
193,193_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,200,0.009279379162970363692508612985,4,71,44
194,194_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,150,0.007395487117138771840374467104,4,98,37
195,195_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.300000000000000044408920985006,161,0.009788062287147382412033636001,27,15,100
196,196_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.294736842105263185942476411583,136,0.007633403568166305212805422542,16,48,96
197,197_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.352631578947368407028761794209,10,0.010000000000000000208166817117,21,97,96
198,198_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.352631578947368407028761794209,200,0.005019583766906519396722163862,32,10,100
199,199_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.294736842105263185942476411583,200,0.010000000000000000208166817117,24,54,100
200,200_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.352631578947368407028761794209,150,0.008452201967786758182721307264,28,91,100
201,201_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.310526315789473650319507669337,200,0.007682419943136787644777374595,27,53,100
202,202_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.257894736842105287699666860135,200,0.007060821289075202254748031550,26,40,81
203,203_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.284210526315789469009587264736,200,0.005675232543736551983626359430,17,41,67
204,204_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,197,0.009080733342261820134622141154,7,46,10
205,205_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.347368421052631548562317220785,143,0.007393377912453571489115322635,32,36,100
206,206_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,200,0.006901989778956893646644221718,4,97,32
207,207_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,200,0.010000000000000000208166817117,4,98,70
208,208_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,132,0.006962284509711036406542916666,4,72,100
209,209_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.205263157894736814057523588417,200,0.006647987949018534063749807927,8,33,10
210,210_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.252631578947368429233222286712,200,0.008494435748330803406802580469,32,45,82
211,211_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.268421052631578893610253544466,200,0.007109808041845007073322726399,32,10,10
212,212_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.215789473684210530990412735264,116,0.009037189097683407529304489003,32,14,100
213,213_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,200,0.007050754517434964889488480111,5,17,47
214,214_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.263157894736842146166111433558,200,0.010000000000000000208166817117,31,11,10
215,215_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.347368421052631548562317220785,200,0.007079465356634386148659832116,20,12,10
216,216_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,200,0.010000000000000000208166817117,20,48,56
217,217_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.226315789473684247923301882111,200,0.010000000000000000208166817117,19,18,100
218,218_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.357894736842105265495206367632,22,0.009551570578135821013021633519,4,100,100
219,219_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,200,0.008540657780068185503385969071,22,35,94
220,220_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,200,0.008090921997057680392639866795,18,47,100
221,221_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.226315789473684247923301882111,200,0.009203202713349602215320288678,14,55,100
222,222_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,38,0.010000000000000000208166817117,4,15,10
223,223_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.257894736842105287699666860135,200,0.010000000000000000208166817117,18,100,100
224,224_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,200,0.010000000000000000208166817117,4,10,31
225,225_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,188,0.008323822847507558742030653320,23,10,88
226,226_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.189473684210526349680492330663,183,0.009432517781791624131293438893,25,42,100
227,227_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.284210526315789469009587264736,200,0.008795069051441036303562448495,32,50,100
228,228_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.215789473684210530990412735264,173,0.010000000000000000208166817117,20,55,100
229,229_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.357894736842105265495206367632,110,0.010000000000000000208166817117,32,10,100
230,230_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.236842105263157853833888566442,197,0.010000000000000000208166817117,18,69,100
231,231_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.199999999999999955591079014994,198,0.010000000000000000208166817117,16,40,76
232,232_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.215789473684210530990412735264,200,0.010000000000000000208166817117,15,67,97
233,233_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.210526315789473672523968161840,200,0.008722545113936927552167333033,18,60,100
234,234_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.263157894736842146166111433558,196,0.008447888951106666266532840837,24,37,15
235,235_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.305263157894736791853063095914,200,0.010000000000000000208166817117,19,55,89
236,236_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,200,0.010000000000000000208166817117,32,40,10
237,237_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.289473684210526327476031838160,200,0.008373797244966077468752985169,21,46,92
238,238_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.226315789473684247923301882111,200,0.007788979215599343627896011810,14,62,99
239,239_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.215789473684210530990412735264,187,0.008986995637389359400937216549,22,56,100
240,240_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.273684210526315752076698117889,200,0.005372494801945831149891930067,12,46,25
241,241_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,194,0.007619482658711060861500552477,21,52,100
242,242_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.205263157894736814057523588417,199,0.010000000000000000208166817117,18,67,71
243,243_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.252631578947368429233222286712,200,0.008635857604643880358619156823,24,54,100
244,244_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.221052631578947389456857308687,195,0.008350780281565614929228935637,4,82,51
245,245_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.331578947368421084185285963031,200,0.010000000000000000208166817117,32,46,100
246,246_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,200,0.010000000000000000208166817117,22,44,100
247,247_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.315789473684210508785952242761,199,0.006859634022091961810807525524,24,27,98
248,248_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,200,0.007954020966480139856469300241,17,40,66
249,249_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.336842105263157942651730536454,158,0.007967435937925010369653477937,22,39,100
250,250_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,200,0.008107368603441198265380229770,20,46,61
251,251_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.231578947368421106389746455534,200,0.009415320977673490368542452700,21,66,63
252,252_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,200,0.010000000000000000208166817117,17,89,71
253,253_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.221052631578947389456857308687,135,0.005907636888546158489277093651,19,11,69
254,254_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,200,0.010000000000000000208166817117,12,78,78
255,255_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.205263157894736814057523588417,200,0.010000000000000000208166817117,16,83,100
256,256_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.326315789473684225718841389607,200,0.006027159327444729999823103128,16,32,49
257,257_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,186,0.010000000000000000208166817117,23,10,43
258,258_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,200,0.008689520534490792827431171474,15,57,67
259,259_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.310526315789473650319507669337,200,0.010000000000000000208166817117,19,47,100
260,260_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.331578947368421084185285963031,200,0.008771778642056216393485534866,26,92,100
261,261_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.268421052631578893610253544466,200,0.008346937921320464817687145853,21,67,76
262,262_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,200,0.010000000000000000208166817117,22,67,100
263,263_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.305263157894736791853063095914,200,0.004996106853106147514809176613,19,17,11
264,264_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,200,0.004639546748404329429282810793,4,84,29
265,265_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.331578947368421084185285963031,193,0.003534065841138753129996308289,15,22,10
266,266_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,200,0.008197525385286773616511091234,14,54,39
267,267_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.321052631578947367252396816184,200,0.010000000000000000208166817117,9,72,100
268,268_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.310526315789473650319507669337,200,0.004345771156575503439689622809,24,10,11
269,269_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.252631578947368429233222286712,196,0.008952552377585501833245906766,18,68,84
270,270_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.236842105263157853833888566442,200,0.008273051645066689316343477856,16,68,66
271,271_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.278947368421052610543142691313,191,0.006917195431729271370979716949,19,52,71
272,272_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.210526315789473672523968161840,179,0.007081260330705821046115566730,23,11,98
273,273_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,198,0.010000000000000000208166817117,16,61,16
274,274_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.210526315789473672523968161840,200,0.007717568091060600203590080781,21,22,100
275,275_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.294736842105263185942476411583,182,0.010000000000000000208166817117,23,65,100
276,276_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.236842105263157853833888566442,200,0.008112877661988497982048507140,12,66,75
277,277_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.273684210526315752076698117889,200,0.007488419040197006812387137131,17,46,68
278,278_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.278947368421052610543142691313,191,0.006817054391210549540991436857,20,12,21
279,279_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,200,0.010000000000000000208166817117,26,100,15
280,280_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.215789473684210530990412735264,200,0.008613244195159505678383027316,11,100,78
281,281_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.273684210526315752076698117889,200,0.008070014064729146008314586425,15,79,84
282,282_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.273684210526315752076698117889,200,0.009141647815845721850025462629,11,71,99
283,283_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.215789473684210530990412735264,200,0.008694277327384819162303664086,32,10,93
284,284_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.294736842105263185942476411583,200,0.009200077393416050686170137851,20,47,66
285,285_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,200,0.007507689057276314449629328607,4,94,10
286,286_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.215789473684210530990412735264,200,0.010000000000000000208166817117,32,10,100
287,287_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.300000000000000044408920985006,199,0.008517063318861985490859645154,28,32,96
288,288_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,126,0.008564522668471838406922813647,13,90,99
289,289_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,181,0.009585620321582308950292272698,14,63,80
290,290_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,167,0.006740503075796551446519089268,25,13,48
291,291_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.289473684210526327476031838160,200,0.007712873278365775173148755073,17,46,82
292,292_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.226315789473684247923301882111,199,0.010000000000000000208166817117,24,54,81
293,293_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.231578947368421106389746455534,85,0.008950620350548381398692043831,4,96,100
294,294_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.215789473684210530990412735264,200,0.008800850862490603929155774665,23,19,74
295,295_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,200,0.010000000000000000208166817117,18,95,75
296,296_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.263157894736842146166111433558,199,0.009118120316465956262663716814,21,45,100
297,297_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.289473684210526327476031838160,196,0.007625751617686566015408278219,23,21,69
298,298_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,200,0.007916451674653920966839848461,25,10,80
299,299_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.268421052631578893610253544466,155,0.010000000000000000208166817117,16,73,100
300,300_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.226315789473684247923301882111,138,0.006630719446577613626625513632,4,69,100
301,301_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,177,0.008422487308230952249288314704,15,86,100
302,302_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,200,0.010000000000000000208166817117,4,78,77
303,303_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.321052631578947367252396816184,174,0.004049985575069868330710942672,20,15,100
304,304_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.278947368421052610543142691313,182,0.010000000000000000208166817117,23,69,63
305,305_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.215789473684210530990412735264,200,0.008897920981321699382404766254,19,66,86
306,306_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.263157894736842146166111433558,186,0.008114307449238265801394476284,18,59,86
307,307_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,82,0.010000000000000000208166817117,4,98,89
308,308_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.284210526315789469009587264736,199,0.005081986995639385315537417398,4,37,27
309,309_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,200,0.009084563763158011104326128304,23,54,89
310,310_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.263157894736842146166111433558,167,0.006773720335596076537465481948,4,100,88
311,311_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,193,0.007938052137517170522840181945,4,67,46
312,312_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.305263157894736791853063095914,177,0.007651243603322510286601776386,21,66,100
313,313_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,174,0.009228559003721730283342772339,10,87,62
314,314_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.336842105263157942651730536454,169,0.009020851526925589836114482978,30,11,45
315,315_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,178,0.008754222440827873208402110095,17,53,100
316,316_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.210526315789473672523968161840,200,0.007018616354017095243511548119,11,99,100
317,317_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.300000000000000044408920985006,200,0.008668048713510448019525789221,17,54,87
318,318_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.236842105263157853833888566442,197,0.006927245078039013029269632682,21,10,51
319,319_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.221052631578947389456857308687,126,0.006899321816495437159622028389,6,93,98
320,320_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.278947368421052610543142691313,149,0.006446219156362736554810588530,20,25,39
321,321_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.273684210526315752076698117889,200,0.009065353316835807542806158210,17,71,100
322,322_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.289473684210526327476031838160,134,0.009213101923850481808631052161,22,100,100
323,323_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.263157894736842146166111433558,200,0.008215123645444806499416046108,13,94,100
324,324_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.221052631578947389456857308687,200,0.007765890716633994453332867636,16,73,100
325,325_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.300000000000000044408920985006,111,0.008653153456307179774986693133,32,16,99
326,326_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.273684210526315752076698117889,134,0.008338424920946161875145996589,19,56,100
327,327_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.268421052631578893610253544466,190,0.008665603428693383764036539674,24,11,23
328,328_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.168421052631578915814714036969,196,0.010000000000000000208166817117,23,14,100
329,329_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.326315789473684225718841389607,165,0.008283471963658842543432037075,28,10,100
330,330_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.357894736842105265495206367632,200,0.010000000000000000208166817117,26,13,100
331,331_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.252631578947368429233222286712,163,0.007138298909025157616692336404,14,68,98
332,332_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,142,0.010000000000000000208166817117,8,95,61
333,333_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.236842105263157853833888566442,90,0.006958279122684180896529770877,8,91,100
334,334_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,200,0.007004839123860503134755273180,16,81,100
335,335_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.289473684210526327476031838160,200,0.008926864613218772268043998963,18,87,100
336,336_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.300000000000000044408920985006,148,0.005325037396815215581802327449,23,10,10
337,337_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.257894736842105287699666860135,162,0.008485487525987250173598042124,18,73,100
338,338_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.263157894736842146166111433558,179,0.006686999131018937780890354361,18,30,79
339,339_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.278947368421052610543142691313,116,0.008837301459464990890935176537,14,94,97
340,340_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.294736842105263185942476411583,102,0.006074442441503001034741604514,21,14,98
341,341_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,200,0.010000000000000000208166817117,12,15,10
342,342_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.263157894736842146166111433558,200,0.006605195460404012994248823532,7,100,99
343,343_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.194736842105263208146936904086,199,0.005157929654024255225475137365,11,10,25
344,344_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.268421052631578893610253544466,200,0.005593363859429216662644268609,13,52,55
345,345_0,RUNNING,BoTorch,BOTORCH_MODULAR,,189,0.003232736700506971816437840062,19,15,96
</pre>
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			<script>
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			<h1>&nbsp;Progressbar log</h1>
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<pre id='simple_pre_tab_tab_progressbar_log'>2025-05-07 12:30:21: SOBOL, Started OmniOpt2 run...
2025-05-07 12:30:27: SOBOL, getting new HP set     
2025-05-07 12:30:31: Sobol, eval start             
2025-05-07 12:30:35: Sobol, starting new job       
2025-05-07 12:30:38: Sobol, unknown 1&sum;1 (2%/50), started new job
2025-05-07 12:30:43: Sobol, unknown 1&sum;1 (2%/50), getting new HP set
2025-05-07 12:30:46: Sobol, pending 1&sum;1 (2%/50), eval start        
2025-05-07 12:30:49: Sobol, pending 1&sum;1 (2%/50), starting new job  
2025-05-07 12:30:54: Sobol, running/unknown 1/1&sum;2 (4%/50), started new job
2025-05-07 12:31:00: Sobol, running/unknown 1/1&sum;2 (4%/50), getting new HP set
2025-05-07 12:31:03: Sobol, running/pending 1/1&sum;2 (4%/50), eval start        
2025-05-07 12:31:06: Sobol, running/pending 1/1&sum;2 (4%/50), starting new job  
2025-05-07 12:31:11: Sobol, running/pending/unknown 1/1/1&sum;3 (6%/50), started new job
2025-05-07 12:31:17: Sobol, running/pending 1/2&sum;3 (6%/50), getting new HP set       
2025-05-07 12:31:20: Sobol, running/pending 1/2&sum;3 (6%/50), eval start               
2025-05-07 12:31:23: Sobol, running/pending 1/2&sum;3 (6%/50), starting new job         
2025-05-07 12:31:27: Sobol, completed/running/unknown 1/2/1&sum;4 (8%/50), started new job
2025-05-07 12:31:31: Sobol, completed/running/pending 1/2/1&sum;4 (8%/50), new result: 0.30000000000000004
2025-05-07 12:31:38: Sobol, best RESULT: 0.30000000000000004, running/pending 2/1&sum;3 (6%/50), finishing jobs (_get_next_trials), finished 1 job
2025-05-07 12:31:41: Sobol, best RESULT: 0.30000000000000004, running/pending 2/1&sum;3 (6%/50), getting new HP set                               
2025-05-07 12:31:44: Sobol, best RESULT: 0.30000000000000004, running/pending 2/1&sum;3 (6%/50), eval start                                       
2025-05-07 12:31:48: Sobol, best RESULT: 0.30000000000000004, running/pending 2/1&sum;3 (6%/50), starting new job                                 
2025-05-07 12:31:53: Sobol, best RESULT: 0.30000000000000004, completed/pending/unknown 2/1/1&sum;4 (8%/50), started new job                      
2025-05-07 12:31:57: Sobol, best RESULT: 0.30000000000000004, completed/running/unknown 2/1/1&sum;4 (8%/50), new result: 0.24736842105263157      
2025-05-07 12:32:05: Sobol, best RESULT: 0.24736842105263157, completed/running 1/2&sum;3 (6%/50), new result: 0.27368421052631575                
2025-05-07 12:32:11: Sobol, best RESULT: 0.24736842105263157, running 2&sum;2 (4%/50), finishing jobs (_get_next_trials), finished 2 jobs         
2025-05-07 12:32:14: Sobol, best RESULT: 0.24736842105263157, running 2&sum;2 (4%/50), getting new HP set                                         
2025-05-07 12:32:18: Sobol, best RESULT: 0.24736842105263157, running 2&sum;2 (4%/50), eval start                                                 
2025-05-07 12:32:21: Sobol, best RESULT: 0.24736842105263157, running 2&sum;2 (4%/50), starting new job                                           
2025-05-07 12:32:25: Sobol, best RESULT: 0.24736842105263157, completed/unknown 2/1&sum;3 (6%/50), started new job                                
2025-05-07 12:32:29: Sobol, best RESULT: 0.24736842105263157, completed/unknown 2/1&sum;3 (6%/50), new result: 0.6210526315789473                 
2025-05-07 12:32:37: Sobol, best RESULT: 0.24736842105263157, completed/running 1/1&sum;2 (4%/50), new result: 0.3052631578947368                 
2025-05-07 12:32:43: Sobol, best RESULT: 0.24736842105263157, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 2 jobs         
2025-05-07 12:32:46: Sobol, best RESULT: 0.24736842105263157, running 1&sum;1 (2%/50), getting new HP set                                         
2025-05-07 12:32:48: Sobol, best RESULT: 0.24736842105263157, running 1&sum;1 (2%/50), eval start                                                 
2025-05-07 12:32:52: Sobol, best RESULT: 0.24736842105263157, running 1&sum;1 (2%/50), starting new job                                           
2025-05-07 12:32:56: Sobol, best RESULT: 0.24736842105263157, running/unknown 1/1&sum;2 (4%/50), started new job                                  
2025-05-07 12:33:00: Sobol, best RESULT: 0.24736842105263157, completed/unknown 1/1&sum;2 (4%/50), new result: 0.23684210526315785                
2025-05-07 12:33:06: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job          
2025-05-07 12:33:09: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), getting new HP set                                         
2025-05-07 12:33:13: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), eval start                                                 
2025-05-07 12:33:17: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), starting new job                                           
2025-05-07 12:33:23: Sobol, best RESULT: 0.23684210526315785, running/unknown 1/1&sum;2 (4%/50), started new job                                  
2025-05-07 12:33:27: Sobol, best RESULT: 0.23684210526315785, completed/unknown 1/1&sum;2 (4%/50), new result: 0.4157894736842105                 
2025-05-07 12:33:34: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job          
2025-05-07 12:33:39: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), getting new HP set                                         
2025-05-07 12:33:46: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), eval start                                                 
2025-05-07 12:33:50: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), starting new job                                           
2025-05-07 12:33:55: Sobol, best RESULT: 0.23684210526315785, running/unknown 1/1&sum;2 (4%/50), started new job                                  
2025-05-07 12:34:04: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1&sum;2 (4%/50), getting new HP set                               
2025-05-07 12:34:07: Sobol, best RESULT: 0.23684210526315785, completed/running 1/1&sum;2 (4%/50), eval start                                     
2025-05-07 12:34:11: Sobol, best RESULT: 0.23684210526315785, completed/running 1/1&sum;2 (4%/50), starting new job                               
2025-05-07 12:34:16: Sobol, best RESULT: 0.23684210526315785, completed/running/unknown 1/1/1&sum;3 (6%/50), started new job                      
2025-05-07 12:34:20: Sobol, best RESULT: 0.23684210526315785, completed/running/pending 1/1/1&sum;3 (6%/50), new result: 0.2684210526315789       
2025-05-07 12:34:26: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1&sum;2 (4%/50), finishing jobs (_get_next_trials), finished 1 job
2025-05-07 12:34:29: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1&sum;2 (4%/50), getting new HP set                               
2025-05-07 12:34:33: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1&sum;2 (4%/50), eval start                                       
2025-05-07 12:34:36: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1&sum;2 (4%/50), starting new job                                 
2025-05-07 12:34:41: Sobol, best RESULT: 0.23684210526315785, completed/running/unknown 1/1/1&sum;3 (6%/50), started new job                      
2025-05-07 12:34:45: Sobol, best RESULT: 0.23684210526315785, completed/running/unknown 1/1/1&sum;3 (6%/50), new result: 0.3631578947368421       
2025-05-07 12:34:52: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1&sum;2 (4%/50), finishing jobs (_get_next_trials), finished 1 job
2025-05-07 12:34:56: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1&sum;2 (4%/50), getting new HP set                               
2025-05-07 12:35:00: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1&sum;2 (4%/50), eval start                                       
2025-05-07 12:35:04: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1&sum;2 (4%/50), starting new job                                 
2025-05-07 12:35:08: Sobol, best RESULT: 0.23684210526315785, completed/pending/unknown 1/1/1&sum;3 (6%/50), started new job                      
2025-05-07 12:35:11: Sobol, best RESULT: 0.23684210526315785, completed/running 1/2&sum;3 (6%/50), new result: 0.2947368421052632                 
2025-05-07 12:35:19: Sobol, best RESULT: 0.23684210526315785, running 2&sum;2 (4%/50), finishing jobs (_get_next_trials), finished 1 job          
2025-05-07 12:35:22: Sobol, best RESULT: 0.23684210526315785, running 2&sum;2 (4%/50), getting new HP set                                         
2025-05-07 12:35:26: Sobol, best RESULT: 0.23684210526315785, running 2&sum;2 (4%/50), eval start                                                 
2025-05-07 12:35:30: Sobol, best RESULT: 0.23684210526315785, running 2&sum;2 (4%/50), starting new job                                           
2025-05-07 12:35:35: Sobol, best RESULT: 0.23684210526315785, running/completed/unknown 1/1/1&sum;3 (6%/50), started new job                      
2025-05-07 12:35:38: Sobol, best RESULT: 0.23684210526315785, completed/pending 2/1&sum;3 (6%/50), new result: 0.2894736842105263                 
2025-05-07 12:35:46: Sobol, best RESULT: 0.23684210526315785, completed/running 1/1&sum;2 (4%/50), new result: 0.2947368421052632                 
2025-05-07 12:35:55: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 2 jobs         
2025-05-07 12:35:58: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), getting new HP set                                         
2025-05-07 12:36:02: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), eval start                                                 
2025-05-07 12:36:06: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), starting new job                                           
2025-05-07 12:36:10: Sobol, best RESULT: 0.23684210526315785, completed/unknown 1/1&sum;2 (4%/50), started new job                                
2025-05-07 12:36:15: Sobol, best RESULT: 0.23684210526315785, completed/unknown 1/1&sum;2 (4%/50), new result: 0.4052631578947369                 
2025-05-07 12:36:24: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job          
2025-05-07 12:36:27: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), getting new HP set                                         
2025-05-07 12:36:30: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), eval start                                                 
2025-05-07 12:36:33: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), starting new job                                           
2025-05-07 12:36:38: Sobol, best RESULT: 0.23684210526315785, running/unknown 1/1&sum;2 (4%/50), started new job                                  
2025-05-07 12:36:42: Sobol, best RESULT: 0.23684210526315785, completed/pending 1/1&sum;2 (4%/50), new result: 0.2684210526315789                 
2025-05-07 12:36:48: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job          
2025-05-07 12:36:51: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), getting new HP set                                         
2025-05-07 12:36:54: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), eval start                                                 
2025-05-07 12:36:58: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), starting new job                                           
2025-05-07 12:37:04: Sobol, best RESULT: 0.23684210526315785, running/unknown 1/1&sum;2 (4%/50), started new job                                  
2025-05-07 12:37:11: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1&sum;2 (4%/50), getting new HP set                               
2025-05-07 12:37:14: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1&sum;2 (4%/50), eval start                                       
2025-05-07 12:37:17: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1&sum;2 (4%/50), starting new job                                 
2025-05-07 12:37:22: Sobol, best RESULT: 0.23684210526315785, completed/running/unknown 1/1/1&sum;3 (6%/50), started new job                      
2025-05-07 12:37:27: Sobol, best RESULT: 0.23684210526315785, completed/running/unknown 1/1/1&sum;3 (6%/50), new result: 0.35789473684210527      
2025-05-07 12:37:34: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1&sum;2 (4%/50), finishing jobs (_get_next_trials), finished 1 job
2025-05-07 12:37:37: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1&sum;2 (4%/50), getting new HP set                               
2025-05-07 12:37:41: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1&sum;2 (4%/50), eval start                                       
2025-05-07 12:37:49: Sobol, best RESULT: 0.23684210526315785, completed/pending 1/1&sum;2 (4%/50), starting new job                               
2025-05-07 12:37:55: Sobol, best RESULT: 0.23684210526315785, completed/running/unknown 1/1/1&sum;3 (6%/50), started new job                      
2025-05-07 12:37:59: Sobol, best RESULT: 0.23684210526315785, completed/running/pending 1/1/1&sum;3 (6%/50), new result: 0.2789473684210526       
2025-05-07 12:38:07: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1&sum;2 (4%/50), finishing jobs (_get_next_trials), finished 1 job
2025-05-07 12:38:10: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1&sum;2 (4%/50), getting new HP set                               
2025-05-07 12:38:13: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1&sum;2 (4%/50), eval start                                       
2025-05-07 12:38:16: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1&sum;2 (4%/50), starting new job                                 
2025-05-07 12:38:20: Sobol, best RESULT: 0.23684210526315785, completed/pending/unknown 1/1/1&sum;3 (6%/50), started new job                      
2025-05-07 12:38:24: Sobol, best RESULT: 0.23684210526315785, completed/pending 1/2&sum;3 (6%/50), new result: 0.34736842105263155                
2025-05-07 12:38:32: Sobol, best RESULT: 0.23684210526315785, running 2&sum;2 (4%/50), finishing jobs (_get_next_trials), finished 1 job          
2025-05-07 12:38:35: Sobol, best RESULT: 0.23684210526315785, running 2&sum;2 (4%/50), getting new HP set                                         
2025-05-07 12:38:39: Sobol, best RESULT: 0.23684210526315785, running 2&sum;2 (4%/50), eval start                                                 
2025-05-07 12:38:42: Sobol, best RESULT: 0.23684210526315785, running 2&sum;2 (4%/50), starting new job                                           
2025-05-07 12:38:47: Sobol, best RESULT: 0.23684210526315785, running/unknown 2/1&sum;3 (6%/50), started new job                                  
2025-05-07 12:38:50: Sobol, best RESULT: 0.23684210526315785, running/pending 2/1&sum;3 (6%/50), new result: 0.3052631578947368                   
2025-05-07 12:38:57: Sobol, best RESULT: 0.23684210526315785, completed/pending 1/1&sum;2 (4%/50), new result: 0.35789473684210527                
2025-05-07 12:39:04: Sobol, best RESULT: 0.23684210526315785, pending 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 2 jobs         
2025-05-07 12:39:08: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), getting new HP set                                         
2025-05-07 12:39:12: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), eval start                                                 
2025-05-07 12:39:15: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), starting new job                                           
2025-05-07 12:39:21: Sobol, best RESULT: 0.23684210526315785, completed/unknown 1/1&sum;2 (4%/50), started new job                                
2025-05-07 12:39:25: Sobol, best RESULT: 0.23684210526315785, completed/pending 1/1&sum;2 (4%/50), new result: 0.33684210526315794                
2025-05-07 12:39:31: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job          
2025-05-07 12:39:35: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), getting new HP set                                         
2025-05-07 12:39:39: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), eval start                                                 
2025-05-07 12:39:42: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), starting new job                                           
2025-05-07 12:39:47: Sobol, best RESULT: 0.23684210526315785, running/unknown 1/1&sum;2 (4%/50), started new job                                  
2025-05-07 12:39:51: Sobol, best RESULT: 0.23684210526315785, completed/unknown 1/1&sum;2 (4%/50), new result: 0.43157894736842106                
2025-05-07 12:39:57: Sobol, best RESULT: 0.23684210526315785, pending 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job          
2025-05-07 12:40:01: Sobol, best RESULT: 0.23684210526315785, pending 1&sum;1 (2%/50), getting new HP set                                         
2025-05-07 12:40:06: Sobol, best RESULT: 0.23684210526315785, pending 1&sum;1 (2%/50), eval start                                                 
2025-05-07 12:40:11: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), starting new job                                           
2025-05-07 12:40:17: Sobol, best RESULT: 0.23684210526315785, running/unknown 1/1&sum;2 (4%/50), started new job                                  
2025-05-07 12:40:23: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1&sum;2 (4%/50), getting new HP set                               
2025-05-07 12:40:27: Sobol, best RESULT: 0.23684210526315785, completed/pending 1/1&sum;2 (4%/50), eval start                                     
2025-05-07 12:40:30: Sobol, best RESULT: 0.23684210526315785, completed/pending 1/1&sum;2 (4%/50), starting new job                               
2025-05-07 12:40:35: Sobol, best RESULT: 0.23684210526315785, completed/running/unknown 1/1/1&sum;3 (6%/50), started new job                      
2025-05-07 12:40:39: Sobol, best RESULT: 0.23684210526315785, completed/running/unknown 1/1/1&sum;3 (6%/50), new result: 0.2947368421052632       
2025-05-07 12:40:47: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1&sum;2 (4%/50), finishing jobs (_get_next_trials), finished 1 job
2025-05-07 12:40:50: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1&sum;2 (4%/50), getting new HP set                               
2025-05-07 12:40:54: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1&sum;2 (4%/50), eval start                                       
2025-05-07 12:40:57: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1&sum;2 (4%/50), starting new job                                 
2025-05-07 12:41:01: Sobol, best RESULT: 0.23684210526315785, completed/pending/unknown 1/1/1&sum;3 (6%/50), started new job                      
2025-05-07 12:41:06: Sobol, best RESULT: 0.23684210526315785, completed/pending/unknown 1/1/1&sum;3 (6%/50), new result: 0.3315789473684211       
2025-05-07 12:41:14: Sobol, best RESULT: 0.23684210526315785, running 2&sum;2 (4%/50), finishing jobs (_get_next_trials), finished 1 job          
2025-05-07 12:41:18: Sobol, best RESULT: 0.23684210526315785, running 2&sum;2 (4%/50), getting new HP set                                         
2025-05-07 12:41:22: Sobol, best RESULT: 0.23684210526315785, running 2&sum;2 (4%/50), eval start                                                 
2025-05-07 12:41:25: Sobol, best RESULT: 0.23684210526315785, running 2&sum;2 (4%/50), starting new job                                           
2025-05-07 12:41:30: Sobol, best RESULT: 0.23684210526315785, running/completed/unknown 1/1/1&sum;3 (6%/50), started new job                      
2025-05-07 12:41:34: Sobol, best RESULT: 0.23684210526315785, completed/pending 2/1&sum;3 (6%/50), new result: 0.24736842105263157                
2025-05-07 12:41:43: Sobol, best RESULT: 0.23684210526315785, completed/running 1/1&sum;2 (4%/50), new result: 0.41052631578947374                
2025-05-07 12:41:50: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 2 jobs         
2025-05-07 12:41:53: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), getting new HP set                                         
2025-05-07 12:41:57: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), eval start                                                 
2025-05-07 12:42:00: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), starting new job                                           
2025-05-07 12:42:05: Sobol, best RESULT: 0.23684210526315785, running/unknown 1/1&sum;2 (4%/50), started new job                                  
2025-05-07 12:42:10: Sobol, best RESULT: 0.23684210526315785, completed/unknown 1/1&sum;2 (4%/50), new result: 0.3631578947368421                 
2025-05-07 12:42:19: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job          
2025-05-07 12:42:23: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), getting new HP set                                         
2025-05-07 12:42:27: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), eval start                                                 
2025-05-07 12:42:30: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), starting new job                                           
2025-05-07 12:42:35: Sobol, best RESULT: 0.23684210526315785, completed/unknown 1/1&sum;2 (4%/50), started new job                                
2025-05-07 12:42:39: Sobol, best RESULT: 0.23684210526315785, completed/pending 1/1&sum;2 (4%/50), new result: 0.3315789473684211                 
2025-05-07 12:42:47: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job          
2025-05-07 12:42:50: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), getting new HP set                                         
2025-05-07 12:42:54: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), eval start                                                 
2025-05-07 12:42:58: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), starting new job                                           
2025-05-07 12:43:02: Sobol, best RESULT: 0.23684210526315785, completed/unknown 1/1&sum;2 (4%/50), started new job                                
2025-05-07 12:43:07: Sobol, best RESULT: 0.23684210526315785, completed/pending 1/1&sum;2 (4%/50), new result: 0.3421052631578947                 
2025-05-07 12:43:14: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job          
2025-05-07 12:43:18: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), getting new HP set                                         
2025-05-07 12:43:23: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), eval start                                                 
2025-05-07 12:43:28: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), starting new job                                           
2025-05-07 12:43:35: Sobol, best RESULT: 0.23684210526315785, running/unknown 1/1&sum;2 (4%/50), started new job                                  
2025-05-07 12:43:40: Sobol, best RESULT: 0.23684210526315785, completed/pending 1/1&sum;2 (4%/50), new result: 0.3157894736842105                 
2025-05-07 12:44:00: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job          
2025-05-07 12:44:10: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), getting new HP set                                         
2025-05-07 12:44:21: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), eval start                                                 
2025-05-07 12:44:29: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), starting new job                                           
2025-05-07 12:44:40: Sobol, best RESULT: 0.23684210526315785, running/unknown 1/1&sum;2 (4%/50), started new job                                  
2025-05-07 12:44:59: Sobol, best RESULT: 0.23684210526315785, running 2&sum;2 (4%/50), getting new HP set                                         
2025-05-07 12:45:07: Sobol, best RESULT: 0.23684210526315785, completed/running 1/1&sum;2 (4%/50), eval start                                     
2025-05-07 12:45:15: Sobol, best RESULT: 0.23684210526315785, completed/running 1/1&sum;2 (4%/50), starting new job                               
2025-05-07 12:45:24: Sobol, best RESULT: 0.23684210526315785, completed/running/unknown 1/1/1&sum;3 (6%/50), started new job                      
2025-05-07 12:45:35: Sobol, best RESULT: 0.23684210526315785, completed/running/pending 1/1/1&sum;3 (6%/50), new result: 0.30000000000000004      
2025-05-07 12:45:50: Sobol, best RESULT: 0.23684210526315785, completed/pending 1/1&sum;2 (4%/50), new result: 0.3631578947368421                 
2025-05-07 12:46:04: Sobol, best RESULT: 0.23684210526315785, pending 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 2 jobs         
2025-05-07 12:46:12: Sobol, best RESULT: 0.23684210526315785, pending 1&sum;1 (2%/50), getting new HP set                                         
2025-05-07 12:46:21: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), eval start                                                 
2025-05-07 12:46:28: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), starting new job                                           
2025-05-07 12:46:39: Sobol, best RESULT: 0.23684210526315785, running/unknown 1/1&sum;2 (4%/50), started new job                                  
2025-05-07 12:46:52: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1&sum;2 (4%/50), getting new HP set                               
2025-05-07 12:47:00: Sobol, best RESULT: 0.23684210526315785, completed/running 1/1&sum;2 (4%/50), eval start                                     
2025-05-07 12:47:06: Sobol, best RESULT: 0.23684210526315785, completed/running 1/1&sum;2 (4%/50), starting new job                               
2025-05-07 12:47:13: Sobol, best RESULT: 0.23684210526315785, completed/running/unknown 1/1/1&sum;3 (6%/50), started new job                      
2025-05-07 12:47:20: Sobol, best RESULT: 0.23684210526315785, completed/running/pending 1/1/1&sum;3 (6%/50), new result: 0.2789473684210526       
2025-05-07 12:47:32: Sobol, best RESULT: 0.23684210526315785, running 2&sum;2 (4%/50), finishing jobs (_get_next_trials), finished 1 job          
2025-05-07 12:47:41: Sobol, best RESULT: 0.23684210526315785, running 2&sum;2 (4%/50), getting new HP set                                         
2025-05-07 12:47:47: Sobol, best RESULT: 0.23684210526315785, running 2&sum;2 (4%/50), eval start                                                 
2025-05-07 12:47:54: Sobol, best RESULT: 0.23684210526315785, completed/running 1/1&sum;2 (4%/50), starting new job                               
2025-05-07 12:48:09: Sobol, best RESULT: 0.23684210526315785, completed/running/unknown 1/1/1&sum;3 (6%/50), started new job                      
2025-05-07 12:48:24: Sobol, best RESULT: 0.23684210526315785, completed/running/pending 1/1/1&sum;3 (6%/50), new result: 0.4052631578947369       
2025-05-07 12:48:57: Sobol, best RESULT: 0.23684210526315785, running 2&sum;2 (4%/50), finishing jobs (_get_next_trials), finished 1 job          
2025-05-07 12:49:09: Sobol, best RESULT: 0.23684210526315785, running 2&sum;2 (4%/50), getting new HP set                                         
2025-05-07 12:49:15: Sobol, best RESULT: 0.23684210526315785, running 2&sum;2 (4%/50), eval start                                                 
2025-05-07 12:49:22: Sobol, best RESULT: 0.23684210526315785, running 2&sum;2 (4%/50), starting new job                                           
2025-05-07 12:49:45: Sobol, best RESULT: 0.23684210526315785, completed/running/unknown 1/1/1&sum;3 (6%/50), started new job                      
2025-05-07 12:50:06: Sobol, best RESULT: 0.23684210526315785, completed/running/pending 1/1/1&sum;3 (6%/50), new result: 0.31052631578947365      
2025-05-07 12:50:44: Sobol, best RESULT: 0.23684210526315785, running 2&sum;2 (4%/50), finishing jobs (_get_next_trials), finished 1 job          
2025-05-07 12:50:52: Sobol, best RESULT: 0.23684210526315785, running 2&sum;2 (4%/50), getting new HP set                                         
2025-05-07 12:50:58: Sobol, best RESULT: 0.23684210526315785, running 2&sum;2 (4%/50), eval start                                                 
2025-05-07 12:51:04: Sobol, best RESULT: 0.23684210526315785, running 2&sum;2 (4%/50), starting new job                                           
2025-05-07 12:51:12: Sobol, best RESULT: 0.23684210526315785, completed/running/unknown 1/1/1&sum;3 (6%/50), started new job                      
2025-05-07 12:51:18: Sobol, best RESULT: 0.23684210526315785, completed/pending 2/1&sum;3 (6%/50), new result: 0.3421052631578947                 
2025-05-07 12:51:32: Sobol, best RESULT: 0.23684210526315785, completed/running 1/1&sum;2 (4%/50), new result: 0.3526315789473684                 
2025-05-07 12:51:46: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 2 jobs         
2025-05-07 12:51:51: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), getting new HP set                                         
2025-05-07 12:51:58: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), eval start                                                 
2025-05-07 12:52:04: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), starting new job                                           
2025-05-07 12:52:11: Sobol, best RESULT: 0.23684210526315785, completed/unknown 1/1&sum;2 (4%/50), started new job                                
2025-05-07 12:52:18: Sobol, best RESULT: 0.23684210526315785, completed/pending 1/1&sum;2 (4%/50), new result: 0.4631578947368421                 
2025-05-07 12:52:32: Sobol, best RESULT: 0.23684210526315785, pending 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job          
2025-05-07 12:52:38: Sobol, best RESULT: 0.23684210526315785, pending 1&sum;1 (2%/50), getting new HP set                                         
2025-05-07 12:52:45: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), eval start                                                 
2025-05-07 12:52:51: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), starting new job                                           
2025-05-07 12:52:58: Sobol, best RESULT: 0.23684210526315785, running/unknown 1/1&sum;2 (4%/50), started new job                                  
2025-05-07 12:53:11: Sobol, best RESULT: 0.23684210526315785, running 2&sum;2 (4%/50), getting new HP set                                         
2025-05-07 12:53:17: Sobol, best RESULT: 0.23684210526315785, completed/running 1/1&sum;2 (4%/50), eval start                                     
2025-05-07 12:53:23: Sobol, best RESULT: 0.23684210526315785, completed/running 1/1&sum;2 (4%/50), starting new job                               
2025-05-07 12:53:31: Sobol, best RESULT: 0.23684210526315785, completed/running/unknown 1/1/1&sum;3 (6%/50), started new job                      
2025-05-07 12:53:38: Sobol, best RESULT: 0.23684210526315785, completed/running 2/1&sum;3 (6%/50), new result: 0.2684210526315789                 
2025-05-07 12:53:52: Sobol, best RESULT: 0.23684210526315785, completed/running 1/1&sum;2 (4%/50), new result: 0.3526315789473684                 
2025-05-07 12:54:05: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 2 jobs         
2025-05-07 12:54:11: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), getting new HP set                                         
2025-05-07 12:54:18: Sobol, best RESULT: 0.23684210526315785, completed 1&sum;1 (2%/50), eval start                                               
2025-05-07 12:54:24: Sobol, best RESULT: 0.23684210526315785, completed 1&sum;1 (2%/50), starting new job                                         
2025-05-07 12:54:33: Sobol, best RESULT: 0.23684210526315785, completed/unknown 1/1&sum;2 (4%/50), started new job                                
2025-05-07 12:54:40: Sobol, best RESULT: 0.23684210526315785, completed/running 1/1&sum;2 (4%/50), new result: 0.32105263157894737                
2025-05-07 12:54:52: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job          
2025-05-07 12:54:58: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), getting new HP set                                         
2025-05-07 12:55:04: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), eval start                                                 
2025-05-07 12:55:11: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), starting new job                                           
2025-05-07 12:55:18: Sobol, best RESULT: 0.23684210526315785, running/unknown 1/1&sum;2 (4%/50), started new job                                  
2025-05-07 12:55:31: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1&sum;2 (4%/50), getting new HP set                               
2025-05-07 12:55:37: Sobol, best RESULT: 0.23684210526315785, completed/pending 1/1&sum;2 (4%/50), eval start                                     
2025-05-07 12:55:44: Sobol, best RESULT: 0.23684210526315785, completed/pending 1/1&sum;2 (4%/50), starting new job                               
2025-05-07 12:55:51: Sobol, best RESULT: 0.23684210526315785, completed/running/unknown 1/1/1&sum;3 (6%/50), started new job                      
2025-05-07 12:55:58: Sobol, best RESULT: 0.23684210526315785, completed/running/pending 1/1/1&sum;3 (6%/50), new result: 0.4789473684210527       
2025-05-07 12:56:11: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1&sum;2 (4%/50), finishing jobs (_get_next_trials), finished 1 job
2025-05-07 12:56:18: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1&sum;2 (4%/50), getting new HP set                               
2025-05-07 12:56:25: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1&sum;2 (4%/50), eval start                                       
2025-05-07 12:56:31: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1&sum;2 (4%/50), starting new job                                 
2025-05-07 12:56:39: Sobol, best RESULT: 0.23684210526315785, completed/running/unknown 1/1/1&sum;3 (6%/50), started new job                      
2025-05-07 12:56:45: Sobol, best RESULT: 0.23684210526315785, completed/running/pending 1/1/1&sum;3 (6%/50), new result: 0.3263157894736842       
2025-05-07 12:57:31: Sobol, best RESULT: 0.23684210526315785, completed 2&sum;2 (4%/50), new result: 0.26315789473684215                          
2025-05-07 12:57:41: Sobol, best RESULT: 0.23684210526315785, completed 1&sum;1 (2%/50), new result: 0.28421052631578947                          
2025-05-07 12:57:51: Sobol, best RESULT: 0.23684210526315785, finishing jobs (_get_next_trials), finished 3 jobs                              
2025-05-07 12:57:55: Sobol, best RESULT: 0.23684210526315785, getting new HP set                                                              
2025-05-07 12:58:00: Sobol, best RESULT: 0.23684210526315785, eval start                                                                      
2025-05-07 12:58:04: Sobol, best RESULT: 0.23684210526315785, starting new job                                                                
2025-05-07 12:58:10: Sobol, best RESULT: 0.23684210526315785, unknown 1&sum;1 (2%/50), started new job                                            
2025-05-07 12:58:20: Sobol, best RESULT: 0.23684210526315785, pending 1&sum;1 (2%/50), getting new HP set                                         
2025-05-07 12:58:25: Sobol, best RESULT: 0.23684210526315785, pending 1&sum;1 (2%/50), eval start                                                 
2025-05-07 12:58:30: Sobol, best RESULT: 0.23684210526315785, pending 1&sum;1 (2%/50), starting new job                                           
2025-05-07 12:58:36: Sobol, best RESULT: 0.23684210526315785, running/unknown 1/1&sum;2 (4%/50), started new job                                  
2025-05-07 12:58:46: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1&sum;2 (4%/50), getting new HP set                               
2025-05-07 12:58:50: Sobol, best RESULT: 0.23684210526315785, completed/pending 1/1&sum;2 (4%/50), eval start                                     
2025-05-07 12:58:54: Sobol, best RESULT: 0.23684210526315785, completed/pending 1/1&sum;2 (4%/50), starting new job                               
2025-05-07 12:59:00: Sobol, best RESULT: 0.23684210526315785, completed/running/unknown 1/1/1&sum;3 (6%/50), started new job                      
2025-05-07 12:59:05: Sobol, best RESULT: 0.23684210526315785, completed/running/pending 1/1/1&sum;3 (6%/50), new result: 0.3526315789473684       
2025-05-07 12:59:14: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1&sum;2 (4%/50), finishing jobs (_get_next_trials), finished 1 job
2025-05-07 12:59:18: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1&sum;2 (4%/50), getting new HP set                               
2025-05-07 12:59:22: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1&sum;2 (4%/50), eval start                                       
2025-05-07 12:59:26: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1&sum;2 (4%/50), starting new job                                 
2025-05-07 12:59:31: Sobol, best RESULT: 0.23684210526315785, completed/running/unknown 1/1/1&sum;3 (6%/50), started new job                      
2025-05-07 12:59:36: Sobol, best RESULT: 0.23684210526315785, completed/running/pending 1/1/1&sum;3 (6%/50), new result: 0.3631578947368421       
2025-05-07 12:59:46: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1&sum;2 (4%/50), finishing jobs (_get_next_trials), finished 1 job
2025-05-07 12:59:50: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1&sum;2 (4%/50), getting new HP set                               
2025-05-07 12:59:54: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1&sum;2 (4%/50), eval start                                       
2025-05-07 12:59:58: Sobol, best RESULT: 0.23684210526315785, running/pending 1/1&sum;2 (4%/50), starting new job                                 
2025-05-07 13:00:03: Sobol, best RESULT: 0.23684210526315785, completed/pending/unknown 1/1/1&sum;3 (6%/50), started new job                      
2025-05-07 13:00:08: Sobol, best RESULT: 0.23684210526315785, completed/running 1/2&sum;3 (6%/50), new result: 0.41052631578947374                
2025-05-07 13:00:18: Sobol, best RESULT: 0.23684210526315785, running 2&sum;2 (4%/50), finishing jobs (_get_next_trials), finished 1 job          
2025-05-07 13:00:21: Sobol, best RESULT: 0.23684210526315785, running 2&sum;2 (4%/50), getting new HP set                                         
2025-05-07 13:00:26: Sobol, best RESULT: 0.23684210526315785, running 2&sum;2 (4%/50), eval start                                                 
2025-05-07 13:00:30: Sobol, best RESULT: 0.23684210526315785, running 2&sum;2 (4%/50), starting new job                                           
2025-05-07 13:00:35: Sobol, best RESULT: 0.23684210526315785, completed/unknown 2/1&sum;3 (6%/50), started new job                                
2025-05-07 13:00:40: Sobol, best RESULT: 0.23684210526315785, completed/running 2/1&sum;3 (6%/50), new result: 0.3631578947368421                 
2025-05-07 13:00:49: Sobol, best RESULT: 0.23684210526315785, completed/running 1/1&sum;2 (4%/50), new result: 0.368421052631579                  
2025-05-07 13:00:58: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), finishing jobs, finished 2 jobs                            
2025-05-07 13:01:02: Sobol, best RESULT: 0.23684210526315785, running 1&sum;1 (2%/50), new result: 0.22631578947368425                            
2025-05-07 13:01:10: Sobol, best RESULT: 0.22631578947368425, finishing previous jobs (1), finished 1 job                                     
2025-05-07 13:01:15: Sobol, best RESULT: 0.22631578947368425, getting new HP set                                                              
2025-05-07 13:01:22: BoTorchModel, best RESULT: 0.22631578947368425, eval start                                                               
2025-05-07 13:01:26: BoTorchModel, best RESULT: 0.22631578947368425, starting new job                                                         
2025-05-07 13:01:31: BoTorchModel, best RESULT: 0.22631578947368425, unknown 1&sum;1 (2%/50), started new job                                     
2025-05-07 13:01:41: BoTorchModel, best RESULT: 0.22631578947368425, pending 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 13:01:47: BoTorchModel, best RESULT: 0.22631578947368425, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 13:01:52: BoTorchModel, best RESULT: 0.22631578947368425, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 13:01:58: BoTorchModel, best RESULT: 0.22631578947368425, running/unknown 1/1&sum;2 (4%/50), started new job                           
2025-05-07 13:02:03: BoTorchModel, best RESULT: 0.22631578947368425, completed/pending 1/1&sum;2 (4%/50), new result: 0.31052631578947365         
2025-05-07 13:02:12: BoTorchModel, best RESULT: 0.22631578947368425, pending 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:02:16: BoTorchModel, best RESULT: 0.22631578947368425, pending 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 13:02:35: BoTorchModel, best RESULT: 0.22631578947368425, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 13:02:40: BoTorchModel, best RESULT: 0.22631578947368425, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 13:02:46: BoTorchModel, best RESULT: 0.22631578947368425, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 13:02:52: BoTorchModel, best RESULT: 0.22631578947368425, completed/running 1/1&sum;2 (4%/50), new result: 0.21052631578947367         
2025-05-07 13:03:03: BoTorchModel, best RESULT: 0.21052631578947367, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:03:08: BoTorchModel, best RESULT: 0.21052631578947367, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 13:03:17: BoTorchModel, best RESULT: 0.21052631578947367, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 13:03:23: BoTorchModel, best RESULT: 0.21052631578947367, completed 1&sum;1 (2%/50), starting new job                                  
2025-05-07 13:03:30: BoTorchModel, best RESULT: 0.21052631578947367, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 13:03:38: BoTorchModel, best RESULT: 0.21052631578947367, completed/pending 1/1&sum;2 (4%/50), new result: 0.27368421052631575         
2025-05-07 13:03:51: BoTorchModel, best RESULT: 0.21052631578947367, pending 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:03:57: BoTorchModel, best RESULT: 0.21052631578947367, pending 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 13:04:05: BoTorchModel, best RESULT: 0.21052631578947367, pending 1&sum;1 (2%/50), eval start                                          
2025-05-07 13:04:10: BoTorchModel, best RESULT: 0.21052631578947367, pending 1&sum;1 (2%/50), starting new job                                    
2025-05-07 13:04:17: BoTorchModel, best RESULT: 0.21052631578947367, running/unknown 1/1&sum;2 (4%/50), started new job                           
2025-05-07 13:04:32: BoTorchModel, best RESULT: 0.21052631578947367, completed/running 1/1&sum;2 (4%/50), getting new HP set                      
2025-05-07 13:04:43: BoTorchModel, best RESULT: 0.21052631578947367, completed/running 1/1&sum;2 (4%/50), eval start                              
2025-05-07 13:04:52: BoTorchModel, best RESULT: 0.21052631578947367, completed/running 1/1&sum;2 (4%/50), starting new job                        
2025-05-07 13:05:02: BoTorchModel, best RESULT: 0.21052631578947367, completed/running/unknown 1/1/1&sum;3 (6%/50), started new job               
2025-05-07 13:05:10: BoTorchModel, best RESULT: 0.21052631578947367, completed/pending 2/1&sum;3 (6%/50), new result: 0.3631578947368421          
2025-05-07 13:05:25: BoTorchModel, best RESULT: 0.21052631578947367, completed/pending 1/1&sum;2 (4%/50), new result: 0.3631578947368421          
2025-05-07 13:05:40: BoTorchModel, best RESULT: 0.21052631578947367, pending 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 2 jobs  
2025-05-07 13:05:47: BoTorchModel, best RESULT: 0.21052631578947367, pending 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 13:05:58: BoTorchModel, best RESULT: 0.21052631578947367, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 13:06:08: BoTorchModel, best RESULT: 0.21052631578947367, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 13:06:16: BoTorchModel, best RESULT: 0.21052631578947367, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 13:06:24: BoTorchModel, best RESULT: 0.21052631578947367, completed/pending 1/1&sum;2 (4%/50), new result: 0.26315789473684215         
2025-05-07 13:06:41: BoTorchModel, best RESULT: 0.21052631578947367, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:06:49: BoTorchModel, best RESULT: 0.21052631578947367, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 13:07:03: BoTorchModel, best RESULT: 0.21052631578947367, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 13:07:12: BoTorchModel, best RESULT: 0.21052631578947367, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 13:07:21: BoTorchModel, best RESULT: 0.21052631578947367, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 13:07:28: BoTorchModel, best RESULT: 0.21052631578947367, completed/pending 1/1&sum;2 (4%/50), new result: 0.3631578947368421          
2025-05-07 13:07:42: BoTorchModel, best RESULT: 0.21052631578947367, pending 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:07:48: BoTorchModel, best RESULT: 0.21052631578947367, pending 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 13:08:00: BoTorchModel, best RESULT: 0.21052631578947367, pending 1&sum;1 (2%/50), eval start                                          
2025-05-07 13:08:07: BoTorchModel, best RESULT: 0.21052631578947367, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 13:08:16: BoTorchModel, best RESULT: 0.21052631578947367, running/unknown 1/1&sum;2 (4%/50), started new job                           
2025-05-07 13:08:34: BoTorchModel, best RESULT: 0.21052631578947367, completed/pending 1/1&sum;2 (4%/50), new result: 0.2421052631578947          
2025-05-07 13:08:50: BoTorchModel, best RESULT: 0.21052631578947367, pending 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:09:00: BoTorchModel, best RESULT: 0.21052631578947367, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 13:09:15: BoTorchModel, best RESULT: 0.21052631578947367, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 13:09:24: BoTorchModel, best RESULT: 0.21052631578947367, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 13:09:34: BoTorchModel, best RESULT: 0.21052631578947367, running/unknown 1/1&sum;2 (4%/50), started new job                           
2025-05-07 13:09:43: BoTorchModel, best RESULT: 0.21052631578947367, completed/pending 1/1&sum;2 (4%/50), new result: 0.2789473684210526          
2025-05-07 13:10:02: BoTorchModel, best RESULT: 0.21052631578947367, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:10:12: BoTorchModel, best RESULT: 0.21052631578947367, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 13:10:30: BoTorchModel, best RESULT: 0.21052631578947367, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 13:10:39: BoTorchModel, best RESULT: 0.21052631578947367, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 13:10:49: BoTorchModel, best RESULT: 0.21052631578947367, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 13:10:59: BoTorchModel, best RESULT: 0.21052631578947367, completed/running 1/1&sum;2 (4%/50), new result: 0.28421052631578947         
2025-05-07 13:11:15: BoTorchModel, best RESULT: 0.21052631578947367, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:11:22: BoTorchModel, best RESULT: 0.21052631578947367, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 13:11:33: BoTorchModel, best RESULT: 0.21052631578947367, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 13:11:43: BoTorchModel, best RESULT: 0.21052631578947367, completed 1&sum;1 (2%/50), starting new job                                  
2025-05-07 13:11:53: BoTorchModel, best RESULT: 0.21052631578947367, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 13:12:01: BoTorchModel, best RESULT: 0.21052631578947367, completed/pending 1/1&sum;2 (4%/50), new result: 0.26315789473684215         
2025-05-07 13:12:18: BoTorchModel, best RESULT: 0.21052631578947367, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:12:34: BoTorchModel, best RESULT: 0.21052631578947367, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 13:12:45: BoTorchModel, best RESULT: 0.21052631578947367, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 13:12:52: BoTorchModel, best RESULT: 0.21052631578947367, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 13:13:02: BoTorchModel, best RESULT: 0.21052631578947367, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 13:13:11: BoTorchModel, best RESULT: 0.21052631578947367, completed/running 1/1&sum;2 (4%/50), new result: 0.20526315789473681         
2025-05-07 13:13:27: BoTorchModel, best RESULT: 0.20526315789473681, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:13:33: BoTorchModel, best RESULT: 0.20526315789473681, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 13:13:47: BoTorchModel, best RESULT: 0.20526315789473681, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 13:13:54: BoTorchModel, best RESULT: 0.20526315789473681, completed 1&sum;1 (2%/50), starting new job                                  
2025-05-07 13:14:03: BoTorchModel, best RESULT: 0.20526315789473681, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 13:14:10: BoTorchModel, best RESULT: 0.20526315789473681, completed/pending 1/1&sum;2 (4%/50), new result: 0.3631578947368421          
2025-05-07 13:14:27: BoTorchModel, best RESULT: 0.20526315789473681, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:14:35: BoTorchModel, best RESULT: 0.20526315789473681, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 13:14:48: BoTorchModel, best RESULT: 0.20526315789473681, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 13:14:55: BoTorchModel, best RESULT: 0.20526315789473681, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 13:15:04: BoTorchModel, best RESULT: 0.20526315789473681, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 13:15:13: BoTorchModel, best RESULT: 0.20526315789473681, completed/pending 1/1&sum;2 (4%/50), new result: 0.3526315789473684          
2025-05-07 13:15:26: BoTorchModel, best RESULT: 0.20526315789473681, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:15:33: BoTorchModel, best RESULT: 0.20526315789473681, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 13:15:42: BoTorchModel, best RESULT: 0.20526315789473681, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 13:15:50: BoTorchModel, best RESULT: 0.20526315789473681, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 13:15:59: BoTorchModel, best RESULT: 0.20526315789473681, running/unknown 1/1&sum;2 (4%/50), started new job                           
2025-05-07 13:16:13: BoTorchModel, best RESULT: 0.20526315789473681, running/pending 1/1&sum;2 (4%/50), getting new HP set                        
2025-05-07 13:16:23: BoTorchModel, best RESULT: 0.20526315789473681, completed/pending 1/1&sum;2 (4%/50), eval start                              
2025-05-07 13:16:30: BoTorchModel, best RESULT: 0.20526315789473681, completed/pending 1/1&sum;2 (4%/50), starting new job                        
2025-05-07 13:16:39: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 1/1/1&sum;3 (6%/50), started new job               
2025-05-07 13:16:47: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 1/1/1&sum;3 (6%/50), new result: 0.2315789473684211
2025-05-07 13:17:01: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 1/1&sum;2 (4%/50), new result: 0.2578947368421053          
2025-05-07 13:17:18: BoTorchModel, best RESULT: 0.20526315789473681, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 2 jobs  
2025-05-07 13:17:25: BoTorchModel, best RESULT: 0.20526315789473681, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 13:17:37: BoTorchModel, best RESULT: 0.20526315789473681, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 13:17:47: BoTorchModel, best RESULT: 0.20526315789473681, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 13:17:56: BoTorchModel, best RESULT: 0.20526315789473681, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 13:18:08: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 1/1&sum;2 (4%/50), new result: 0.19999999999999996         
2025-05-07 13:18:30: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:18:38: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 13:18:53: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 13:19:02: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 13:19:15: BoTorchModel, best RESULT: 0.19999999999999996, running/unknown 1/1&sum;2 (4%/50), started new job                           
2025-05-07 13:19:26: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.28421052631578947         
2025-05-07 13:19:44: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:19:51: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 13:20:02: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 13:20:10: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 13:20:19: BoTorchModel, best RESULT: 0.19999999999999996, running/unknown 1/1&sum;2 (4%/50), started new job                           
2025-05-07 13:20:35: BoTorchModel, best RESULT: 0.19999999999999996, running/pending 1/1&sum;2 (4%/50), getting new HP set                        
2025-05-07 13:20:46: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), eval start                              
2025-05-07 13:20:55: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), starting new job                        
2025-05-07 13:21:02: BoTorchModel, best RESULT: 0.19999999999999996, completed/running/unknown 1/1/1&sum;3 (6%/50), started new job               
2025-05-07 13:21:10: BoTorchModel, best RESULT: 0.19999999999999996, completed/running/pending 1/1/1&sum;3 (6%/50), new result: 0.3631578947368421
2025-05-07 13:21:28: BoTorchModel, best RESULT: 0.19999999999999996, running 2&sum;2 (4%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:21:37: BoTorchModel, best RESULT: 0.19999999999999996, running 2&sum;2 (4%/50), getting new HP set                                  
2025-05-07 13:21:51: BoTorchModel, best RESULT: 0.19999999999999996, running 2&sum;2 (4%/50), eval start                                          
2025-05-07 13:22:00: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), starting new job                        
2025-05-07 13:22:08: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 2/1&sum;3 (6%/50), started new job                         
2025-05-07 13:22:15: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 2/1&sum;3 (6%/50), new result: 0.3631578947368421          
2025-05-07 13:22:30: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.32105263157894737         
2025-05-07 13:22:43: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 2 jobs  
2025-05-07 13:22:49: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 13:22:59: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), eval start                                        
2025-05-07 13:23:05: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                  
2025-05-07 13:23:13: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 13:23:20: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.33684210526315794         
2025-05-07 13:23:34: BoTorchModel, best RESULT: 0.19999999999999996, pending 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:23:41: BoTorchModel, best RESULT: 0.19999999999999996, pending 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 13:23:50: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 13:23:57: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 13:24:04: BoTorchModel, best RESULT: 0.19999999999999996, running/unknown 1/1&sum;2 (4%/50), started new job                           
2025-05-07 13:24:12: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.28421052631578947         
2025-05-07 13:24:26: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), new result: 0.2789473684210526                    
2025-05-07 13:24:41: BoTorchModel, best RESULT: 0.19999999999999996, finishing jobs (_get_next_trials), finished 2 jobs                       
2025-05-07 13:24:47: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                       
2025-05-07 13:24:58: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                               
2025-05-07 13:25:03: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                         
2025-05-07 13:25:13: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1&sum;1 (2%/50), started new job                                     
2025-05-07 13:25:29: BoTorchModel, best RESULT: 0.19999999999999996, pending 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 13:25:38: BoTorchModel, best RESULT: 0.19999999999999996, pending 1&sum;1 (2%/50), eval start                                          
2025-05-07 13:25:44: BoTorchModel, best RESULT: 0.19999999999999996, pending 1&sum;1 (2%/50), starting new job                                    
2025-05-07 13:25:54: BoTorchModel, best RESULT: 0.19999999999999996, running/unknown 1/1&sum;2 (4%/50), started new job                           
2025-05-07 13:26:12: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), getting new HP set                      
2025-05-07 13:26:24: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), eval start                              
2025-05-07 13:26:43: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), starting new job                        
2025-05-07 13:26:56: BoTorchModel, best RESULT: 0.19999999999999996, completed/running/unknown 1/1/1&sum;3 (6%/50), started new job               
2025-05-07 13:27:07: BoTorchModel, best RESULT: 0.19999999999999996, completed/running/pending 1/1/1&sum;3 (6%/50), new result: 0.3421052631578947
2025-05-07 13:27:28: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.3526315789473684          
2025-05-07 13:27:47: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 2 jobs  
2025-05-07 13:27:56: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 13:28:10: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), eval start                                        
2025-05-07 13:28:21: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                  
2025-05-07 13:28:35: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 13:28:48: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.2315789473684211          
2025-05-07 13:29:13: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:29:23: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 13:29:34: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 13:29:45: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 13:29:56: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 13:30:06: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.3631578947368421          
2025-05-07 13:30:26: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:30:34: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 13:30:48: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 13:30:58: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 13:31:10: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 13:31:23: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.20526315789473681         
2025-05-07 13:31:47: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:31:59: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 13:32:15: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), eval start                                        
2025-05-07 13:32:27: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                  
2025-05-07 13:32:43: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 13:32:55: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.2947368421052632          
2025-05-07 13:33:16: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:33:23: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 13:33:37: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 13:33:47: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 13:33:58: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 13:34:08: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.27368421052631575         
2025-05-07 13:34:34: BoTorchModel, best RESULT: 0.19999999999999996, pending 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:34:45: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 13:34:59: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 13:35:09: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 13:35:20: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 13:35:29: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.31052631578947365         
2025-05-07 13:35:51: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:36:04: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 13:36:19: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 13:36:32: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 13:36:45: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 13:36:58: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.2421052631578947          
2025-05-07 13:37:24: BoTorchModel, best RESULT: 0.19999999999999996, pending 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:37:40: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 13:37:56: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 13:38:06: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 13:38:21: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 13:38:34: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.2684210526315789          
2025-05-07 13:39:01: BoTorchModel, best RESULT: 0.19999999999999996, pending 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:39:13: BoTorchModel, best RESULT: 0.19999999999999996, pending 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 13:39:28: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), eval start                                        
2025-05-07 13:39:45: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                  
2025-05-07 13:40:00: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 13:40:14: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.3157894736842105          
2025-05-07 13:40:38: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:40:49: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 13:41:01: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 13:41:10: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 13:41:20: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 13:41:29: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.32105263157894737         
2025-05-07 13:41:47: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:41:55: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 13:42:07: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 13:42:16: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                  
2025-05-07 13:42:27: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 13:42:37: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.2894736842105263          
2025-05-07 13:42:58: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:43:11: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 13:43:27: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 13:43:40: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 13:43:58: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 13:44:15: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.35789473684210527         
2025-05-07 13:44:38: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:44:52: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 13:45:05: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 13:45:17: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 13:45:30: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 13:45:41: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.3631578947368421          
2025-05-07 13:46:06: BoTorchModel, best RESULT: 0.19999999999999996, pending 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:46:19: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 13:46:33: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 13:46:45: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 13:46:56: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 13:47:06: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.21052631578947367         
2025-05-07 13:47:28: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:47:36: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 13:47:49: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 13:47:57: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 13:48:06: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 13:48:15: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.21578947368421053         
2025-05-07 13:48:31: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:48:40: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 13:48:52: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 13:49:02: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                  
2025-05-07 13:49:12: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 13:49:23: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.2210526315789474          
2025-05-07 13:49:41: BoTorchModel, best RESULT: 0.19999999999999996, pending 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:49:50: BoTorchModel, best RESULT: 0.19999999999999996, pending 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 13:50:03: BoTorchModel, best RESULT: 0.19999999999999996, pending 1&sum;1 (2%/50), eval start                                          
2025-05-07 13:50:12: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 13:50:23: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 13:50:34: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.26315789473684215         
2025-05-07 13:50:57: BoTorchModel, best RESULT: 0.19999999999999996, pending 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:51:09: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 13:51:22: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 13:51:35: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 13:51:50: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 13:51:59: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.2578947368421053          
2025-05-07 13:52:20: BoTorchModel, best RESULT: 0.19999999999999996, pending 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:52:31: BoTorchModel, best RESULT: 0.19999999999999996, pending 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 13:52:47: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 13:53:04: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 13:53:17: BoTorchModel, best RESULT: 0.19999999999999996, running/unknown 1/1&sum;2 (4%/50), started new job                           
2025-05-07 13:53:38: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.24736842105263157         
2025-05-07 13:54:28: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:54:56: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 13:55:35: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 13:56:07: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 13:56:27: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 13:56:47: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.27368421052631575         
2025-05-07 13:57:41: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 13:58:12: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 13:58:37: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 13:58:54: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 13:59:16: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 13:59:45: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.25263157894736843         
2025-05-07 14:00:39: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 14:01:01: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 14:01:41: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 14:02:13: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                  
2025-05-07 14:02:40: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 14:03:06: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.30000000000000004         
2025-05-07 14:04:04: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 14:04:27: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 14:04:47: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 14:05:11: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 14:05:33: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 14:06:10: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.3631578947368421          
2025-05-07 14:07:13: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs, finished 1 job                      
2025-05-07 14:07:55: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), waiting for 1 job                                   
2025-05-07 14:08:37: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), waiting for 1 job                                   
2025-05-07 14:09:34: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), new result: 0.24736842105263157                   
2025-05-07 14:10:26: BoTorchModel, best RESULT: 0.19999999999999996, waiting for 1 job), finished 1 job                                       
2025-05-07 14:10:51: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                       
2025-05-07 14:11:25: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                               
2025-05-07 14:11:49: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                         
2025-05-07 14:12:10: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1&sum;1 (2%/50), started new job                                     
2025-05-07 14:13:07: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 14:13:41: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 14:14:03: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 14:14:28: BoTorchModel, best RESULT: 0.19999999999999996, running/unknown 1/1&sum;2 (4%/50), started new job                           
2025-05-07 14:14:55: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.33684210526315794         
2025-05-07 14:15:45: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 14:16:04: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 14:16:32: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 14:17:01: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 14:17:34: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 14:18:07: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.33684210526315794         
2025-05-07 14:19:21: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 14:20:02: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 14:20:30: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 14:21:06: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 14:21:37: BoTorchModel, best RESULT: 0.19999999999999996, running/unknown 1/1&sum;2 (4%/50), started new job                           
2025-05-07 14:22:34: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), getting new HP set                      
2025-05-07 14:23:11: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), eval start                              
2025-05-07 14:23:38: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), starting new job                        
2025-05-07 14:24:11: BoTorchModel, best RESULT: 0.19999999999999996, completed/running/unknown 1/1/1&sum;3 (6%/50), started new job               
2025-05-07 14:24:38: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 2/1&sum;3 (6%/50), new result: 0.3631578947368421          
2025-05-07 14:25:42: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.2789473684210526          
2025-05-07 14:26:49: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), new result: 0.33684210526315794                   
2025-05-07 14:27:44: BoTorchModel, best RESULT: 0.19999999999999996, finishing jobs (_get_next_trials), finished 3 jobs                       
2025-05-07 14:28:04: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                       
2025-05-07 14:28:46: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                               
2025-05-07 14:29:17: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                         
2025-05-07 14:29:54: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1&sum;1 (2%/50), started new job                                     
2025-05-07 14:30:56: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 14:31:42: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 14:32:15: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 14:32:45: BoTorchModel, best RESULT: 0.19999999999999996, running/unknown 1/1&sum;2 (4%/50), started new job                           
2025-05-07 14:33:16: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.24736842105263157         
2025-05-07 14:34:36: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 14:35:02: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 14:35:45: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 14:36:14: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 14:36:34: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 14:36:54: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.27368421052631575         
2025-05-07 14:37:40: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 14:37:59: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 14:38:24: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 14:38:41: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 14:38:59: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 14:39:16: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.3157894736842105          
2025-05-07 14:39:49: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 14:40:08: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 14:40:28: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 14:40:52: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                  
2025-05-07 14:41:16: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 14:41:35: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.2578947368421053          
2025-05-07 14:42:19: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 14:42:40: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 14:43:05: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 14:43:21: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 14:43:38: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 14:43:54: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.3631578947368421          
2025-05-07 14:44:38: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 14:45:10: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 14:45:32: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 14:45:54: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 14:46:11: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 14:46:28: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.35789473684210527         
2025-05-07 14:46:57: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 14:47:20: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 14:47:41: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 14:47:55: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 14:48:09: BoTorchModel, best RESULT: 0.19999999999999996, running/unknown 1/1&sum;2 (4%/50), started new job                           
2025-05-07 14:49:05: BoTorchModel, best RESULT: 0.19999999999999996, running 2&sum;2 (4%/50), getting new HP set                                  
2025-05-07 14:49:52: BoTorchModel, best RESULT: 0.19999999999999996, running 2&sum;2 (4%/50), eval start                                          
2025-05-07 14:50:25: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), starting new job                        
2025-05-07 14:50:58: BoTorchModel, best RESULT: 0.19999999999999996, completed/running/unknown 1/1/1&sum;3 (6%/50), started new job               
2025-05-07 14:51:31: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 2/1&sum;3 (6%/50), new result: 0.28421052631578947         
2025-05-07 14:53:18: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.26315789473684215         
2025-05-07 14:54:49: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), new result: 0.24736842105263157                   
2025-05-07 14:55:51: BoTorchModel, best RESULT: 0.19999999999999996, finishing jobs (_get_next_trials), finished 3 jobs                       
2025-05-07 14:56:15: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                       
2025-05-07 14:56:37: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                               
2025-05-07 14:56:54: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                         
2025-05-07 14:57:12: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1&sum;1 (2%/50), started new job                                     
2025-05-07 14:57:52: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 14:58:11: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 14:58:31: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 14:58:56: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 14:59:13: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.4052631578947369          
2025-05-07 14:59:50: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 15:00:15: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), getting new HP set                                
2025-05-07 15:00:37: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), eval start                                        
2025-05-07 15:00:55: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                  
2025-05-07 15:01:16: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 15:01:38: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.22631578947368425         
2025-05-07 15:02:14: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 15:02:39: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 15:03:01: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 15:03:23: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                  
2025-05-07 15:03:42: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 15:04:00: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.2421052631578947          
2025-05-07 15:04:35: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 15:04:50: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 15:05:08: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 15:05:27: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 15:05:46: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 15:06:05: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.3315789473684211          
2025-05-07 15:06:43: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 15:07:01: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 15:07:21: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 15:07:41: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 15:08:02: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 15:08:24: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.20526315789473681         
2025-05-07 15:09:03: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 15:09:24: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 15:09:44: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 15:10:06: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                  
2025-05-07 15:10:31: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 15:10:55: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.28421052631578947         
2025-05-07 15:11:43: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), new result: 0.3631578947368421                      
2025-05-07 15:12:21: BoTorchModel, best RESULT: 0.19999999999999996, finishing jobs (_get_next_trials), finished 2 jobs                       
2025-05-07 15:12:40: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                       
2025-05-07 15:13:06: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                               
2025-05-07 15:13:29: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                         
2025-05-07 15:13:50: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1&sum;1 (2%/50), started new job                                     
2025-05-07 15:14:31: BoTorchModel, best RESULT: 0.19999999999999996, pending 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 15:14:51: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 15:15:08: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 15:15:24: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 15:15:42: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.2421052631578947          
2025-05-07 15:16:21: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 15:16:42: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 15:17:08: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 15:17:26: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                  
2025-05-07 15:17:49: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 15:18:18: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.3631578947368421          
2025-05-07 15:18:56: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), new result: 0.2684210526315789                    
2025-05-07 15:19:39: BoTorchModel, best RESULT: 0.19999999999999996, finishing jobs (_get_next_trials), finished 2 jobs                       
2025-05-07 15:19:58: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                       
2025-05-07 15:20:25: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                               
2025-05-07 15:20:47: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                         
2025-05-07 15:21:09: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1&sum;1 (2%/50), started new job                                     
2025-05-07 15:21:49: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 15:22:10: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 15:22:29: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 15:22:48: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 15:23:10: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.3631578947368421          
2025-05-07 15:23:55: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), new result: 0.24736842105263157                   
2025-05-07 15:24:43: BoTorchModel, best RESULT: 0.19999999999999996, finishing jobs (_get_next_trials), finished 2 jobs                       
2025-05-07 15:25:04: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                       
2025-05-07 15:25:26: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                               
2025-05-07 15:25:47: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                         
2025-05-07 15:26:09: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1&sum;1 (2%/50), started new job                                     
2025-05-07 15:26:53: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 15:27:18: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), eval start                                        
2025-05-07 15:27:38: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                  
2025-05-07 15:28:04: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 15:28:25: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.21578947368421053         
2025-05-07 15:29:12: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), new result: 0.32105263157894737                     
2025-05-07 15:29:59: BoTorchModel, best RESULT: 0.19999999999999996, finishing jobs (_get_next_trials), finished 2 jobs                       
2025-05-07 15:30:19: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                       
2025-05-07 15:30:50: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                               
2025-05-07 15:31:23: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                         
2025-05-07 15:31:56: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1&sum;1 (2%/50), started new job                                     
2025-05-07 15:32:59: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 15:33:38: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 15:34:15: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                  
2025-05-07 15:34:44: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 15:35:20: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.26315789473684215         
2025-05-07 15:36:07: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 15:36:23: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 15:36:47: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 15:37:20: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 15:37:49: BoTorchModel, best RESULT: 0.19999999999999996, running/unknown 1/1&sum;2 (4%/50), started new job                           
2025-05-07 15:38:33: BoTorchModel, best RESULT: 0.19999999999999996, running 2&sum;2 (4%/50), getting new HP set                                  
2025-05-07 15:38:57: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), eval start                              
2025-05-07 15:39:18: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), starting new job                        
2025-05-07 15:39:40: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 2/1&sum;3 (6%/50), started new job                         
2025-05-07 15:40:00: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 2/1&sum;3 (6%/50), new result: 0.3315789473684211          
2025-05-07 15:40:52: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.27368421052631575         
2025-05-07 15:41:35: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), new result: 0.3631578947368421                    
2025-05-07 15:42:12: BoTorchModel, best RESULT: 0.19999999999999996, finishing jobs (_get_next_trials), finished 3 jobs                       
2025-05-07 15:42:28: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                       
2025-05-07 15:42:53: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                               
2025-05-07 15:43:07: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                         
2025-05-07 15:43:26: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1&sum;1 (2%/50), started new job                                     
2025-05-07 15:43:59: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 15:44:21: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 15:44:36: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                  
2025-05-07 15:44:58: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 15:45:14: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.3052631578947368          
2025-05-07 15:46:01: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 15:46:17: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 15:46:36: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), eval start                                        
2025-05-07 15:46:54: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                  
2025-05-07 15:47:20: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 15:47:40: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.3631578947368421          
2025-05-07 15:48:24: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 15:48:44: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), getting new HP set                                
2025-05-07 15:49:11: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), eval start                                        
2025-05-07 15:49:29: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                  
2025-05-07 15:49:52: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 15:50:14: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.3052631578947368          
2025-05-07 15:50:52: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 15:51:15: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 15:51:40: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 15:52:02: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                  
2025-05-07 15:52:25: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 15:52:47: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.24736842105263157         
2025-05-07 15:53:33: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 15:53:56: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 15:54:25: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 15:54:47: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                  
2025-05-07 15:55:06: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 15:55:27: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.25263157894736843         
2025-05-07 15:56:11: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 15:56:32: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 15:57:02: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 15:57:30: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                  
2025-05-07 15:58:08: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 15:58:39: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.22631578947368425         
2025-05-07 15:59:34: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 16:01:19: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 16:01:55: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 16:03:17: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 16:03:41: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 16:04:08: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.21578947368421053         
2025-05-07 16:04:38: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), new result: 0.23684210526315785                   
2025-05-07 16:05:21: BoTorchModel, best RESULT: 0.19999999999999996, finishing jobs (_get_next_trials), finished 2 jobs                       
2025-05-07 16:05:41: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                       
2025-05-07 16:06:06: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                               
2025-05-07 16:06:29: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                         
2025-05-07 16:06:59: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1&sum;1 (2%/50), started new job                                     
2025-05-07 16:07:52: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 16:08:28: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 16:08:54: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                  
2025-05-07 16:09:22: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 16:09:49: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.2210526315789474          
2025-05-07 16:10:35: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), new result: 0.21578947368421053                   
2025-05-07 16:12:40: BoTorchModel, best RESULT: 0.19999999999999996, finishing jobs (_get_next_trials), finished 2 jobs                       
2025-05-07 16:13:24: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                       
2025-05-07 16:14:21: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                               
2025-05-07 16:14:51: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                         
2025-05-07 16:15:16: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1&sum;1 (2%/50), started new job                                     
2025-05-07 16:15:50: BoTorchModel, best RESULT: 0.19999999999999996, pending 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 16:16:12: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 16:16:30: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 16:16:52: BoTorchModel, best RESULT: 0.19999999999999996, running/unknown 1/1&sum;2 (4%/50), started new job                           
2025-05-07 16:17:30: BoTorchModel, best RESULT: 0.19999999999999996, running 2&sum;2 (4%/50), getting new HP set                                  
2025-05-07 16:17:53: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), eval start                              
2025-05-07 16:18:12: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), starting new job                        
2025-05-07 16:18:32: BoTorchModel, best RESULT: 0.19999999999999996, completed/running/unknown 1/1/1&sum;3 (6%/50), started new job               
2025-05-07 16:18:54: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/2&sum;3 (6%/50), new result: 0.2789473684210526          
2025-05-07 16:19:36: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.28421052631578947         
2025-05-07 16:20:13: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 2 jobs  
2025-05-07 16:20:35: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 16:20:56: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), eval start                                        
2025-05-07 16:21:20: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                  
2025-05-07 16:21:43: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 16:22:03: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.35789473684210527         
2025-05-07 16:22:40: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), new result: 0.2421052631578947                    
2025-05-07 16:23:21: BoTorchModel, best RESULT: 0.19999999999999996, finishing jobs (_get_next_trials), finished 2 jobs                       
2025-05-07 16:23:41: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                       
2025-05-07 16:24:02: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                               
2025-05-07 16:24:27: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                         
2025-05-07 16:24:55: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1&sum;1 (2%/50), started new job                                     
2025-05-07 16:25:42: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 16:26:08: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), eval start                                        
2025-05-07 16:26:27: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                  
2025-05-07 16:26:47: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 16:27:06: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.3157894736842105          
2025-05-07 16:27:43: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), new result: 0.30000000000000004                   
2025-05-07 16:28:26: BoTorchModel, best RESULT: 0.19999999999999996, finishing jobs (_get_next_trials), finished 2 jobs                       
2025-05-07 16:28:46: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                       
2025-05-07 16:29:09: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                               
2025-05-07 16:29:32: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                         
2025-05-07 16:29:59: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1&sum;1 (2%/50), started new job                                     
2025-05-07 16:30:53: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 16:31:27: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 16:31:47: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 16:32:09: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 16:32:32: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.3631578947368421          
2025-05-07 16:33:14: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), new result: 0.2789473684210526                    
2025-05-07 16:33:58: BoTorchModel, best RESULT: 0.19999999999999996, finishing jobs, finished 2 jobs                                          
2025-05-07 16:34:23: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                       
2025-05-07 16:34:55: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                               
2025-05-07 16:35:17: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                         
2025-05-07 16:35:39: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1&sum;1 (2%/50), started new job                                     
2025-05-07 16:36:18: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 16:36:43: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), eval start                                        
2025-05-07 16:37:05: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                  
2025-05-07 16:37:27: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 16:37:54: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.3631578947368421          
2025-05-07 16:38:35: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 16:38:53: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 16:39:17: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 16:39:40: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 16:39:59: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 16:40:19: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.2315789473684211          
2025-05-07 16:40:56: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 16:41:12: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 16:41:34: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 16:41:57: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                  
2025-05-07 16:42:20: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 16:42:44: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.23684210526315785         
2025-05-07 16:43:28: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), new result: 0.3631578947368421                    
2025-05-07 16:44:19: BoTorchModel, best RESULT: 0.19999999999999996, finishing jobs (_get_next_trials), finished 2 jobs                       
2025-05-07 16:44:43: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                       
2025-05-07 16:45:06: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                               
2025-05-07 16:45:28: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                         
2025-05-07 16:45:45: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1&sum;1 (2%/50), started new job                                     
2025-05-07 16:46:36: BoTorchModel, best RESULT: 0.19999999999999996, pending 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 16:46:57: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 16:47:21: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 16:47:45: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 16:48:09: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.22631578947368425         
2025-05-07 16:48:53: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), new result: 0.2421052631578947                    
2025-05-07 16:49:36: BoTorchModel, best RESULT: 0.19999999999999996, finishing jobs (_get_next_trials), finished 2 jobs                       
2025-05-07 16:50:03: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                       
2025-05-07 16:50:27: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                               
2025-05-07 16:50:55: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                         
2025-05-07 16:51:21: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1&sum;1 (2%/50), started new job                                     
2025-05-07 16:52:19: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 16:52:43: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), eval start                                        
2025-05-07 16:53:02: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                  
2025-05-07 16:53:26: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 16:53:47: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.3421052631578947          
2025-05-07 16:54:40: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 16:55:06: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), getting new HP set                                
2025-05-07 16:55:36: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), eval start                                        
2025-05-07 16:56:01: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                  
2025-05-07 16:56:29: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 16:56:51: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.2947368421052632          
2025-05-07 16:57:40: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 16:58:04: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), getting new HP set                                
2025-05-07 16:58:30: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), eval start                                        
2025-05-07 16:58:56: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                  
2025-05-07 16:59:22: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 16:59:55: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.26315789473684215         
2025-05-07 17:00:39: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), new result: 0.3526315789473684                    
2025-05-07 17:01:30: BoTorchModel, best RESULT: 0.19999999999999996, finishing jobs (_get_next_trials), finished 2 jobs                       
2025-05-07 17:01:50: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                       
2025-05-07 17:02:13: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                               
2025-05-07 17:02:21: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                         
2025-05-07 17:02:32: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1&sum;1 (2%/50), started new job                                     
2025-05-07 17:02:56: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 17:03:08: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 17:03:16: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 17:03:27: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 17:03:36: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.32105263157894737         
2025-05-07 17:03:58: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 17:04:07: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 17:04:26: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), eval start                                        
2025-05-07 17:04:35: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                  
2025-05-07 17:04:43: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 17:04:54: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.42105263157894735         
2025-05-07 17:05:16: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 17:05:27: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 17:05:38: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 17:05:48: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                  
2025-05-07 17:05:57: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 17:06:05: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.3526315789473684          
2025-05-07 17:06:21: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 17:06:29: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 17:06:42: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 17:06:51: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 17:07:00: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 17:07:08: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.2210526315789474          
2025-05-07 17:07:24: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 17:07:36: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 17:07:48: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 17:07:57: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 17:08:06: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 17:08:14: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.32105263157894737         
2025-05-07 17:08:42: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 17:08:50: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 17:09:03: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), eval start                                        
2025-05-07 17:09:13: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                  
2025-05-07 17:09:27: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 17:09:41: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.31052631578947365         
2025-05-07 17:10:08: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), new result: 0.2947368421052632                    
2025-05-07 17:10:33: BoTorchModel, best RESULT: 0.19999999999999996, finishing jobs (_get_next_trials), finished 2 jobs                       
2025-05-07 17:10:41: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                       
2025-05-07 17:10:58: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                               
2025-05-07 17:11:08: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                         
2025-05-07 17:11:21: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1&sum;1 (2%/50), started new job                                     
2025-05-07 17:11:43: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 17:11:57: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 17:12:06: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 17:12:24: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 17:12:34: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.20526315789473681         
2025-05-07 17:12:55: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 17:13:03: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 17:13:17: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 17:13:31: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 17:13:44: BoTorchModel, best RESULT: 0.19999999999999996, running/unknown 1/1&sum;2 (4%/50), started new job                           
2025-05-07 17:13:54: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.22631578947368425         
2025-05-07 17:14:15: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 17:14:30: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 17:14:45: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 17:14:54: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                  
2025-05-07 17:15:02: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 17:15:11: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.2578947368421053          
2025-05-07 17:15:30: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 17:15:39: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 17:15:51: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 17:16:02: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                  
2025-05-07 17:16:11: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 17:16:19: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.2421052631578947          
2025-05-07 17:16:42: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 17:16:51: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 17:17:04: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 17:17:12: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 17:17:20: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 17:17:31: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.22631578947368425         
2025-05-07 17:17:53: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), new result: 0.2210526315789474                      
2025-05-07 17:18:12: BoTorchModel, best RESULT: 0.19999999999999996, finishing jobs (_get_next_trials), finished 2 jobs                       
2025-05-07 17:18:19: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                       
2025-05-07 17:18:32: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                               
2025-05-07 17:18:44: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                         
2025-05-07 17:18:56: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1&sum;1 (2%/50), started new job                                     
2025-05-07 17:19:15: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 17:19:27: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 17:19:39: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                  
2025-05-07 17:19:51: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 17:20:03: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.32105263157894737         
2025-05-07 17:20:23: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 17:20:32: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 17:20:47: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 17:20:56: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                  
2025-05-07 17:21:07: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 17:21:16: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.3631578947368421          
2025-05-07 17:21:35: BoTorchModel, best RESULT: 0.19999999999999996, pending 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 17:21:48: BoTorchModel, best RESULT: 0.19999999999999996, pending 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 17:22:06: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 17:22:14: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 17:22:24: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 17:22:32: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.3631578947368421          
2025-05-07 17:22:53: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 17:23:04: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 17:23:22: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 17:23:33: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 17:23:46: BoTorchModel, best RESULT: 0.19999999999999996, running/unknown 1/1&sum;2 (4%/50), started new job                           
2025-05-07 17:24:05: BoTorchModel, best RESULT: 0.19999999999999996, running/pending 1/1&sum;2 (4%/50), getting new HP set                        
2025-05-07 17:24:20: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), eval start                              
2025-05-07 17:24:30: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), starting new job                        
2025-05-07 17:24:39: BoTorchModel, best RESULT: 0.19999999999999996, completed/running/unknown 1/1/1&sum;3 (6%/50), started new job               
2025-05-07 17:24:48: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/2&sum;3 (6%/50), new result: 0.23684210526315785         
2025-05-07 17:25:06: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.4052631578947369          
2025-05-07 17:25:25: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), new result: 0.3421052631578947                      
2025-05-07 17:25:42: BoTorchModel, best RESULT: 0.19999999999999996, finishing jobs (_get_next_trials), finished 3 jobs                       
2025-05-07 17:25:50: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                       
2025-05-07 17:26:04: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                               
2025-05-07 17:26:13: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                         
2025-05-07 17:26:25: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1&sum;1 (2%/50), started new job                                     
2025-05-07 17:26:47: BoTorchModel, best RESULT: 0.19999999999999996, pending 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 17:26:59: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 17:27:09: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 17:27:19: BoTorchModel, best RESULT: 0.19999999999999996, running/unknown 1/1&sum;2 (4%/50), started new job                           
2025-05-07 17:27:27: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.32105263157894737         
2025-05-07 17:27:46: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 17:27:55: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 17:28:10: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 17:28:19: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 17:28:30: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 17:28:40: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.27368421052631575         
2025-05-07 17:28:59: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 17:29:08: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 17:29:22: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 17:29:30: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                  
2025-05-07 17:29:42: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 17:29:51: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.2421052631578947          
2025-05-07 17:30:11: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 17:30:21: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 17:30:36: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 17:30:46: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                  
2025-05-07 17:30:58: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 17:31:10: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.25263157894736843         
2025-05-07 17:31:45: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 17:31:57: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 17:32:12: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 17:32:28: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 17:32:38: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 17:32:48: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.3526315789473684          
2025-05-07 17:33:09: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 17:33:22: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 17:33:38: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 17:33:47: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                  
2025-05-07 17:33:58: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 17:34:07: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.2789473684210526          
2025-05-07 17:34:28: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 17:34:38: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 17:34:52: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 17:35:01: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                  
2025-05-07 17:35:12: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                         
2025-05-07 17:35:23: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.27368421052631575         
2025-05-07 17:35:55: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job   
2025-05-07 17:36:05: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                  
2025-05-07 17:36:22: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                          
2025-05-07 17:36:33: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                    
2025-05-07 17:36:45: BoTorchModel, best RESULT: 0.19999999999999996, running/unknown 1/1&sum;2 (4%/50), started new job                           
2025-05-07 17:37:08: BoTorchModel, best RESULT: 0.19999999999999996, running 2&sum;2 (4%/50), getting new HP set                                  
2025-05-07 17:37:25: BoTorchModel, best RESULT: 0.19999999999999996, running 2&sum;2 (4%/50), eval start                                          
2025-05-07 17:37:36: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), starting new job                        
2025-05-07 17:37:48: BoTorchModel, best RESULT: 0.19999999999999996, completed/running/unknown 1/1/1&sum;3 (6%/50), started new job               
2025-05-07 17:37:58: BoTorchModel, best RESULT: 0.19999999999999996, completed/running/pending 1/1/1&sum;3 (6%/50), new result: 0.21052631578947367
2025-05-07 17:38:22: BoTorchModel, best RESULT: 0.19999999999999996, running 2&sum;2 (4%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 17:38:31: BoTorchModel, best RESULT: 0.19999999999999996, running 2&sum;2 (4%/50), getting new HP set                                   
2025-05-07 17:38:50: BoTorchModel, best RESULT: 0.19999999999999996, running 2&sum;2 (4%/50), eval start                                           
2025-05-07 17:39:00: BoTorchModel, best RESULT: 0.19999999999999996, completed 2&sum;2 (4%/50), starting new job                                   
2025-05-07 17:39:11: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 2/1&sum;3 (6%/50), started new job                          
2025-05-07 17:39:23: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 2/1&sum;3 (6%/50), new result: 0.3157894736842105           
2025-05-07 17:39:47: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.2684210526315789           
2025-05-07 17:40:10: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 2 jobs   
2025-05-07 17:40:20: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 17:40:40: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), eval start                                         
2025-05-07 17:40:51: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 17:41:02: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 17:41:13: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.3631578947368421           
2025-05-07 17:41:40: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 17:41:50: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 17:42:06: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), eval start                                         
2025-05-07 17:42:15: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 17:42:26: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 17:42:36: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.2789473684210526           
2025-05-07 17:42:57: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 17:43:06: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 17:43:23: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 17:43:32: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 17:43:43: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 17:43:53: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.20526315789473681          
2025-05-07 17:44:14: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 17:44:24: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 17:44:42: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 17:44:51: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 17:45:02: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 17:45:12: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.24736842105263157          
2025-05-07 17:45:33: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 17:45:43: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 17:45:59: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 17:46:09: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                     
2025-05-07 17:46:20: BoTorchModel, best RESULT: 0.19999999999999996, running/unknown 1/1&sum;2 (4%/50), started new job                            
2025-05-07 17:46:30: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.3631578947368421           
2025-05-07 17:46:52: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 17:47:02: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 17:47:26: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), eval start                                         
2025-05-07 17:47:35: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 17:47:47: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 17:47:57: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.3631578947368421           
2025-05-07 17:48:18: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 17:48:28: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 17:48:45: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 17:48:54: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 17:49:06: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 17:49:17: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.30000000000000004          
2025-05-07 17:49:38: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 17:49:48: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 17:50:04: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 17:50:14: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                     
2025-05-07 17:50:26: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 17:50:36: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.2947368421052632           
2025-05-07 17:50:58: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 17:51:08: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 17:51:26: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 17:51:36: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 17:51:47: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 17:51:57: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.3526315789473684           
2025-05-07 17:52:19: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 17:52:29: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 17:52:46: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 17:52:56: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                     
2025-05-07 17:53:08: BoTorchModel, best RESULT: 0.19999999999999996, running/unknown 1/1&sum;2 (4%/50), started new job                            
2025-05-07 17:53:30: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.3526315789473684           
2025-05-07 17:53:52: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing previous jobs (2), finished 1 job          
2025-05-07 17:54:03: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), waiting for 1 job                                    
2025-05-07 17:54:18: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), new result: 0.2947368421052632                       
2025-05-07 17:54:40: BoTorchModel, best RESULT: 0.19999999999999996, waiting for 1 job), finished 1 job                                        
2025-05-07 17:54:50: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                        
2025-05-07 17:55:08: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                                
2025-05-07 17:55:18: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                          
2025-05-07 17:55:29: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1&sum;1 (2%/50), started new job                                      
2025-05-07 17:55:50: BoTorchModel, best RESULT: 0.19999999999999996, pending 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 17:56:06: BoTorchModel, best RESULT: 0.19999999999999996, pending 1&sum;1 (2%/50), eval start                                           
2025-05-07 17:56:16: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                     
2025-05-07 17:56:27: BoTorchModel, best RESULT: 0.19999999999999996, running/unknown 1/1&sum;2 (4%/50), started new job                            
2025-05-07 17:56:38: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.3526315789473684           
2025-05-07 17:57:01: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 17:57:11: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 17:57:27: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 17:57:38: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 17:57:49: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 17:57:59: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.31052631578947365          
2025-05-07 17:58:22: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 17:58:32: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 17:58:49: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 17:58:59: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 17:59:11: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 17:59:21: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.2578947368421053           
2025-05-07 17:59:43: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 17:59:54: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 18:00:12: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 18:00:23: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                     
2025-05-07 18:00:34: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 18:00:44: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.28421052631578947          
2025-05-07 18:01:07: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 18:01:17: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 18:01:34: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 18:01:44: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                     
2025-05-07 18:01:55: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 18:02:05: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.3631578947368421           
2025-05-07 18:02:27: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 18:02:38: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 18:02:56: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 18:03:07: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 18:03:18: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 18:03:29: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.34736842105263155          
2025-05-07 18:03:52: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 18:04:01: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 18:04:21: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 18:04:31: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 18:04:43: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 18:04:55: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.3631578947368421           
2025-05-07 18:05:18: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 18:05:27: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 18:05:45: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 18:05:56: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                     
2025-05-07 18:06:08: BoTorchModel, best RESULT: 0.19999999999999996, running/unknown 1/1&sum;2 (4%/50), started new job                            
2025-05-07 18:06:19: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.24736842105263157          
2025-05-07 18:06:42: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 18:06:52: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 18:07:10: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 18:07:21: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                     
2025-05-07 18:07:33: BoTorchModel, best RESULT: 0.19999999999999996, running/unknown 1/1&sum;2 (4%/50), started new job                            
2025-05-07 18:07:47: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.3631578947368421           
2025-05-07 18:08:10: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 18:08:21: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 18:08:42: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 18:08:53: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 18:09:04: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 18:09:15: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.20526315789473681          
2025-05-07 18:09:39: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 18:09:49: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 18:10:07: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 18:10:18: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                     
2025-05-07 18:10:29: BoTorchModel, best RESULT: 0.19999999999999996, running/unknown 1/1&sum;2 (4%/50), started new job                            
2025-05-07 18:10:40: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.25263157894736843          
2025-05-07 18:11:07: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 18:11:18: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 18:11:35: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 18:11:45: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 18:11:56: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 18:12:07: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.2684210526315789           
2025-05-07 18:12:29: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 18:12:40: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 18:13:01: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 18:13:11: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 18:13:23: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 18:13:34: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.21578947368421053          
2025-05-07 18:13:57: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 18:14:07: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 18:14:26: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 18:14:37: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 18:14:48: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 18:14:59: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.3631578947368421           
2025-05-07 18:15:22: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 18:15:33: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 18:15:51: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 18:16:01: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 18:16:13: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 18:16:24: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.26315789473684215          
2025-05-07 18:16:48: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 18:16:59: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 18:17:18: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 18:17:28: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 18:17:41: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 18:17:52: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.34736842105263155          
2025-05-07 18:18:15: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), new result: 0.24736842105263157                    
2025-05-07 18:18:37: BoTorchModel, best RESULT: 0.19999999999999996, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 18:18:47: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                        
2025-05-07 18:19:06: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                                
2025-05-07 18:19:17: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                          
2025-05-07 18:19:29: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1&sum;1 (2%/50), started new job                                      
2025-05-07 18:19:51: BoTorchModel, best RESULT: 0.19999999999999996, pending 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 18:20:10: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 18:20:21: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                     
2025-05-07 18:20:33: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 18:20:45: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.22631578947368425          
2025-05-07 18:21:09: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 18:21:20: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 18:21:39: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 18:21:50: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 18:22:01: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 18:22:13: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.35789473684210527          
2025-05-07 18:22:37: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 18:22:47: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 18:23:06: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 18:23:17: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 18:23:28: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 18:23:39: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.24736842105263157          
2025-05-07 18:24:03: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), new result: 0.2421052631578947                     
2025-05-07 18:24:26: BoTorchModel, best RESULT: 0.19999999999999996, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 18:24:37: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                        
2025-05-07 18:24:57: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                                
2025-05-07 18:25:09: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                          
2025-05-07 18:25:23: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1&sum;1 (2%/50), started new job                                      
2025-05-07 18:25:47: BoTorchModel, best RESULT: 0.19999999999999996, pending 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 18:26:07: BoTorchModel, best RESULT: 0.19999999999999996, pending 1&sum;1 (2%/50), eval start                                           
2025-05-07 18:26:18: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 18:26:30: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 18:26:41: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.22631578947368425          
2025-05-07 18:27:04: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 18:27:16: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 18:27:35: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 18:27:46: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 18:27:58: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 18:28:09: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.3631578947368421           
2025-05-07 18:28:32: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), new result: 0.2578947368421053                     
2025-05-07 18:28:55: BoTorchModel, best RESULT: 0.19999999999999996, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 18:29:06: BoTorchModel, best RESULT: 0.19999999999999996, getting new HP set                                                        
2025-05-07 18:29:28: BoTorchModel, best RESULT: 0.19999999999999996, eval start                                                                
2025-05-07 18:29:39: BoTorchModel, best RESULT: 0.19999999999999996, starting new job                                                          
2025-05-07 18:29:50: BoTorchModel, best RESULT: 0.19999999999999996, unknown 1&sum;1 (2%/50), started new job                                      
2025-05-07 18:30:14: BoTorchModel, best RESULT: 0.19999999999999996, pending 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 18:30:32: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 18:30:43: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), starting new job                                     
2025-05-07 18:30:55: BoTorchModel, best RESULT: 0.19999999999999996, running/unknown 1/1&sum;2 (4%/50), started new job                            
2025-05-07 18:31:06: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.3631578947368421           
2025-05-07 18:31:30: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 18:31:40: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 18:31:59: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 18:32:10: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 18:32:25: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 18:32:36: BoTorchModel, best RESULT: 0.19999999999999996, completed/pending 1/1&sum;2 (4%/50), new result: 0.3631578947368421           
2025-05-07 18:32:59: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 18:33:10: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 18:33:30: BoTorchModel, best RESULT: 0.19999999999999996, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 18:33:41: BoTorchModel, best RESULT: 0.19999999999999996, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 18:33:52: BoTorchModel, best RESULT: 0.19999999999999996, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 18:34:04: BoTorchModel, best RESULT: 0.19999999999999996, completed/running 1/1&sum;2 (4%/50), new result: 0.18947368421052635          
2025-05-07 18:34:27: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), new result: 0.28421052631578947                    
2025-05-07 18:34:51: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 18:35:01: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 18:35:20: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 18:35:31: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 18:35:43: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1&sum;1 (2%/50), started new job                                      
2025-05-07 18:36:05: BoTorchModel, best RESULT: 0.18947368421052635, pending 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 18:36:23: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 18:36:34: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), starting new job                                     
2025-05-07 18:36:46: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 18:36:57: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1&sum;2 (4%/50), new result: 0.21578947368421053          
2025-05-07 18:37:25: BoTorchModel, best RESULT: 0.18947368421052635, pending 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 18:37:35: BoTorchModel, best RESULT: 0.18947368421052635, pending 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 18:37:57: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), eval start                                         
2025-05-07 18:38:08: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 18:38:20: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 18:38:31: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1&sum;2 (4%/50), new result: 0.35789473684210527          
2025-05-07 18:38:54: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), new result: 0.23684210526315785                    
2025-05-07 18:39:17: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 18:39:27: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 18:39:52: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 18:40:03: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 18:40:15: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1&sum;1 (2%/50), started new job                                      
2025-05-07 18:40:39: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 18:40:57: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 18:41:09: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 18:41:21: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 18:41:32: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1&sum;2 (4%/50), new result: 0.19999999999999996          
2025-05-07 18:41:56: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), new result: 0.21578947368421053                    
2025-05-07 18:42:18: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 18:42:29: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 18:42:48: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 18:42:59: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 18:43:11: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1&sum;1 (2%/50), started new job                                      
2025-05-07 18:43:35: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 18:43:53: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), eval start                                         
2025-05-07 18:44:04: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 18:44:16: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 18:44:28: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1&sum;2 (4%/50), new result: 0.21052631578947367          
2025-05-07 18:44:51: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), new result: 0.26315789473684215                    
2025-05-07 18:45:15: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 18:45:26: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 18:45:45: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 18:45:56: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 18:46:09: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1&sum;1 (2%/50), started new job                                      
2025-05-07 18:46:32: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 18:46:51: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 18:47:02: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 18:47:16: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 18:47:27: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1&sum;2 (4%/50), new result: 0.3052631578947368           
2025-05-07 18:47:52: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), new result: 0.3631578947368421                     
2025-05-07 18:48:16: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 18:48:27: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 18:48:46: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 18:48:57: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 18:49:09: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1&sum;1 (2%/50), started new job                                      
2025-05-07 18:49:33: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 18:49:51: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), eval start                                         
2025-05-07 18:50:06: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 18:50:18: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 18:50:29: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1&sum;2 (4%/50), new result: 0.2894736842105263           
2025-05-07 18:50:54: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 18:51:05: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 18:51:26: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 18:51:37: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 18:51:50: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 18:52:02: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1&sum;2 (4%/50), new result: 0.22631578947368425          
2025-05-07 18:52:25: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), new result: 0.21578947368421053                    
2025-05-07 18:52:52: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 18:53:03: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 18:53:24: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 18:53:35: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 18:53:48: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1&sum;1 (2%/50), started new job                                      
2025-05-07 18:54:13: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 18:54:32: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 18:54:43: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 18:54:56: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 18:55:07: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1&sum;2 (4%/50), new result: 0.27368421052631575          
2025-05-07 18:55:31: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), new result: 0.24736842105263157                    
2025-05-07 18:55:55: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 18:56:06: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 18:56:27: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 18:56:38: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 18:56:50: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1&sum;1 (2%/50), started new job                                      
2025-05-07 18:57:13: BoTorchModel, best RESULT: 0.18947368421052635, pending 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 18:57:34: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), eval start                                         
2025-05-07 18:57:45: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 18:57:58: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 18:58:10: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1&sum;2 (4%/50), new result: 0.20526315789473681          
2025-05-07 18:58:36: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 18:58:47: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 18:59:06: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 18:59:17: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 18:59:30: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 18:59:42: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1&sum;2 (4%/50), new result: 0.25263157894736843          
2025-05-07 19:00:07: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 19:00:18: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 19:00:39: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 19:00:51: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 19:01:03: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 19:01:15: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1&sum;2 (4%/50), new result: 0.2210526315789474           
2025-05-07 19:01:41: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 19:01:53: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 19:02:13: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 19:02:24: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 19:02:37: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 19:02:49: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1&sum;2 (4%/50), new result: 0.3315789473684211           
2025-05-07 19:03:14: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 19:03:25: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 19:03:45: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 19:03:57: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 19:04:09: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 19:04:22: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1&sum;2 (4%/50), new result: 0.24736842105263157          
2025-05-07 19:04:48: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 19:05:00: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 19:05:20: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 19:05:32: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 19:05:45: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 19:05:58: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1&sum;2 (4%/50), new result: 0.3157894736842105           
2025-05-07 19:06:24: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 19:06:36: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 19:06:57: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 19:07:08: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 19:07:21: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 19:07:33: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1&sum;2 (4%/50), new result: 0.2421052631578947           
2025-05-07 19:08:01: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs, finished 1 job                       
2025-05-07 19:08:13: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), new result: 0.33684210526315794                      
2025-05-07 19:08:38: BoTorchModel, best RESULT: 0.18947368421052635, finishing previous jobs (1), finished 1 job                               
2025-05-07 19:08:52: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 19:09:15: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 19:09:27: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 19:09:39: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1&sum;1 (2%/50), started new job                                      
2025-05-07 19:10:06: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), getting new HP set                                 
2025-05-07 19:10:25: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), eval start                                         
2025-05-07 19:10:38: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 19:10:50: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 19:11:03: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1&sum;2 (4%/50), new result: 0.24736842105263157          
2025-05-07 19:11:31: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 19:11:43: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 19:12:07: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 19:12:20: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 19:12:34: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 19:12:46: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1&sum;2 (4%/50), new result: 0.2315789473684211           
2025-05-07 19:13:12: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), new result: 0.2421052631578947                     
2025-05-07 19:13:37: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 19:13:49: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 19:14:14: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 19:14:25: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 19:14:39: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1&sum;1 (2%/50), started new job                                      
2025-05-07 19:15:04: BoTorchModel, best RESULT: 0.18947368421052635, pending 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 19:15:27: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), eval start                                         
2025-05-07 19:15:40: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 19:15:55: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 19:16:09: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1&sum;2 (4%/50), new result: 0.2210526315789474           
2025-05-07 19:16:40: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), new result: 0.2421052631578947                     
2025-05-07 19:17:05: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 19:17:16: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 19:17:43: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 19:17:55: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 19:18:08: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1&sum;1 (2%/50), started new job                                      
2025-05-07 19:18:33: BoTorchModel, best RESULT: 0.18947368421052635, pending 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 19:18:54: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 19:19:06: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), starting new job                                     
2025-05-07 19:19:19: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 19:19:31: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1&sum;2 (4%/50), new result: 0.20526315789473681          
2025-05-07 19:19:59: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 19:20:10: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 19:20:30: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 19:20:42: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 19:20:56: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 19:21:08: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1&sum;2 (4%/50), new result: 0.3263157894736842           
2025-05-07 19:21:35: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 19:21:46: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 19:22:09: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 19:22:21: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 19:22:34: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 19:22:46: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1&sum;2 (4%/50), new result: 0.3631578947368421           
2025-05-07 19:23:11: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), new result: 0.2421052631578947                     
2025-05-07 19:23:37: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 19:23:48: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 19:24:10: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 19:24:22: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 19:24:35: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1&sum;1 (2%/50), started new job                                      
2025-05-07 19:25:01: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 19:25:20: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), eval start                                         
2025-05-07 19:25:31: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 19:25:45: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 19:25:57: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1&sum;2 (4%/50), new result: 0.31052631578947365          
2025-05-07 19:26:23: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), new result: 0.3315789473684211                     
2025-05-07 19:26:48: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 19:26:59: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 19:27:23: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 19:27:35: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 19:27:48: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1&sum;1 (2%/50), started new job                                      
2025-05-07 19:28:15: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 19:28:36: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 19:28:48: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 19:29:01: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 19:29:13: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1&sum;2 (4%/50), new result: 0.2684210526315789           
2025-05-07 19:29:39: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 19:29:50: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 19:30:09: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 19:30:21: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 19:30:33: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 19:30:45: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1&sum;2 (4%/50), new result: 0.2421052631578947           
2025-05-07 19:31:11: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 19:31:22: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 19:31:42: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 19:31:54: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 19:32:07: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 19:32:18: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1&sum;2 (4%/50), new result: 0.3052631578947368           
2025-05-07 19:32:44: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 19:32:55: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 19:33:18: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 19:33:30: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 19:33:43: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 19:33:55: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1&sum;2 (4%/50), new result: 0.24736842105263157          
2025-05-07 19:34:21: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 19:34:32: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 19:34:57: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), eval start                                         
2025-05-07 19:35:08: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 19:35:21: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 19:35:33: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1&sum;2 (4%/50), new result: 0.3315789473684211           
2025-05-07 19:35:59: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 19:36:10: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 19:36:31: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 19:36:43: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 19:36:56: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 19:37:07: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1&sum;2 (4%/50), new result: 0.2421052631578947           
2025-05-07 19:37:34: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 19:37:45: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 19:38:06: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 19:38:18: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 19:38:31: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 19:38:42: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1&sum;2 (4%/50), new result: 0.32105263157894737          
2025-05-07 19:39:09: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 19:39:20: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 19:39:41: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 19:39:53: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 19:40:05: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 19:40:17: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1&sum;2 (4%/50), new result: 0.31052631578947365          
2025-05-07 19:40:44: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 19:40:55: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 19:41:15: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 19:41:27: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 19:41:40: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 19:41:51: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1&sum;2 (4%/50), new result: 0.25263157894736843          
2025-05-07 19:42:18: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 19:42:29: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 19:42:49: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 19:43:01: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 19:43:13: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 19:43:25: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1&sum;2 (4%/50), new result: 0.23684210526315785          
2025-05-07 19:43:51: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 19:44:03: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 19:44:24: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 19:44:36: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 19:44:52: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 19:45:04: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1&sum;2 (4%/50), new result: 0.2789473684210526           
2025-05-07 19:45:30: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), new result: 0.21052631578947367                      
2025-05-07 19:45:55: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 19:46:07: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 19:46:28: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 19:46:40: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 19:46:54: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1&sum;1 (2%/50), started new job                                      
2025-05-07 19:47:20: BoTorchModel, best RESULT: 0.18947368421052635, pending 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 19:47:41: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), eval start                                         
2025-05-07 19:47:53: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 19:48:06: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 19:48:18: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1&sum;2 (4%/50), new result: 0.3631578947368421           
2025-05-07 19:48:44: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), new result: 0.21052631578947367                    
2025-05-07 19:49:09: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 19:49:21: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 19:49:56: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 19:50:08: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 19:50:20: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1&sum;1 (2%/50), started new job                                      
2025-05-07 19:50:46: BoTorchModel, best RESULT: 0.18947368421052635, pending 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 19:51:09: BoTorchModel, best RESULT: 0.18947368421052635, pending 1&sum;1 (2%/50), eval start                                           
2025-05-07 19:51:22: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 19:51:35: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 19:51:48: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1&sum;2 (4%/50), new result: 0.2947368421052632           
2025-05-07 19:52:15: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 19:52:27: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 19:52:50: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 19:53:02: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 19:53:16: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 19:53:29: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1&sum;2 (4%/50), new result: 0.23684210526315785          
2025-05-07 19:53:55: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), new result: 0.27368421052631575                    
2025-05-07 19:54:21: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 19:54:33: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 19:54:56: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 19:55:08: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 19:55:22: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1&sum;1 (2%/50), started new job                                      
2025-05-07 19:55:48: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 19:56:12: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 19:56:24: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 19:56:38: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 19:56:51: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1&sum;2 (4%/50), new result: 0.2789473684210526           
2025-05-07 19:57:16: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), new result: 0.3631578947368421                     
2025-05-07 19:57:43: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 19:57:56: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 19:58:20: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 19:58:31: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 19:58:45: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1&sum;1 (2%/50), started new job                                      
2025-05-07 19:59:11: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 19:59:35: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 19:59:47: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 20:00:01: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 20:00:13: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1&sum;2 (4%/50), new result: 0.21578947368421053          
2025-05-07 20:00:41: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 20:00:53: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 20:01:16: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 20:01:28: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 20:01:42: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 20:01:55: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1&sum;2 (4%/50), new result: 0.27368421052631575          
2025-05-07 20:02:22: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 20:02:35: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 20:02:57: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 20:03:09: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 20:03:23: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 20:03:36: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1&sum;2 (4%/50), new result: 0.27368421052631575          
2025-05-07 20:04:06: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 20:04:19: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 20:04:41: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 20:04:53: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 20:05:07: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 20:05:20: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1&sum;2 (4%/50), new result: 0.21578947368421053          
2025-05-07 20:05:47: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), new result: 0.2947368421052632                       
2025-05-07 20:06:14: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 20:06:26: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 20:06:51: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 20:07:03: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 20:07:17: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1&sum;1 (2%/50), started new job                                      
2025-05-07 20:07:44: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 20:08:08: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 20:08:20: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 20:08:34: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 20:08:47: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1&sum;2 (4%/50), new result: 0.3631578947368421           
2025-05-07 20:09:14: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), new result: 0.21578947368421053                    
2025-05-07 20:09:40: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 20:09:53: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 20:10:19: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 20:10:32: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 20:10:46: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1&sum;1 (2%/50), started new job                                      
2025-05-07 20:11:13: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), getting new HP set                                 
2025-05-07 20:11:35: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), eval start                                         
2025-05-07 20:11:47: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 20:12:01: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 20:12:14: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1&sum;2 (4%/50), new result: 0.30000000000000004          
2025-05-07 20:12:42: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 20:12:54: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 20:13:19: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 20:13:33: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 20:13:47: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 20:14:00: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1&sum;2 (4%/50), new result: 0.2421052631578947           
2025-05-07 20:14:28: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 20:14:42: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 20:15:05: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 20:15:18: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 20:15:32: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 20:15:46: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1&sum;2 (4%/50), new result: 0.24736842105263157          
2025-05-07 20:16:14: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), new result: 0.24736842105263157                    
2025-05-07 20:16:41: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 20:16:53: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 20:17:19: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 20:17:31: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 20:17:45: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1&sum;1 (2%/50), started new job                                      
2025-05-07 20:18:12: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 20:18:34: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 20:18:47: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 20:19:01: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 20:19:14: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1&sum;2 (4%/50), new result: 0.2894736842105263           
2025-05-07 20:19:42: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 20:19:55: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 20:20:19: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 20:20:32: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 20:20:45: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 20:20:58: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1&sum;2 (4%/50), new result: 0.22631578947368425          
2025-05-07 20:21:26: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 20:21:38: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 20:22:04: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), eval start                                         
2025-05-07 20:22:17: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 20:22:30: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 20:22:44: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1&sum;2 (4%/50), new result: 0.2315789473684211           
2025-05-07 20:23:15: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), new result: 0.21578947368421053                      
2025-05-07 20:23:42: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 20:23:54: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 20:24:20: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 20:24:38: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 20:24:53: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1&sum;1 (2%/50), started new job                                      
2025-05-07 20:25:21: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 20:25:45: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 20:25:58: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 20:26:11: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 20:26:24: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1&sum;2 (4%/50), new result: 0.2421052631578947           
2025-05-07 20:26:53: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 20:27:05: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 20:27:29: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 20:27:42: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), starting new job                                     
2025-05-07 20:27:56: BoTorchModel, best RESULT: 0.18947368421052635, running/unknown 1/1&sum;2 (4%/50), started new job                            
2025-05-07 20:28:27: BoTorchModel, best RESULT: 0.18947368421052635, running 2&sum;2 (4%/50), getting new HP set                                   
2025-05-07 20:28:52: BoTorchModel, best RESULT: 0.18947368421052635, running 2&sum;2 (4%/50), eval start                                           
2025-05-07 20:29:04: BoTorchModel, best RESULT: 0.18947368421052635, running 2&sum;2 (4%/50), starting new job                                     
2025-05-07 20:29:19: BoTorchModel, best RESULT: 0.18947368421052635, running/unknown 2/1&sum;3 (6%/50), started new job                            
2025-05-07 20:29:53: BoTorchModel, best RESULT: 0.18947368421052635, running 3&sum;3 (6%/50), getting new HP set                                   
2025-05-07 20:30:17: BoTorchModel, best RESULT: 0.18947368421052635, running 3&sum;3 (6%/50), eval start                                           
2025-05-07 20:30:30: BoTorchModel, best RESULT: 0.18947368421052635, running 3&sum;3 (6%/50), starting new job                                     
2025-05-07 20:30:45: BoTorchModel, best RESULT: 0.18947368421052635, running/unknown 3/1&sum;4 (8%/50), started new job                            
2025-05-07 20:31:21: BoTorchModel, best RESULT: 0.18947368421052635, running 4&sum;4 (8%/50), waiting for 4 jobs                                   
2025-05-07 20:31:43: BoTorchModel, best RESULT: 0.18947368421052635, running 4&sum;4 (8%/50), waiting for 4 jobs                                   
2025-05-07 20:32:05: BoTorchModel, best RESULT: 0.18947368421052635, running 4&sum;4 (8%/50), waiting for 4 jobs                                   
2025-05-07 20:32:28: BoTorchModel, best RESULT: 0.18947368421052635, running 4&sum;4 (8%/50), waiting for 4 jobs                                   
2025-05-07 20:32:51: BoTorchModel, best RESULT: 0.18947368421052635, running 4&sum;4 (8%/50), waiting for 4 jobs                                   
2025-05-07 20:33:17: BoTorchModel, best RESULT: 0.18947368421052635, running 4&sum;4 (8%/50), waiting for 4 jobs                                   
2025-05-07 20:33:39: BoTorchModel, best RESULT: 0.18947368421052635, running 4&sum;4 (8%/50), waiting for 4 jobs                                   
2025-05-07 20:34:02: BoTorchModel, best RESULT: 0.18947368421052635, running 4&sum;4 (8%/50), waiting for 4 jobs                                   
2025-05-07 20:34:25: BoTorchModel, best RESULT: 0.18947368421052635, running 4&sum;4 (8%/50), waiting for 4 jobs                                   
2025-05-07 20:34:50: BoTorchModel, best RESULT: 0.18947368421052635, running 4&sum;4 (8%/50), waiting for 4 jobs                                   
2025-05-07 20:35:13: BoTorchModel, best RESULT: 0.18947368421052635, running 4&sum;4 (8%/50), waiting for 4 jobs                                   
2025-05-07 20:35:36: BoTorchModel, best RESULT: 0.18947368421052635, running 4&sum;4 (8%/50), waiting for 4 jobs                                   
2025-05-07 20:35:59: BoTorchModel, best RESULT: 0.18947368421052635, running 4&sum;4 (8%/50), waiting for 4 jobs                                   
2025-05-07 20:36:21: BoTorchModel, best RESULT: 0.18947368421052635, running 4&sum;4 (8%/50), waiting for 4 jobs                                   
2025-05-07 20:36:44: BoTorchModel, best RESULT: 0.18947368421052635, running 4&sum;4 (8%/50), waiting for 4 jobs                                   
2025-05-07 20:37:07: BoTorchModel, best RESULT: 0.18947368421052635, running 4&sum;4 (8%/50), waiting for 4 jobs                                   
2025-05-07 20:37:31: BoTorchModel, best RESULT: 0.18947368421052635, running 4&sum;4 (8%/50), waiting for 4 jobs                                   
2025-05-07 20:37:54: BoTorchModel, best RESULT: 0.18947368421052635, running 4&sum;4 (8%/50), waiting for 4 jobs                                   
2025-05-07 20:38:18: BoTorchModel, best RESULT: 0.18947368421052635, running 4&sum;4 (8%/50), waiting for 4 jobs                                   
2025-05-07 20:38:42: BoTorchModel, best RESULT: 0.18947368421052635, running 4&sum;4 (8%/50), waiting for 4 jobs                                   
2025-05-07 20:39:07: BoTorchModel, best RESULT: 0.18947368421052635, running 4&sum;4 (8%/50), waiting for 4 jobs                                   
2025-05-07 20:39:30: BoTorchModel, best RESULT: 0.18947368421052635, running 4&sum;4 (8%/50), waiting for 4 jobs                                   
2025-05-07 20:39:50: BoTorchModel, best RESULT: 0.18947368421052635, running 4&sum;4 (8%/50), new result: 0.26315789473684215                      
2025-05-07 20:40:20: BoTorchModel, best RESULT: 0.18947368421052635, running 3&sum;3 (6%/50), new result: 0.2894736842105263                       
2025-05-07 20:40:49: BoTorchModel, best RESULT: 0.18947368421052635, running 2&sum;2 (4%/50), new result: 0.3631578947368421                       
2025-05-07 20:41:19: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), new result: 0.2684210526315789                       
2025-05-07 20:41:51: BoTorchModel, best RESULT: 0.18947368421052635, waiting for 4 jobs, finished 4 jobs                                       
2025-05-07 20:42:07: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 20:42:34: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 20:42:48: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 20:43:05: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1&sum;1 (2%/50), started new job                                      
2025-05-07 20:43:36: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 20:44:03: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 20:44:18: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 20:44:34: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 20:44:48: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1&sum;2 (4%/50), new result: 0.22631578947368425          
2025-05-07 20:45:21: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 20:45:35: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 20:46:01: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 20:46:16: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 20:46:32: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 20:46:49: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1&sum;2 (4%/50), new result: 0.2421052631578947           
2025-05-07 20:47:26: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 20:47:42: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 20:48:11: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), eval start                                         
2025-05-07 20:48:28: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 20:48:45: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 20:49:00: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1&sum;2 (4%/50), new result: 0.3631578947368421           
2025-05-07 20:49:35: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 20:49:51: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 20:50:25: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), eval start                                         
2025-05-07 20:50:40: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 20:50:58: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 20:51:16: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1&sum;2 (4%/50), new result: 0.32105263157894737          
2025-05-07 20:51:51: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), new result: 0.2789473684210526                     
2025-05-07 20:52:28: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 20:52:44: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 20:53:15: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 20:53:31: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 20:53:50: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1&sum;1 (2%/50), started new job                                      
2025-05-07 20:54:24: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 20:54:54: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 20:55:11: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 20:55:29: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 20:55:45: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1&sum;2 (4%/50), new result: 0.21578947368421053          
2025-05-07 20:56:23: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 20:56:40: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 20:57:09: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 20:57:26: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), starting new job                                     
2025-05-07 20:57:44: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 20:58:02: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1&sum;2 (4%/50), new result: 0.26315789473684215          
2025-05-07 20:58:39: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 20:58:56: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 20:59:30: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 20:59:49: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 21:00:05: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 21:00:21: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1&sum;2 (4%/50), new result: 0.3631578947368421           
2025-05-07 21:00:56: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 21:01:11: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 21:01:44: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 21:01:59: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 21:02:15: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 21:02:30: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1&sum;2 (4%/50), new result: 0.28421052631578947          
2025-05-07 21:03:00: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), new result: 0.24736842105263157                    
2025-05-07 21:03:32: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 21:03:47: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 21:04:15: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 21:04:30: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 21:04:47: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1&sum;1 (2%/50), started new job                                      
2025-05-07 21:05:19: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 21:05:49: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 21:06:05: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 21:06:21: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 21:06:36: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1&sum;2 (4%/50), new result: 0.26315789473684215          
2025-05-07 21:07:08: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 21:07:22: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 21:07:51: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 21:08:05: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 21:08:22: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 21:08:38: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1&sum;2 (4%/50), new result: 0.3631578947368421           
2025-05-07 21:09:11: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 21:09:26: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 21:09:53: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 21:10:07: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 21:10:22: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 21:10:37: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1&sum;2 (4%/50), new result: 0.3052631578947368           
2025-05-07 21:11:08: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), new result: 0.24736842105263157                    
2025-05-07 21:11:40: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 21:11:56: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 21:12:26: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 21:12:45: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 21:13:07: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1&sum;1 (2%/50), started new job                                      
2025-05-07 21:13:47: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 21:14:25: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), eval start                                         
2025-05-07 21:14:42: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 21:14:59: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 21:15:16: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1&sum;2 (4%/50), new result: 0.33684210526315794          
2025-05-07 21:15:53: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 21:16:10: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 21:16:39: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 21:16:55: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 21:17:13: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 21:17:33: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1&sum;2 (4%/50), new result: 0.24736842105263157          
2025-05-07 21:18:08: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 21:18:26: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 21:18:57: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 21:19:13: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 21:19:31: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 21:19:48: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1&sum;2 (4%/50), new result: 0.21052631578947367          
2025-05-07 21:20:24: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 21:20:40: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 21:21:08: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 21:21:24: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 21:21:43: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 21:22:03: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1&sum;2 (4%/50), new result: 0.30000000000000004          
2025-05-07 21:22:37: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), new result: 0.23684210526315785                    
2025-05-07 21:23:11: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 21:23:28: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 21:24:00: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 21:24:17: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 21:24:37: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1&sum;1 (2%/50), started new job                                      
2025-05-07 21:25:15: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 21:26:00: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), eval start                                         
2025-05-07 21:26:17: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 21:26:35: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 21:26:53: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1&sum;2 (4%/50), new result: 0.2210526315789474           
2025-05-07 21:27:30: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), new result: 0.2789473684210526                     
2025-05-07 21:28:06: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 21:28:21: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 21:28:52: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 21:29:09: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 21:29:27: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1&sum;1 (2%/50), started new job                                      
2025-05-07 21:30:07: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 21:30:38: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 21:30:57: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 21:31:17: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 21:31:35: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1&sum;2 (4%/50), new result: 0.27368421052631575          
2025-05-07 21:32:16: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 21:32:35: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 21:33:10: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 21:33:29: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 21:33:51: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 21:34:10: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1&sum;2 (4%/50), new result: 0.2894736842105263           
2025-05-07 21:34:53: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 21:35:10: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 21:35:44: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 21:36:01: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 21:36:20: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 21:36:40: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1&sum;2 (4%/50), new result: 0.26315789473684215          
2025-05-07 21:37:20: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 21:37:43: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 21:38:15: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 21:38:32: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), starting new job                                     
2025-05-07 21:38:52: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 21:39:10: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1&sum;2 (4%/50), new result: 0.2210526315789474           
2025-05-07 21:39:48: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 21:40:08: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 21:40:38: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 21:41:00: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 21:41:20: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 21:41:37: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1&sum;2 (4%/50), new result: 0.30000000000000004          
2025-05-07 21:42:13: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 21:42:30: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 21:43:02: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 21:43:22: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 21:43:40: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 21:43:57: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1&sum;2 (4%/50), new result: 0.27368421052631575          
2025-05-07 21:44:33: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), new result: 0.2684210526315789                     
2025-05-07 21:45:10: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 21:45:27: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set                                                        
2025-05-07 21:46:04: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                                
2025-05-07 21:46:28: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                          
2025-05-07 21:46:48: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1&sum;1 (2%/50), started new job                                      
2025-05-07 21:47:25: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 21:47:54: BoTorchModel, best RESULT: 0.18947368421052635, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 21:48:12: BoTorchModel, best RESULT: 0.18947368421052635, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 21:48:32: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 21:48:54: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1&sum;2 (4%/50), new result: 0.16842105263157892          
2025-05-07 21:49:32: BoTorchModel, best RESULT: 0.16842105263157892, completed 1&sum;1 (2%/50), new result: 0.3263157894736842                     
2025-05-07 21:50:12: BoTorchModel, best RESULT: 0.16842105263157892, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 21:50:32: BoTorchModel, best RESULT: 0.16842105263157892, getting new HP set                                                        
2025-05-07 21:51:15: BoTorchModel, best RESULT: 0.16842105263157892, eval start                                                                
2025-05-07 21:51:33: BoTorchModel, best RESULT: 0.16842105263157892, starting new job                                                          
2025-05-07 21:51:51: BoTorchModel, best RESULT: 0.16842105263157892, unknown 1&sum;1 (2%/50), started new job                                      
2025-05-07 21:52:29: BoTorchModel, best RESULT: 0.16842105263157892, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 21:53:00: BoTorchModel, best RESULT: 0.16842105263157892, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 21:53:19: BoTorchModel, best RESULT: 0.16842105263157892, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 21:53:37: BoTorchModel, best RESULT: 0.16842105263157892, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 21:53:55: BoTorchModel, best RESULT: 0.16842105263157892, completed/pending 1/1&sum;2 (4%/50), new result: 0.35789473684210527          
2025-05-07 21:54:33: BoTorchModel, best RESULT: 0.16842105263157892, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 21:54:50: BoTorchModel, best RESULT: 0.16842105263157892, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 21:55:21: BoTorchModel, best RESULT: 0.16842105263157892, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 21:55:38: BoTorchModel, best RESULT: 0.16842105263157892, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 21:55:57: BoTorchModel, best RESULT: 0.16842105263157892, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 21:56:16: BoTorchModel, best RESULT: 0.16842105263157892, completed/running 1/1&sum;2 (4%/50), new result: 0.25263157894736843          
2025-05-07 21:56:53: BoTorchModel, best RESULT: 0.16842105263157892, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 21:57:09: BoTorchModel, best RESULT: 0.16842105263157892, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 21:57:45: BoTorchModel, best RESULT: 0.16842105263157892, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 21:58:02: BoTorchModel, best RESULT: 0.16842105263157892, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 21:58:20: BoTorchModel, best RESULT: 0.16842105263157892, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 21:58:40: BoTorchModel, best RESULT: 0.16842105263157892, completed/running 1/1&sum;2 (4%/50), new result: 0.3631578947368421           
2025-05-07 21:59:15: BoTorchModel, best RESULT: 0.16842105263157892, completed 1&sum;1 (2%/50), new result: 0.23684210526315785                    
2025-05-07 21:59:52: BoTorchModel, best RESULT: 0.16842105263157892, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 22:00:07: BoTorchModel, best RESULT: 0.16842105263157892, getting new HP set                                                        
2025-05-07 22:00:56: BoTorchModel, best RESULT: 0.16842105263157892, eval start                                                                
2025-05-07 22:01:15: BoTorchModel, best RESULT: 0.16842105263157892, starting new job                                                          
2025-05-07 22:01:35: BoTorchModel, best RESULT: 0.16842105263157892, unknown 1&sum;1 (2%/50), started new job                                      
2025-05-07 22:02:12: BoTorchModel, best RESULT: 0.16842105263157892, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 22:02:43: BoTorchModel, best RESULT: 0.16842105263157892, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 22:02:59: BoTorchModel, best RESULT: 0.16842105263157892, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 22:03:15: BoTorchModel, best RESULT: 0.16842105263157892, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 22:03:33: BoTorchModel, best RESULT: 0.16842105263157892, completed/pending 1/1&sum;2 (4%/50), new result: 0.3631578947368421           
2025-05-07 22:04:07: BoTorchModel, best RESULT: 0.16842105263157892, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 22:04:23: BoTorchModel, best RESULT: 0.16842105263157892, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 22:04:55: BoTorchModel, best RESULT: 0.16842105263157892, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 22:05:12: BoTorchModel, best RESULT: 0.16842105263157892, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 22:05:29: BoTorchModel, best RESULT: 0.16842105263157892, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 22:05:48: BoTorchModel, best RESULT: 0.16842105263157892, completed/pending 1/1&sum;2 (4%/50), new result: 0.2894736842105263           
2025-05-07 22:06:24: BoTorchModel, best RESULT: 0.16842105263157892, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
2025-05-07 22:06:40: BoTorchModel, best RESULT: 0.16842105263157892, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 22:07:19: BoTorchModel, best RESULT: 0.16842105263157892, completed 1&sum;1 (2%/50), eval start                                         
2025-05-07 22:07:37: BoTorchModel, best RESULT: 0.16842105263157892, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 22:07:55: BoTorchModel, best RESULT: 0.16842105263157892, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 22:08:14: BoTorchModel, best RESULT: 0.16842105263157892, completed/running 1/1&sum;2 (4%/50), new result: 0.30000000000000004          
2025-05-07 22:08:48: BoTorchModel, best RESULT: 0.16842105263157892, completed 1&sum;1 (2%/50), new result: 0.2578947368421053                     
2025-05-07 22:09:30: BoTorchModel, best RESULT: 0.16842105263157892, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 22:09:50: BoTorchModel, best RESULT: 0.16842105263157892, getting new HP set                                                        
2025-05-07 22:10:28: BoTorchModel, best RESULT: 0.16842105263157892, eval start                                                                
2025-05-07 22:10:47: BoTorchModel, best RESULT: 0.16842105263157892, starting new job                                                          
2025-05-07 22:11:06: BoTorchModel, best RESULT: 0.16842105263157892, unknown 1&sum;1 (2%/50), started new job                                      
2025-05-07 22:11:52: BoTorchModel, best RESULT: 0.16842105263157892, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 22:12:29: BoTorchModel, best RESULT: 0.16842105263157892, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 22:12:49: BoTorchModel, best RESULT: 0.16842105263157892, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 22:13:09: BoTorchModel, best RESULT: 0.16842105263157892, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 22:13:29: BoTorchModel, best RESULT: 0.16842105263157892, completed/running 1/1&sum;2 (4%/50), new result: 0.26315789473684215          
2025-05-07 22:14:11: BoTorchModel, best RESULT: 0.16842105263157892, completed 1&sum;1 (2%/50), new result: 0.2789473684210526                     
2025-05-07 22:14:51: BoTorchModel, best RESULT: 0.16842105263157892, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 22:15:15: BoTorchModel, best RESULT: 0.16842105263157892, getting new HP set                                                        
2025-05-07 22:16:00: BoTorchModel, best RESULT: 0.16842105263157892, eval start                                                                
2025-05-07 22:16:25: BoTorchModel, best RESULT: 0.16842105263157892, starting new job                                                          
2025-05-07 22:16:50: BoTorchModel, best RESULT: 0.16842105263157892, unknown 1&sum;1 (2%/50), started new job                                      
2025-05-07 22:17:37: BoTorchModel, best RESULT: 0.16842105263157892, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 22:18:14: BoTorchModel, best RESULT: 0.16842105263157892, completed 1&sum;1 (2%/50), eval start                                         
2025-05-07 22:18:32: BoTorchModel, best RESULT: 0.16842105263157892, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 22:18:52: BoTorchModel, best RESULT: 0.16842105263157892, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 22:19:11: BoTorchModel, best RESULT: 0.16842105263157892, completed/running 1/1&sum;2 (4%/50), new result: 0.2947368421052632           
2025-05-07 22:19:49: BoTorchModel, best RESULT: 0.16842105263157892, completed 1&sum;1 (2%/50), new result: 0.3631578947368421                     
2025-05-07 22:20:28: BoTorchModel, best RESULT: 0.16842105263157892, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 22:20:51: BoTorchModel, best RESULT: 0.16842105263157892, getting new HP set                                                        
2025-05-07 22:21:32: BoTorchModel, best RESULT: 0.16842105263157892, eval start                                                                
2025-05-07 22:21:50: BoTorchModel, best RESULT: 0.16842105263157892, starting new job                                                          
2025-05-07 22:22:09: BoTorchModel, best RESULT: 0.16842105263157892, unknown 1&sum;1 (2%/50), started new job                                      
2025-05-07 22:22:47: BoTorchModel, best RESULT: 0.16842105263157892, pending 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 22:23:19: BoTorchModel, best RESULT: 0.16842105263157892, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 22:23:36: BoTorchModel, best RESULT: 0.16842105263157892, running 1&sum;1 (2%/50), starting new job                                     
2025-05-07 22:23:55: BoTorchModel, best RESULT: 0.16842105263157892, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 22:24:13: BoTorchModel, best RESULT: 0.16842105263157892, completed/running 1/1&sum;2 (4%/50), new result: 0.26315789473684215          
2025-05-07 22:24:56: BoTorchModel, best RESULT: 0.16842105263157892, running 1&sum;1 (2%/50), new result: 0.1947368421052632                       
2025-05-07 22:25:42: BoTorchModel, best RESULT: 0.16842105263157892, finishing jobs (_get_next_trials), finished 2 jobs                        
2025-05-07 22:26:01: BoTorchModel, best RESULT: 0.16842105263157892, getting new HP set                                                        
2025-05-07 22:26:40: BoTorchModel, best RESULT: 0.16842105263157892, eval start                                                                
2025-05-07 22:26:58: BoTorchModel, best RESULT: 0.16842105263157892, starting new job                                                          
2025-05-07 22:27:17: BoTorchModel, best RESULT: 0.16842105263157892, unknown 1&sum;1 (2%/50), started new job                                      
2025-05-07 22:27:58: BoTorchModel, best RESULT: 0.16842105263157892, running 1&sum;1 (2%/50), getting new HP set                                   
2025-05-07 22:28:35: BoTorchModel, best RESULT: 0.16842105263157892, running 1&sum;1 (2%/50), eval start                                           
2025-05-07 22:28:56: BoTorchModel, best RESULT: 0.16842105263157892, completed 1&sum;1 (2%/50), starting new job                                   
2025-05-07 22:29:16: BoTorchModel, best RESULT: 0.16842105263157892, completed/unknown 1/1&sum;2 (4%/50), started new job                          
2025-05-07 22:29:35: BoTorchModel, best RESULT: 0.16842105263157892, completed/pending 1/1&sum;2 (4%/50), new result: 0.2684210526315789           
2025-05-07 22:30:19: BoTorchModel, best RESULT: 0.16842105263157892, running 1&sum;1 (2%/50), finishing jobs (_get_next_trials), finished 1 job    
</pre><button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("simple_pre_tab_tab_progressbar_log")'> Copy raw data to clipboard</button>
			<button onclick='download_as_file("simple_pre_tab_tab_progressbar_log", "progressbar")'> Download &raquo;progressbar&laquo; as file</button>
			
			<h1>&nbsp;Args Overview</h1>
			<h2>Arguments Overview:                                                                                           </h2><table cellspacing="0" cellpadding="5"><thead><tr><th> Key</th><th>Value                                                                                                                                                    </th></tr></thead><tbody><tr><td> config_yaml</td><td>None                                                                                                                                                     </td></tr><tr><td> config_toml</td><td>None                                                                                                                                                     </td></tr><tr><td> config_json</td><td>None                                                                                                                                                     </td></tr><tr><td> num_random_steps</td><td>50                                                                                                                                                       </td></tr><tr><td> max_eval</td><td>2000                                                                                                                                                     </td></tr><tr><td> run_program</td><td>[[&#039;YmFzaCAvZGF0YS9ob3JzZS93cy9wd2lua2xlci1vb3B0L3J1bi5zaCAlKGVwb2NocykgJShscikgJShic3opICUoZGEpICUoZGIp&#039;]]                                               </td></tr><tr><td> experiment_name</td><td>vergl_botorch                                                                                                                                            </td></tr><tr><td> mem_gb</td><td>10                                                                                                                                                       </td></tr><tr><td> parameter</td><td>[[&#039;epochs&#039;, &#039;range&#039;, &#039;10&#039;, &#039;200&#039;, &#039;int&#039;, &#039;false&#039;], [&#039;lr&#039;, &#039;range&#039;, &#039;0.0001&#039;, &#039;0.01&#039;, &#039;float&#039;, &#039;false&#039;], [&#039;bsz&#039;, &#039;range&#039;, &#039;4&#039;, &#039;32&#039;, &#039;int&#039;, &#039;false&#039;],     </td></tr><tr><td></td><td>[&#039;da&#039;, &#039;range&#039;, &#039;10&#039;, &#039;100&#039;, &#039;int&#039;, &#039;false&#039;], [&#039;db&#039;, &#039;range&#039;, &#039;10&#039;, &#039;100&#039;, &#039;int&#039;, &#039;false&#039;]]                                                              </td></tr><tr><td> continue_previous_job</td><td>None                                                                                                                                                     </td></tr><tr><td> experiment_constraints</td><td>None                                                                                                                                                     </td></tr><tr><td> run_dir</td><td>runs                                                                                                                                                     </td></tr><tr><td> seed</td><td>None                                                                                                                                                     </td></tr><tr><td> decimalrounding</td><td>4                                                                                                                                                        </td></tr><tr><td> enforce_sequential_optimization</td><td>False                                                                                                                                                    </td></tr><tr><td> verbose_tqdm</td><td>False                                                                                                                                                    </td></tr><tr><td> model</td><td>BOTORCH_MODULAR                                                                                                                                          </td></tr><tr><td> gridsearch</td><td>False                                                                                                                                                    </td></tr><tr><td> occ</td><td>False                                                                                                                                                    </td></tr><tr><td> show_sixel_scatter</td><td>False                                                                                                                                                    </td></tr><tr><td> show_sixel_general</td><td>False                                                                                                                                                    </td></tr><tr><td> show_sixel_trial_index_result</td><td>False                                                                                                                                                    </td></tr><tr><td> follow</td><td>True                                                                                                                                                     </td></tr><tr><td> send_anonymized_usage_stats</td><td>True                                                                                                                                                     </td></tr><tr><td> ui_url</td><td>aHR0cHM6Ly9pbWFnZXNlZy5zY2Fkcy5kZS9vbW5pYXgvZ3VpP3BhcnRpdGlvbj1iYXJuYXJkJmV4cGVyaW1lbnRfbmFtZT12ZXJnbF9ib3RvcmNoJnJlc2VydmF0aW9uPSZhY2NvdW50PSZtZW1fZ2I&hellip; </td></tr><tr><td> root_venv_dir</td><td>/home/pwinkler                                                                                                                                           </td></tr><tr><td> exclude</td><td>None                                                                                                                                                     </td></tr><tr><td> main_process_gb</td><td>8                                                                                                                                                        </td></tr><tr><td> pareto_front_confidence</td><td>1.0                                                                                                                                                      </td></tr><tr><td> max_nr_of_zero_results</td><td>50                                                                                                                                                       </td></tr><tr><td> abbreviate_job_names</td><td>False                                                                                                                                                    </td></tr><tr><td> orchestrator_file</td><td>None                                                                                                                                                     </td></tr><tr><td> checkout_to_latest_tested_version</td><td>True                                                                                                                                                     </td></tr><tr><td> live_share</td><td>True                                                                                                                                                     </td></tr><tr><td> disable_tqdm</td><td>False                                                                                                                                                    </td></tr><tr><td> workdir</td><td></td></tr><tr><td> occ_type</td><td>euclid                                                                                                                                                   </td></tr><tr><td> result_names</td><td>[&#039;RESULT=min&#039;]                                                                                                                                           </td></tr><tr><td> minkowski_p</td><td>2                                                                                                                                                        </td></tr><tr><td> signed_weighted_euclidean_weights</td><td></td></tr><tr><td> generation_strategy</td><td>None                                                                                                                                                     </td></tr><tr><td> generate_all_jobs_at_once</td><td>False                                                                                                                                                    </td></tr><tr><td> revert_to_random_when_seemingly_exhausted</td><td>True                                                                                                                                                     </td></tr><tr><td> load_data_from_existing_jobs</td><td>[]                                                                                                                                                       </td></tr><tr><td> n_estimators_randomforest</td><td>100                                                                                                                                                      </td></tr><tr><td> external_generator</td><td>None                                                                                                                                                     </td></tr><tr><td> username</td><td>None                                                                                                                                                     </td></tr><tr><td> max_failed_jobs</td><td>0                                                                                                                                                        </td></tr><tr><td> num_parallel_jobs</td><td>50                                                                                                                                                       </td></tr><tr><td> worker_timeout</td><td>30                                                                                                                                                       </td></tr><tr><td> slurm_use_srun</td><td>False                                                                                                                                                    </td></tr><tr><td> time</td><td>600                                                                                                                                                      </td></tr><tr><td> partition</td><td>barnard                                                                                                                                                  </td></tr><tr><td> reservation</td><td>None                                                                                                                                                     </td></tr><tr><td> force_local_execution</td><td>False                                                                                                                                                    </td></tr><tr><td> slurm_signal_delay_s</td><td>0                                                                                                                                                        </td></tr><tr><td> nodes_per_job</td><td>1                                                                                                                                                        </td></tr><tr><td> cpus_per_task</td><td>1                                                                                                                                                        </td></tr><tr><td> account</td><td>None                                                                                                                                                     </td></tr><tr><td> gpus</td><td>0                                                                                                                                                        </td></tr><tr><td> run_mode</td><td>local                                                                                                                                                    </td></tr><tr><td> verbose</td><td>False                                                                                                                                                    </td></tr><tr><td> verbose_break_run_search_table</td><td>False                                                                                                                                                    </td></tr><tr><td> debug</td><td>False                                                                                                                                                    </td></tr><tr><td> no_sleep</td><td>False                                                                                                                                                    </td></tr><tr><td> tests</td><td>False                                                                                                                                                    </td></tr><tr><td> show_worker_percentage_table_at_end</td><td>False                                                                                                                                                    </td></tr><tr><td> auto_exclude_defective_hosts</td><td>False                                                                                                                                                    </td></tr><tr><td> run_tests_that_fail_on_taurus</td><td>False                                                                                                                                                    </td></tr><tr><td> raise_in_eval</td><td>False                                                                                                                                                    </td></tr><tr><td> show_ram_every_n_seconds</td><td>0                                                                                                                                                        </td></tr></tbody></table>
			<h1>&nbsp;Worker-Usage</h1>
			<div class='invert_in_dark_mode' id='workerUsagePlot'></div><button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("pre_tab_worker_usage")'> Copy raw data to clipboard</button>
			<button onclick='download_as_file("pre_tab_worker_usage", "worker_usage.csv")'> Download &raquo;worker_usage.csv&laquo; as file</button>
<pre id="pre_tab_worker_usage">1746613821.807602,50,0,0
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1746613849.3623512,50,1,2
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1746613860.5341938,50,2,4
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1746613871.3357224,50,3,6
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1746613925.1977894,50,3,6
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1746641627.0421312,50,2,4
1746641640.3303297,50,2,4
1746641668.8402352,50,1,2
1746641682.0620067,50,1,2
1746641705.9967773,50,1,2
1746641718.5785136,50,1,2
1746641732.6930344,50,2,4
1746641746.638529,50,2,4
1746641774.686307,50,1,2
1746641801.483104,50,0,0
1746641813.7512176,50,0,0
1746641839.2133725,50,0,0
1746641851.747104,50,0,0
1746641865.4785116,50,1,2
1746641892.255127,50,1,2
1746641914.9190874,50,1,2
1746641927.4870288,50,1,2
1746641941.8973906,50,2,4
1746641954.8773177,50,2,4
1746641982.94445,50,1,2
1746641995.6345265,50,1,2
1746642019.1739876,50,1,2
1746642032.0117126,50,1,2
1746642045.6162596,50,2,4
1746642058.4603631,50,2,4
1746642086.0302975,50,1,2
1746642098.2220986,50,1,2
1746642124.5755022,50,1,2
1746642137.1282518,50,1,2
1746642150.8921235,50,2,4
1746642164.6664867,50,2,4
1746642195.387503,50,1,2
1746642222.4105945,50,0,0
1746642234.4719024,50,0,0
1746642260.9513946,50,0,0
1746642278.4942555,50,0,0
1746642293.1163225,50,1,2
1746642321.833162,50,1,2
1746642345.3567567,50,1,2
1746642358.2796054,50,1,2
1746642371.8893387,50,2,4
1746642384.7955399,50,2,4
1746642413.2137654,50,1,2
1746642425.6531017,50,1,2
1746642449.637084,50,1,2
1746642462.4033742,50,1,2
1746642476.8966622,50,2,4
1746642507.7988167,50,2,4
1746642532.208064,50,2,4
1746642544.9513242,50,2,4
1746642559.631669,50,3,6
1746642593.6477408,50,3,6
1746642617.395843,50,3,6
1746642630.4623418,50,3,6
1746642645.2899709,50,4,8
</pre><button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("pre_tab_worker_usage")'> Copy raw data to clipboard</button>
			<button onclick='download_as_file("pre_tab_worker_usage", "worker_usage.csv")'> Download &raquo;worker_usage.csv&laquo; as file</button>
			
			<h1>&nbsp;CPU/RAM-Usage (main)</h1>
			<div class='invert_in_dark_mode' id='mainWorkerCPURAM'></div><button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("pre_tab_main_worker_cpu_ram")'> Copy raw data to clipboard</button>
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<pre id="pre_tab_main_worker_cpu_ram">timestamp,ram_usage_mb,cpu_usage_percent
1746613817,622.0859375,14.0
1746613821,622.34375,14.0
1746613824,622.34375,14.0
1746613824,622.34375,16.7
1746613824,622.34375,13.3
1746613824,622.34375,13.6
1746613824,622.34375,16.7
1746615675,647.9921875,14.1
1746615675,647.9921875,14.1
1746615675,647.9921875,14.6
1746615675,647.9921875,13.0
1746619675,708.21875,12.8
1746619675,708.21875,7.2
1746619675,708.21875,7.5
1746619675,708.21875,3.8
1746628462,726.45703125,7.7
1746628462,726.45703125,9.1
1746628462,726.45703125,8.7
1746628462,726.45703125,13.3
1746633243,752.13671875,11.6
1746633243,752.13671875,17.4
1746633243,752.13671875,21.1
1746633243,752.13671875,21.7
1746637730,765.0546875,20.4
1746637730,765.0546875,21.2
1746637730,765.0546875,23.5
1746637730,765.0546875,23.3
1746642681,786.328125,18.1
1746642681,786.328125,15.4
1746642681,786.328125,16.7
1746642681,786.328125,17.4
</pre><button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("pre_tab_main_worker_cpu_ram")'> Copy raw data to clipboard</button>
			<button onclick='download_as_file("pre_tab_main_worker_cpu_ram", "cpu_ram_usage.csv")'> Download &raquo;cpu_ram_usage.csv&laquo; as file</button>
			
			<h1>&nbsp;Parallel Plot</h1>
			<div class="invert_in_dark_mode" id="parallel-plot"></div>
			<h1>&nbsp;Scatter-2D</h1>
			<div class='invert_in_dark_mode' id='plotScatter2d'></div>
			<h1>&nbsp;Scatter-3D</h1>
			<div class='invert_in_dark_mode' id='plotScatter3d'></div>
			<h1>&nbsp;Results by Generation Method</h1>
			<div class="invert_in_dark_mode" id="plotResultsDistributionByGenerationMethod"></div>
			<h1>&nbsp;Job Status Distribution</h1>
			<div class="invert_in_dark_mode" id="plotJobStatusDistribution"></div>
			<h1>&nbsp;Boxplots</h1>
			<div class="invert_in_dark_mode" id="plotBoxplot"></div>
			<h1>&nbsp;Violin</h1>
			<div class="invert_in_dark_mode" id="plotViolin"></div>
			<h1>&nbsp;Histogram</h1>
			<div class="invert_in_dark_mode" id="plotHistogram"></div>
			<h1>&nbsp;Heatmap</h1>
			<div class="invert_in_dark_mode" id="plotHeatmap"></div><br>
			    <h1>Correlation Heatmap Explanation</h1>
			
			    <p>
			        This is a heatmap that visualizes the correlation between numerical columns in a dataset. The values represented in the heatmap show the strength and direction of relationships between different variables.
			    </p>
			
			    <h2>How It Works</h2>
			    <p>
			        The heatmap uses a matrix to represent correlations between each pair of numerical columns. The calculation behind this is based on the concept of "correlation," which measures how strongly two variables are related. A correlation can be positive, negative, or zero:
			    </p>
			    <ul>
			        <li><strong>Positive correlation</strong>: Both variables increase or decrease together (e.g., if the temperature rises, ice cream sales increase).</li>
			        <li><strong>Negative correlation</strong>: As one variable increases, the other decreases (e.g., as the price of a product rises, the demand for it decreases).</li>
			        <li><strong>Zero correlation</strong>: There is no relationship between the two variables (e.g., height and shoe size might show zero correlation in some contexts).</li>
			    </ul>
			
			    <h2>Color Scale: Yellow to Purple (Viridis)</h2>
			    <p>
			        The heatmap uses a color scale called "Viridis," which ranges from yellow to purple. Here's what the colors represent:
			    </p>
			    <ul>
			        <li><strong>Yellow (brightest)</strong>: A strong positive correlation (close to +1). This indicates that as one variable increases, the other increases in a very predictable manner.</li>
			        <li><strong>Green</strong>: A moderate positive correlation. Variables are still positively related, but the relationship is not as strong.</li>
			        <li><strong>Blue</strong>: A weak or near-zero correlation. There is a small or no discernible relationship between the variables.</li>
			        <li><strong>Purple (darkest)</strong>: A strong negative correlation (close to -1). This indicates that as one variable increases, the other decreases in a very predictable manner.</li>
			    </ul>
			
			    <h2>What the Heatmap Shows</h2>
			    <p>
			        In the heatmap, each cell represents the correlation between two numerical columns. The color of the cell is determined by the correlation coefficient: from yellow for strong positive correlations, through green and blue for weaker correlations, to purple for strong negative correlations.
			    </p>
			
			<h1>&nbsp;Evolution</h1>
			<div class="invert_in_dark_mode" id="plotResultEvolution"></div>
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