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,0.215789473684210530990412735264,182,0.004086844545602799118333425810,5,15,85
1,1_0,COMPLETED,Sobol,SOBOL,0.357894736842105265495206367632,93,0.005281418676208705746677463111,20,87,29
2,2_0,COMPLETED,Sobol,SOBOL,0.373684210526315840894540087902,47,0.001921856395900249647734625569,16,50,53
3,3_0,COMPLETED,Sobol,SOBOL,0.278947368421052610543142691313,149,0.008066364510636777132579489091,31,76,64
4,4_0,COMPLETED,Sobol,SOBOL,0.436842105263157920447270043951,114,0.000270663183648139264812076954,22,65,74
5,5_0,COMPLETED,Sobol,SOBOL,0.289473684210526327476031838160,13,0.009015402867831289954181350765,7,39,40
6,6_0,COMPLETED,Sobol,SOBOL,0.342105263157894690095872647362,76,0.003055609608162194578556691837,25,98,18
7,7_0,COMPLETED,Sobol,SOBOL,0.221052631578947389456857308687,166,0.006850415381975472409181726618,11,27,99
8,8_0,COMPLETED,Sobol,SOBOL,0.305263157894736791853063095914,155,0.002123264156468212659339966919,28,33,22
9,9_0,COMPLETED,Sobol,SOBOL,0.278947368421052610543142691313,65,0.008402737917471677156489029414,14,59,78
10,10_0,COMPLETED,Sobol,SOBOL,0.478947368421052677156524168822,27,0.004908276228047908293361523135,25,22,60
11,11_0,COMPLETED,Sobol,SOBOL,0.278947368421052610543142691313,129,0.006237683899421245757588305736,10,93,49
12,12_0,COMPLETED,Sobol,SOBOL,0.352631578947368407028761794209,136,0.003469326064269989944727212716,16,81,33
13,13_0,COMPLETED,Sobol,SOBOL,0.389473684210526305271571345656,34,0.007129166191816331196728917519,30,10,68
14,14_0,COMPLETED,Sobol,SOBOL,0.342105263157894690095872647362,103,0.001304272636305541009996145085,5,70,95
15,15_0,COMPLETED,Sobol,SOBOL,0.300000000000000044408920985006,192,0.009914178853482008210717957297,19,44,14
16,16_0,COMPLETED,Sobol,SOBOL,0.336842105263157942651730536454,199,0.000824830826744437370715012925,13,97,63
17,17_0,COMPLETED,Sobol,SOBOL,0.257894736842105287699666860135,97,0.009395421993639321150970644680,28,32,51
18,18_0,COMPLETED,Sobol,SOBOL,0.300000000000000044408920985006,40,0.003608634402230382134946218287,10,63,30
19,19_0,COMPLETED,Sobol,SOBOL,0.310526315789473650319507669337,129,0.007229159479495138665439135650,24,43,88
20,20_0,COMPLETED,Sobol,SOBOL,0.352631578947368407028761794209,122,0.004501324065867812196373165534,30,54,97
21,21_0,COMPLETED,Sobol,SOBOL,0.310526315789473650319507669337,32,0.005791419010423124943964801048,15,74,18
22,22_0,COMPLETED,Sobol,SOBOL,0.363157894736842123961650941055,60,0.002335062141809612391851747049,19,20,42
23,23_0,COMPLETED,Sobol,SOBOL,0.231578947368421106389746455534,161,0.008575223175995051738684793463,4,86,75
24,24_0,COMPLETED,Sobol,SOBOL,0.326315789473684225718841389607,171,0.002651093154959380596147333620,21,68,44
25,25_0,COMPLETED,Sobol,SOBOL,0.268421052631578893610253544466,70,0.006406586238835007898750895095,7,48,56
26,26_0,COMPLETED,Sobol,SOBOL,0.342105263157894690095872647362,19,0.000484896582923829554557376698,32,80,83
27,27_0,COMPLETED,Sobol,SOBOL,0.273684210526315752076698117889,109,0.009190323577169329932745611700,18,15,25
28,28_0,COMPLETED,Sobol,SOBOL,0.284210526315789469009587264736,144,0.001435144597943872326814562790,8,26,10
29,29_0,COMPLETED,Sobol,SOBOL,0.357894736842105265495206367632,54,0.007540337625518441985739137579,23,92,89
30,30_0,COMPLETED,Sobol,SOBOL,0.294736842105263185942476411583,86,0.004218882526364178126021542425,12,37,71
31,31_0,COMPLETED,Sobol,SOBOL,0.294736842105263185942476411583,187,0.005374141643568874221470466068,26,57,37
32,32_0,COMPLETED,Sobol,SOBOL,0.384210526315789446805126772233,184,0.001757793323975056533348126919,25,85,99
33,33_0,COMPLETED,Sobol,SOBOL,0.205263157894736814057523588417,83,0.007843690539896489011262303848,10,19,20
34,34_0,COMPLETED,Sobol,SOBOL,0.352631578947368407028761794209,57,0.003922780809830874945709489054,28,72,39
35,35_0,COMPLETED,Sobol,SOBOL,0.284210526315789469009587264736,147,0.005058744115382433209626711346,14,52,72
36,36_0,COMPLETED,Sobol,SOBOL,0.289473684210526327476031838160,106,0.002949573803134262692249301097,5,41,66
37,37_0,COMPLETED,Sobol,SOBOL,0.363157894736842123961650941055,17,0.006724438229668886456147358643,19,61,54
38,38_0,COMPLETED,Sobol,SOBOL,0.473684210526315818690079595399,73,0.000164627968706190601615863001,16,31,27
39,39_0,COMPLETED,Sobol,SOBOL,0.315789473684210508785952242761,174,0.008889426305610686682157073335,30,96,84
40,40_0,COMPLETED,Sobol,SOBOL,0.321052631578947367252396816184,164,0.004802222148794681524930361149,17,55,14
41,41_0,COMPLETED,Sobol,SOBOL,0.394736842105263163738015919080,63,0.006111688436008990733816492735,31,36,93
42,42_0,COMPLETED,Sobol,SOBOL,0.378947368421052588338682198810,29,0.002017209487129002776217845394,6,90,68
43,43_0,COMPLETED,Sobol,SOBOL,0.326315789473684225718841389607,119,0.008276741863973438584345387881,21,25,35
44,44_0,COMPLETED,Sobol,SOBOL,0.300000000000000044408920985006,133,0.001140227838605642344052548687,26,13,47
45,45_0,COMPLETED,Sobol,SOBOL,0.226315789473684247923301882111,42,0.009691523193847388292776479091,12,79,59
46,46_0,COMPLETED,Sobol,SOBOL,0.336842105263157942651730536454,94,0.003305281856656074827155444851,22,47,80
47,47_0,COMPLETED,Sobol,SOBOL,0.247368421052631570766777713288,195,0.006906511122267693959797529857,8,67,23
48,48_0,COMPLETED,Sobol,SOBOL,0.331578947368421084185285963031,189,0.003792012777086347513622044403,32,28,78
49,49_0,COMPLETED,Sobol,SOBOL,0.300000000000000044408920985006,99,0.007432481561973691870648384139,18,99,43
50,50_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,133,0.008577504456510273711522529538,9,21,14
51,51_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.284210526315789469009587264736,121,0.009818272291073204885436531697,10,86,12
52,52_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.263157894736842146166111433558,142,0.007137340016123906727418813034,7,10,42
53,53_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.210526315789473672523968161840,125,0.009744594475476721015527736824,9,32,18
54,54_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,166,0.006950327656025007821982697465,4,14,84
55,55_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.226315789473684247923301882111,139,0.008798112083856104645440687761,7,11,69
56,56_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.342105263157894690095872647362,120,0.010000000000000000208166817117,10,100,83
57,57_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,48,0.010000000000000000208166817117,12,75,12
58,58_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,79,0.009258267750248419525327392421,9,91,22
59,59_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.226315789473684247923301882111,196,0.005556302825780697236812688544,9,12,88
60,60_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.231578947368421106389746455534,103,0.010000000000000000208166817117,10,10,40
61,61_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.284210526315789469009587264736,160,0.008001981087390761318567378169,6,13,35
62,62_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,125,0.008515341535115643692432918499,8,56,12
63,63_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.252631578947368429233222286712,116,0.009648653744496277218090085626,9,65,29
64,64_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.252631578947368429233222286712,116,0.010000000000000000208166817117,10,50,56
65,65_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.284210526315789469009587264736,114,0.009279508125766304169057541174,9,97,36
66,66_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.221052631578947389456857308687,187,0.005193540037535490302977869703,6,15,12
67,67_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.231578947368421106389746455534,116,0.008813640999560575992055611039,9,50,15
68,68_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.300000000000000044408920985006,68,0.010000000000000000208166817117,12,32,20
69,69_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.221052631578947389456857308687,112,0.009008066003247780853535608969,10,10,12
70,70_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,99,0.010000000000000000208166817117,8,95,34
71,71_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,175,0.008982729676910994331962001525,6,37,13
72,72_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,96,0.010000000000000000208166817117,10,63,12
73,73_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.315789473684210508785952242761,26,0.010000000000000000208166817117,15,90,20
74,74_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.315789473684210508785952242761,138,0.009313386529547548059460027048,8,54,49
75,75_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.194736842105263208146936904086,166,0.009214396673853866501224807450,9,12,12
76,76_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.221052631578947389456857308687,163,0.009546552301604260479250818605,9,76,94
77,77_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.368421052631578982428095514479,147,0.006954417456552954360238238962,4,14,21
78,78_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.215789473684210530990412735264,74,0.009640987831256973145110933388,10,25,47
79,79_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.226315789473684247923301882111,126,0.009737317249339197400281875616,9,59,35
80,80_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.278947368421052610543142691313,134,0.010000000000000000208166817117,11,77,22
81,81_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,136,0.009714152980487143068666355816,7,94,38
82,82_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.252631578947368429233222286712,130,0.005989085553031035791260450196,7,17,10
83,83_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,93,0.008907503300410438487610953473,10,95,11
84,84_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,155,0.009489672677845194248558158279,8,90,68
85,85_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,133,0.007919025068734422342919820892,5,31,10
86,86_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.263157894736842146166111433558,170,0.007093616379362981637368701371,9,11,11
87,87_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.357894736842105265495206367632,145,0.010000000000000000208166817117,8,13,26
88,88_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,198,0.008744131195503632852927822228,6,11,96
89,89_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,158,0.010000000000000000208166817117,9,54,16
90,90_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,165,0.009780347900098872171437136558,10,31,94
91,91_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.199999999999999955591079014994,165,0.010000000000000000208166817117,10,21,61
92,92_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,125,0.008824063502547264264963544633,5,34,14
93,93_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.415789473684210486581491750258,17,0.010000000000000000208166817117,14,27,23
94,94_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.357894736842105265495206367632,76,0.010000000000000000208166817117,6,90,84
95,95_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.199999999999999955591079014994,180,0.001943773273209835165953318636,4,15,80
96,96_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,90,0.010000000000000000208166817117,11,43,37
97,97_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.236842105263157853833888566442,136,0.009872329444681192042732043035,9,35,80
98,98_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.347368421052631548562317220785,100,0.010000000000000000208166817117,9,63,82
99,99_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.352631578947368407028761794209,147,0.008498460640559984610731270038,4,10,55
100,100_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.357894736842105265495206367632,128,0.007328165143666878940387210406,11,10,48
101,101_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.305263157894736791853063095914,199,0.003580058943620138735969282706,7,34,66
102,102_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.289473684210526327476031838160,173,0.007354887547036352904439304723,12,13,42
103,103_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.289473684210526327476031838160,196,0.000680550022858143798323848905,5,10,63
104,104_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.263157894736842146166111433558,190,0.005528909705012396806622643197,9,70,71
105,105_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.305263157894736791853063095914,189,0.003570749819384346195744184271,9,13,52
106,106_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.231578947368421106389746455534,196,0.003750095933055425188179521356,5,82,77
107,107_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.221052631578947389456857308687,141,0.008569652555526699813648328075,13,14,54
108,108_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.236842105263157853833888566442,198,0.003852011714893742531234943627,9,10,44
109,109_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.321052631578947367252396816184,65,0.007063617445149230310297294722,10,13,69
110,110_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.300000000000000044408920985006,200,0.005628487729766808340958750279,7,95,95
111,111_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.336842105263157942651730536454,200,0.001300815900408056578763105193,4,42,35
112,112_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,186,0.006164225392213050838674526233,6,85,95
113,113_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.305263157894736791853063095914,198,0.006288258460588526214951610172,9,92,71
114,114_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.373684210526315840894540087902,199,0.000905037362874354183416014674,5,43,68
115,115_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.278947368421052610543142691313,165,0.008388896327259951629651268945,13,39,60
116,116_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.294736842105263185942476411583,167,0.010000000000000000208166817117,30,14,29
117,117_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.352631578947368407028761794209,138,0.003544362072843388992982038843,9,10,92
118,118_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.273684210526315752076698117889,191,0.007007867855856318196894338968,13,19,64
119,119_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,138,0.010000000000000000208166817117,27,78,18
120,120_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.336842105263157942651730536454,121,0.005714763782904381389515791057,10,10,68
121,121_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,144,0.006895473797321891723521858353,12,11,33
122,122_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.294736842105263185942476411583,164,0.010000000000000000208166817117,27,43,24
123,123_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.310526315789473650319507669337,194,0.003040045886165567909364959576,6,64,37
124,124_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.231578947368421106389746455534,195,0.010000000000000000208166817117,27,76,34
125,125_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.310526315789473650319507669337,190,0.002120316804501299907254052712,9,12,96
126,126_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.326315789473684225718841389607,191,0.000100000000000000004792173602,5,14,77
127,127_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.273684210526315752076698117889,180,0.005267571433207468567516684743,9,40,53
128,128_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.315789473684210508785952242761,115,0.007758164796308052169049318536,12,10,46
129,129_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.342105263157894690095872647362,170,0.003762872988497674344582355488,9,27,77
130,130_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.236842105263157853833888566442,190,0.007947880364360022237280034574,12,36,44
131,131_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.321052631578947367252396816184,192,0.004951282663584587878657927718,9,42,65
132,132_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.226315789473684247923301882111,198,0.003896030035410551640301379805,6,36,65
133,133_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.231578947368421106389746455534,149,0.007881764468139451987327426252,13,55,36
134,134_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.326315789473684225718841389607,168,0.009222464332006793247265008517,28,25,75
135,135_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.257894736842105287699666860135,196,0.003806215445926703928175571789,6,89,50
136,136_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,191,0.007021442597610894065240927375,9,58,71
137,137_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,191,0.007128999541857151608925668995,12,18,24
138,138_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.305263157894736791853063095914,182,0.008026985369642108958387893836,12,46,33
139,139_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.257894736842105287699666860135,194,0.003306135577411622398363855169,6,78,59
140,140_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.273684210526315752076698117889,182,0.004323422961681195123007093173,6,85,70
141,141_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.273684210526315752076698117889,141,0.007719074453487567190335116862,13,19,62
142,142_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,144,0.010000000000000000208166817117,31,72,15
143,143_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.342105263157894690095872647362,193,0.000857345903600753383132226926,9,20,82
144,144_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.300000000000000044408920985006,188,0.001281827816867635522549151439,9,27,85
145,145_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.289473684210526327476031838160,178,0.005897926953008805067701914027,11,57,57
146,146_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.252631578947368429233222286712,158,0.005338181538748697566032497264,10,10,64
147,147_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.278947368421052610543142691313,197,0.003731141318260021520064606548,8,29,95
148,148_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.273684210526315752076698117889,106,0.010000000000000000208166817117,30,17,21
149,149_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,136,0.009874131838474345043699109681,26,69,39
150,150_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.194736842105263208146936904086,200,0.010000000000000000208166817117,15,10,100
151,151_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.210526315789473672523968161840,200,0.010000000000000000208166817117,15,13,34
152,152_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.305263157894736791853063095914,138,0.010000000000000000208166817117,15,12,95
153,153_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.231578947368421106389746455534,192,0.010000000000000000208166817117,16,100,100
154,154_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.300000000000000044408920985006,196,0.007730263524140227986147788641,13,96,25
155,155_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.463157894736842101757190448552,200,0.000100000000000000004792173602,32,10,10
156,156_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.378947368421052588338682198810,200,0.000100000000000000004792173602,32,100,10
157,157_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.315789473684210508785952242761,177,0.001313545503326270583177581841,32,52,23
158,158_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,198,0.008014373080690435219297640401,12,20,93
159,159_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.305263157894736791853063095914,191,0.001608538467685494350103980743,31,96,68
160,160_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.310526315789473650319507669337,199,0.010000000000000000208166817117,20,20,78
161,161_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.278947368421052610543142691313,171,0.010000000000000000208166817117,13,16,100
162,162_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.389473684210526305271571345656,42,0.000100000000000000004792173602,32,59,46
163,163_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.310526315789473650319507669337,198,0.004294366743974310958453788345,30,90,20
164,164_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.357894736842105265495206367632,159,0.006007570117257618816375419613,28,31,81
165,165_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,193,0.010000000000000000208166817117,32,10,97
166,166_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.326315789473684225718841389607,180,0.001543628383647337870554494543,31,48,12
167,167_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.405263157894736880670905065926,112,0.000100000000000000004792173602,32,77,26
168,168_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.284210526315789469009587264736,199,0.008903408070860379872057954742,16,53,70
169,169_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,98,0.000100000000000000004792173602,32,88,10
170,170_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.394736842105263163738015919080,61,0.002675672718157655338711009563,32,91,11
171,171_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.205263157894736814057523588417,194,0.009483950817449808903814023608,14,49,85
172,172_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.478947368421052677156524168822,194,0.003112244397367996701780912261,31,48,62
173,173_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.326315789473684225718841389607,144,0.002241743597017828437678588216,31,25,25
174,174_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.352631578947368407028761794209,192,0.008198805150044939996090143097,18,14,13
175,175_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.331578947368421084185285963031,122,0.002513119276252127800436175775,28,23,35
176,176_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.294736842105263185942476411583,132,0.000629139444783942771745322009,30,33,20
177,177_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.294736842105263185942476411583,195,0.010000000000000000208166817117,13,87,80
178,178_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.357894736842105265495206367632,192,0.008371381953704055620124613313,15,11,25
179,179_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.357894736842105265495206367632,184,0.002241882606741776775421959300,30,56,34
180,180_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.278947368421052610543142691313,136,0.002320195776518194519938420584,27,13,26
181,181_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,172,0.001147543717954733642414022476,31,74,14
182,182_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.389473684210526305271571345656,180,0.005813898878096229044798448626,28,14,92
183,183_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.205263157894736814057523588417,95,0.005906303250325943034193532100,7,13,99
184,184_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.215789473684210530990412735264,199,0.008103652102722510436327851835,12,14,24
185,185_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.252631578947368429233222286712,195,0.007648087627267045190970762292,14,92,92
186,186_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.273684210526315752076698117889,173,0.005238454956395250348977210564,29,14,70
187,187_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.268421052631578893610253544466,159,0.001032169478795734061590816388,32,25,14
188,188_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.342105263157894690095872647362,172,0.002377266684934614508761807627,30,55,16
189,189_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.305263157894736791853063095914,191,0.007451484272620452660451650928,32,60,24
190,190_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.368421052631578982428095514479,120,0.000815032302419993167144629531,32,42,25
191,191_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.215789473684210530990412735264,200,0.007960593673277541540422852506,28,20,74
192,192_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.315789473684210508785952242761,182,0.006262168295360940814542338728,31,51,58
193,193_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.347368421052631548562317220785,185,0.001676929286724987032061728875,30,27,12
194,194_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.315789473684210508785952242761,200,0.004849079563059101143085438679,10,48,11
195,195_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,149,0.005553668164979486988885870602,25,39,81
196,196_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.352631578947368407028761794209,158,0.000699616396771418147873533577,25,96,79
197,197_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.231578947368421106389746455534,198,0.007649381166543604664009858851,19,28,79
198,198_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.300000000000000044408920985006,196,0.001348557631808395542924450261,30,59,13
199,199_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.347368421052631548562317220785,186,0.007058599013385699269540474177,30,81,90
200,200_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.368421052631578982428095514479,78,0.010000000000000000208166817117,4,10,100
201,201_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.300000000000000044408920985006,92,0.010000000000000000208166817117,13,10,100
202,202_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.252631578947368429233222286712,196,0.010000000000000000208166817117,4,100,100
203,203_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,74,0.010000000000000000208166817117,4,12,42
204,204_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,67,0.007996080402047250554331547789,4,10,81
205,205_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.189473684210526349680492330663,169,0.006708814873979875893772462092,4,100,100
206,206_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.305263157894736791853063095914,164,0.002169413565395823719622603321,4,100,100
207,207_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.257894736842105287699666860135,200,0.010000000000000000208166817117,11,50,100
208,208_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,90,0.010000000000000000208166817117,4,10,70
209,209_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,79,0.010000000000000000208166817117,4,10,10
210,210_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,200,0.009749012337050041998587346370,4,59,22
211,211_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.357894736842105265495206367632,82,0.010000000000000000208166817117,13,10,59
212,212_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,83,0.010000000000000000208166817117,8,10,25
213,213_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,200,0.010000000000000000208166817117,4,55,95
214,214_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.336842105263157942651730536454,72,0.009472401634708067438839229624,5,16,81
215,215_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.357894736842105265495206367632,78,0.007481519651620194277796827009,4,11,12
216,216_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.226315789473684247923301882111,93,0.010000000000000000208166817117,15,14,57
217,217_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,64,0.010000000000000000208166817117,4,11,51
218,218_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,96,0.009694800616111378874228954317,16,19,87
219,219_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.336842105263157942651730536454,10,0.010000000000000000208166817117,4,100,69
220,220_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,54,0.010000000000000000208166817117,4,14,100
221,221_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.236842105263157853833888566442,46,0.009440972924177703715087339731,4,24,80
222,222_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.321052631578947367252396816184,175,0.010000000000000000208166817117,15,95,95
223,223_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.331578947368421084185285963031,17,0.010000000000000000208166817117,6,95,54
224,224_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.347368421052631548562317220785,94,0.009343742192117206191159795026,10,19,95
225,225_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.347368421052631548562317220785,70,0.008955403214434798711551799499,18,14,64
226,226_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.278947368421052610543142691313,164,0.007264409825752541315091459495,13,94,98
227,227_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.357894736842105265495206367632,28,0.010000000000000000208166817117,24,98,27
228,228_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.231578947368421106389746455534,178,0.010000000000000000208166817117,7,98,57
229,229_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.226315789473684247923301882111,69,0.010000000000000000208166817117,17,15,79
230,230_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.263157894736842146166111433558,140,0.005010466861507650686291537312,6,92,87
231,231_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,41,0.010000000000000000208166817117,4,41,32
232,232_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.342105263157894690095872647362,17,0.007055760108174730788066497666,4,95,62
233,233_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.284210526315789469009587264736,99,0.009194321504287672475186354859,12,20,83
234,234_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.284210526315789469009587264736,67,0.003364656865678123959934042730,6,93,79
235,235_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,52,0.005685192655278845444422053390,5,98,85
236,236_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.221052631578947389456857308687,200,0.010000000000000000208166817117,11,100,64
237,237_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.305263157894736791853063095914,12,0.010000000000000000208166817117,4,49,73
238,238_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,121,0.010000000000000000208166817117,14,16,100
239,239_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.305263157894736791853063095914,100,0.010000000000000000208166817117,23,26,83
240,240_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.215789473684210530990412735264,198,0.007731675252046769225566791306,6,45,94
241,241_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.305263157894736791853063095914,86,0.010000000000000000208166817117,22,19,91
242,242_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.336842105263157942651730536454,51,0.010000000000000000208166817117,5,20,64
243,243_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,200,0.010000000000000000208166817117,9,34,32
244,244_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.331578947368421084185285963031,71,0.009280344521994299614164880552,10,14,89
245,245_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,27,0.010000000000000000208166817117,4,51,90
246,246_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.231578947368421106389746455534,87,0.006955764471627999372127515443,5,25,35
247,247_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.357894736842105265495206367632,79,0.009402314477485483601437721290,20,13,84
248,248_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.236842105263157853833888566442,19,0.008174287507179699846515674722,9,96,94
249,249_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.199999999999999955591079014994,87,0.008685049338473319058273602877,12,16,100
250,250_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.199999999999999955591079014994,200,0.007291676439191521232052739521,9,10,100
251,251_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.268421052631578893610253544466,200,0.007929985518306420858025695964,10,59,95
252,252_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.284210526315789469009587264736,199,0.008195248509410299128652432898,10,76,100
253,253_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,193,0.007931655319971116571697855591,11,90,74
254,254_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.263157894736842146166111433558,193,0.009594192945999061722384126938,11,22,96
255,255_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.205263157894736814057523588417,200,0.007055811264348119289657734754,9,77,100
256,256_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.357894736842105265495206367632,200,0.010000000000000000208166817117,12,10,72
257,257_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.263157894736842146166111433558,200,0.010000000000000000208166817117,12,93,100
258,258_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.336842105263157942651730536454,200,0.005425183743495280187796314664,4,100,100
259,259_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.221052631578947389456857308687,200,0.008440358256238074396993198434,10,17,89
260,260_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,168,0.006826646227095431451736828876,7,85,100
261,261_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.257894736842105287699666860135,200,0.008151733417899107228543620352,12,85,97
262,262_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.410526315789473739137349639350,55,0.000100000000000000004792173602,4,76,12
263,263_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.263157894736842146166111433558,200,0.010000000000000000208166817117,22,20,95
264,264_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.184210526315789491214047757239,189,0.006015229369388397882845165299,7,14,66
265,265_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.226315789473684247923301882111,195,0.003128322759995349425926614018,4,90,28
266,266_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.347368421052631548562317220785,200,0.010000000000000000208166817117,11,10,100
267,267_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.294736842105263185942476411583,196,0.010000000000000000208166817117,15,58,32
268,268_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.205263157894736814057523588417,199,0.007625260542159143992146930202,22,12,17
269,269_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.257894736842105287699666860135,195,0.010000000000000000208166817117,25,47,98
270,270_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,198,0.006201190276445331557575446624,6,31,93
271,271_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,195,0.008296187054131350449570625472,24,100,17
272,272_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.226315789473684247923301882111,200,0.006883295264170376757950631230,10,77,99
273,273_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.231578947368421106389746455534,192,0.007434520055481418088216827300,7,77,99
274,274_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.194736842105263208146936904086,197,0.008846428018668237025501355220,17,31,56
275,275_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.284210526315789469009587264736,199,0.010000000000000000208166817117,21,47,98
276,276_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.252631578947368429233222286712,198,0.008938719527158999964000507532,21,94,92
277,277_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,197,0.010000000000000000208166817117,16,85,22
278,278_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.305263157894736791853063095914,200,0.007962235188536335647735420196,9,96,100
279,279_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.305263157894736791853063095914,194,0.008734301063598860423442538092,25,16,18
280,280_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.221052631578947389456857308687,175,0.008487945627539824136609247773,27,77,31
281,281_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.284210526315789469009587264736,200,0.009537737592372700495824133782,19,78,83
282,282_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.326315789473684225718841389607,117,0.002561336279059253564355236321,4,18,100
283,283_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.252631578947368429233222286712,199,0.010000000000000000208166817117,23,79,28
284,284_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.284210526315789469009587264736,179,0.003390113275396877332013012563,4,59,18
285,285_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.205263157894736814057523588417,198,0.010000000000000000208166817117,27,11,11
286,286_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.305263157894736791853063095914,175,0.009349272459615030547719349840,26,97,49
287,287_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.347368421052631548562317220785,36,0.005056488906256526895399705523,9,12,12
288,288_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.252631578947368429233222286712,191,0.009836560025212250091275478781,27,21,57
289,289_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,187,0.008391866727533774106273511961,10,12,90
290,290_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.215789473684210530990412735264,199,0.008772779087706203057783760357,13,16,76
291,291_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.210526315789473672523968161840,199,0.010000000000000000208166817117,25,20,49
292,292_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.321052631578947367252396816184,170,0.007863181618209195977708958480,27,98,32
293,293_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.257894736842105287699666860135,187,0.007664264830929409973159227576,25,63,37
294,294_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,188,0.008505773835092489409959171098,23,28,22
295,295_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.289473684210526327476031838160,199,0.008127769768451859402902393015,15,11,69
296,296_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.289473684210526327476031838160,136,0.008573263979629782913227664665,26,93,26
297,297_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.357894736842105265495206367632,184,0.008766550644958560206676523308,12,18,68
298,298_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.263157894736842146166111433558,198,0.006391300842046437717669515877,4,37,95
299,299_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,193,0.008208469928146253785650188206,27,47,11
300,300_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.357894736842105265495206367632,200,0.010000000000000000208166817117,23,10,41
301,301_0,RUNNING,BoTorch,BOTORCH_MODULAR,,191,0.008690228343366133631486825095,16,13,99
302,302_0,RUNNING,BoTorch,BOTORCH_MODULAR,,151,0.008214996255335754726800701064,11,88,99
303,303_0,RUNNING,BoTorch,BOTORCH_MODULAR,,200,0.007200959901677950018850093983,13,47,100
304,304_0,RUNNING,BoTorch,BOTORCH_MODULAR,,200,0.005081474352885096898435612900,6,94,11
305,305_0,RUNNING,BoTorch,BOTORCH_MODULAR,,200,0.004392889949584495752621382536,4,82,27
306,306_0,RUNNING,BoTorch,BOTORCH_MODULAR,,200,0.004433710192649271963905022176,4,15,72
307,307_0,RUNNING,BoTorch,BOTORCH_MODULAR,,193,0.006026825322515550267810091611,10,96,90
308,308_0,RUNNING,BoTorch,BOTORCH_MODULAR,,200,0.010000000000000000208166817117,23,10,10
309,309_0,RUNNING,BoTorch,BOTORCH_MODULAR,,197,0.005826684793629684049054429096,8,59,60
310,310_0,RUNNING,BoTorch,BOTORCH_MODULAR,,137,0.006825591395611478248706127658,10,94,99
311,311_0,RUNNING,BoTorch,BOTORCH_MODULAR,,199,0.005738844622553738485104535272,8,14,21
312,312_0,RUNNING,BoTorch,BOTORCH_MODULAR,,26,0.006196918380796844622038221928,9,24,90
313,313_0,RUNNING,BoTorch,BOTORCH_MODULAR,,170,0.006861978646614732592345919926,9,86,100
314,314_0,RUNNING,BoTorch,BOTORCH_MODULAR,,197,0.010000000000000000208166817117,32,10,44
315,315_0,RUNNING,BoTorch,BOTORCH_MODULAR,,91,0.010000000000000000208166817117,15,74,100
316,316_0,RUNNING,BoTorch,BOTORCH_MODULAR,,200,0.006487832008299583910759800176,8,94,100
317,317_0,RUNNING,BoTorch,BOTORCH_MODULAR,,189,0.006594452433289561994744776285,18,31,28
318,318_0,RUNNING,BoTorch,BOTORCH_MODULAR,,184,0.008788193223409001067492063441,28,11,17
319,319_0,RUNNING,BoTorch,BOTORCH_MODULAR,,185,0.009706456536513294319767908291,19,12,100
320,320_0,RUNNING,BoTorch,BOTORCH_MODULAR,,179,0.010000000000000000208166817117,32,95,10
321,321_0,RUNNING,BoTorch,BOTORCH_MODULAR,,124,0.007660351672229673974934271996,10,19,88
322,322_0,RUNNING,BoTorch,BOTORCH_MODULAR,,199,0.007697847625975125750164007599,19,33,97
323,323_0,RUNNING,BoTorch,BOTORCH_MODULAR,,189,0.007080508871516897825837411062,11,17,98
324,324_0,RUNNING,BoTorch,BOTORCH_MODULAR,,195,0.006347464730234357935256817029,11,98,91
325,325_0,RUNNING,BoTorch,BOTORCH_MODULAR,,152,0.007053687018213984465109245292,9,40,98
326,326_0,RUNNING,BoTorch,BOTORCH_MODULAR,,196,0.006733822685616534450825376723,8,12,36
327,327_0,RUNNING,BoTorch,BOTORCH_MODULAR,,200,0.005330177068560809118535903650,4,11,92
328,328_0,RUNNING,BoTorch,BOTORCH_MODULAR,,167,0.007082479005346094258488420792,10,96,90
329,329_0,RUNNING,BoTorch,BOTORCH_MODULAR,,192,0.008223181018541025899537544319,22,10,75
330,330_0,RUNNING,BoTorch,BOTORCH_MODULAR,,181,0.007530052111167856790374663944,13,10,100
331,331_0,RUNNING,BoTorch,BOTORCH_MODULAR,,197,0.005755042939312985175726034015,23,11,18
332,332_0,RUNNING,BoTorch,BOTORCH_MODULAR,,198,0.008448069330515475122700408406,22,16,88
333,333_0,RUNNING,BoTorch,BOTORCH_MODULAR,,192,0.006854246695185100927971699747,11,95,24
334,334_0,RUNNING,BoTorch,BOTORCH_MODULAR,,198,0.006760587303112118931491814067,9,99,68
335,335_0,RUNNING,BoTorch,BOTORCH_MODULAR,,191,0.009999002156982919609085058710,31,37,44
336,336_0,RUNNING,BoTorch,BOTORCH_MODULAR,,191,0.006767322079922043903676964760,11,10,67
337,337_0,RUNNING,BoTorch,BOTORCH_MODULAR,,200,0.009130179879195661138413520064,24,100,19
338,338_0,RUNNING,BoTorch,BOTORCH_MODULAR,,198,0.010000000000000000208166817117,19,19,20
339,339_0,RUNNING,BoTorch,BOTORCH_MODULAR,,199,0.006120715678959642511158811828,9,36,94
340,340_0,RUNNING,BoTorch,BOTORCH_MODULAR,,166,0.006052328243896887977060217167,9,51,100
341,341_0,RUNNING,BoTorch,BOTORCH_MODULAR,,199,0.007480037307678853025771914531,19,10,63
342,342_0,RUNNING,BoTorch,BOTORCH_MODULAR,,134,0.006649065335040425968327060247,13,94,98
343,343_0,RUNNING,BoTorch,BOTORCH_MODULAR,,171,0.006060800778925073614700202995,6,88,41
344,344_0,RUNNING,BoTorch,BOTORCH_MODULAR,,199,0.007390091014643066814893135330,10,13,78
345,345_0,RUNNING,BoTorch,BOTORCH_MODULAR,,172,0.005118832947024146845516057169,5,16,95
346,346_0,RUNNING,BoTorch,BOTORCH_MODULAR,,196,0.006318060363255504144341934136,14,10,77
347,347_0,RUNNING,BoTorch,BOTORCH_MODULAR,,200,0.003110382722629966793098654776,4,88,76
348,348_0,RUNNING,BoTorch,BOTORCH_MODULAR,,160,0.007329839398934116095896129650,16,15,33
349,349_0,RUNNING,BoTorch,BOTORCH_MODULAR,,152,0.007336594368444059217904129611,9,97,87

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start_time,end_time,run_time,program_string,epochs,lr,bsz,da,db,RESULT,exit_code,signal,hostname,OO_Info_SLURM_JOB_ID
1746533719,1746533811,92,bash /data/horse/ws/pwinkler-oopt/run.sh 93 0.005281418676208706 20 87 29,93,0.005281418676208706,20,87,29,0.35789473684210527,0,None,n1719,16897993
1746533775,1746533812,37,bash /data/horse/ws/pwinkler-oopt/run.sh 114 0.00027066318364813926 22 65 74,114,0.00027066318364813926,22,65,74,0.4368421052631579,0,None,n1719,16898020
1746533775,1746533812,37,bash /data/horse/ws/pwinkler-oopt/run.sh 13 0.00901540286783129 7 39 40,13,0.00901540286783129,7,39,40,0.2894736842105263,0,None,n1719,16898021
1746533715,1746533813,98,bash /data/horse/ws/pwinkler-oopt/run.sh 47 0.0019218563959002496 16 50 53,47,0.0019218563959002496,16,50,53,0.37368421052631584,0,None,n1719,16897996
1746533747,1746533814,67,bash /data/horse/ws/pwinkler-oopt/run.sh 149 0.008066364510636777 31 76 64,149,0.008066364510636777,31,76,64,0.2789473684210526,0,None,n1719,16898009
1746533684,1746533825,141,bash /data/horse/ws/pwinkler-oopt/run.sh 182 0.004086844545602799 5 15 85,182,0.004086844545602799,5,15,85,0.21578947368421053,0,None,n1719,16897981
1746533806,1746533830,24,bash /data/horse/ws/pwinkler-oopt/run.sh 76 0.0030556096081621946 25 98 18,76,0.0030556096081621946,25,98,18,0.3421052631578947,0,None,n1719,16898033
1746533834,1746533859,25,bash /data/horse/ws/pwinkler-oopt/run.sh 155 0.0021232641564682127 28 33 22,155,0.0021232641564682127,28,33,22,0.3052631578947368,0,None,n1719,16898045
1746533834,1746533871,37,bash /data/horse/ws/pwinkler-oopt/run.sh 166 0.006850415381975472 11 27 99,166,0.006850415381975472,11,27,99,0.2210526315789474,0,None,n1719,16898044
1746533871,1746533889,18,bash /data/horse/ws/pwinkler-oopt/run.sh 27 0.004908276228047908 25 22 60,27,0.004908276228047908,25,22,60,0.4789473684210527,0,None,n1719,16898059
1746533867,1746533891,24,bash /data/horse/ws/pwinkler-oopt/run.sh 65 0.008402737917471677 14 59 78,65,0.008402737917471677,14,59,78,0.2789473684210526,0,None,n1719,16898056
1746533898,1746533923,25,bash /data/horse/ws/pwinkler-oopt/run.sh 136 0.00346932606426999 16 81 33,136,0.00346932606426999,16,81,33,0.3526315789473684,0,None,n1719,16898072
1746533898,1746533929,31,bash /data/horse/ws/pwinkler-oopt/run.sh 129 0.006237683899421246 10 93 49,129,0.006237683899421246,10,93,49,0.2789473684210526,0,None,n1719,16898070
1746533957,1746534000,43,bash /data/horse/ws/pwinkler-oopt/run.sh 192 0.009914178853482008 19 44 14,192,0.009914178853482008,19,44,14,0.30000000000000004,0,None,n1719,16898097
1746533940,1746534001,61,bash /data/horse/ws/pwinkler-oopt/run.sh 34 0.007129166191816331 30 10 68,34,0.007129166191816331,30,10,68,0.3894736842105263,0,None,n1714,16898083
1746533957,1746534006,49,bash /data/horse/ws/pwinkler-oopt/run.sh 103 0.001304272636305541 5 70 95,103,0.001304272636305541,5,70,95,0.3421052631578947,0,None,n1719,16898095
1746533989,1746534013,24,bash /data/horse/ws/pwinkler-oopt/run.sh 199 0.0008248308267444374 13 97 63,199,0.0008248308267444374,13,97,63,0.33684210526315794,0,None,n1719,16898108
1746534050,1746534081,31,bash /data/horse/ws/pwinkler-oopt/run.sh 129 0.007229159479495139 24 43 88,129,0.007229159479495139,24,43,88,0.31052631578947365,0,None,n1719,16898133
1746534050,1746534087,37,bash /data/horse/ws/pwinkler-oopt/run.sh 40 0.003608634402230382 10 63 30,40,0.003608634402230382,10,63,30,0.30000000000000004,0,None,n1719,16898131
1746534079,1746534103,24,bash /data/horse/ws/pwinkler-oopt/run.sh 122 0.004501324065867812 30 54 97,122,0.004501324065867812,30,54,97,0.3526315789473684,0,None,n1719,16898161
1746534034,1746534108,74,bash /data/horse/ws/pwinkler-oopt/run.sh 97 0.009395421993639321 28 32 51,97,0.009395421993639321,28,32,51,0.2578947368421053,0,None,n1720,16898119
1746534084,1746534109,25,bash /data/horse/ws/pwinkler-oopt/run.sh 32 0.005791419010423125 15 74 18,32,0.005791419010423125,15,74,18,0.31052631578947365,0,None,n1719,16898176
1746534114,1746534138,24,bash /data/horse/ws/pwinkler-oopt/run.sh 60 0.0023350621418096124 19 20 42,60,0.0023350621418096124,19,20,42,0.3631578947368421,0,None,n1720,16898202
1746534144,1746534163,19,bash /data/horse/ws/pwinkler-oopt/run.sh 171 0.0026510931549593806 21 68 44,171,0.0026510931549593806,21,68,44,0.3263157894736842,0,None,n1719,16898215
1746534140,1746534177,37,bash /data/horse/ws/pwinkler-oopt/run.sh 161 0.008575223175995052 4 86 75,161,0.008575223175995052,4,86,75,0.2315789473684211,0,None,n1719,16898214
1746534169,1746534187,18,bash /data/horse/ws/pwinkler-oopt/run.sh 19 0.00048489658292382955 32 80 83,19,0.00048489658292382955,32,80,83,0.3421052631578947,0,None,n1719,16898228
1746534173,1746534192,19,bash /data/horse/ws/pwinkler-oopt/run.sh 70 0.006406586238835008 7 48 56,70,0.006406586238835008,7,48,56,0.2684210526315789,0,None,n1719,16898227
1746534201,1746534226,25,bash /data/horse/ws/pwinkler-oopt/run.sh 109 0.00919032357716933 18 15 25,109,0.00919032357716933,18,15,25,0.27368421052631575,0,None,n1719,16898242
1746534206,1746534231,25,bash /data/horse/ws/pwinkler-oopt/run.sh 144 0.0014351445979438723 8 26 10,144,0.0014351445979438723,8,26,10,0.28421052631578947,0,None,n1719,16898246
1746534230,1746534249,19,bash /data/horse/ws/pwinkler-oopt/run.sh 54 0.007540337625518442 23 92 89,54,0.007540337625518442,23,92,89,0.35789473684210527,0,None,n1719,16898257
1746534261,1746534286,25,bash /data/horse/ws/pwinkler-oopt/run.sh 86 0.004218882526364178 12 37 71,86,0.004218882526364178,12,37,71,0.2947368421052632,0,None,n1719,16898271
1746534266,1746534290,24,bash /data/horse/ws/pwinkler-oopt/run.sh 187 0.005374141643568874 26 57 37,187,0.005374141643568874,26,57,37,0.2947368421052632,0,None,n1719,16898272
1746534290,1746534309,19,bash /data/horse/ws/pwinkler-oopt/run.sh 83 0.007843690539896489 10 19 20,83,0.007843690539896489,10,19,20,0.20526315789473681,0,None,n1719,16898285
1746534296,1746534314,18,bash /data/horse/ws/pwinkler-oopt/run.sh 184 0.0017577933239750565 25 85 99,184,0.0017577933239750565,25,85,99,0.38421052631578945,0,None,n1719,16898283
1746534321,1746534339,18,bash /data/horse/ws/pwinkler-oopt/run.sh 57 0.003922780809830875 28 72 39,57,0.003922780809830875,28,72,39,0.3526315789473684,0,None,n1719,16898295
1746534321,1746534340,19,bash /data/horse/ws/pwinkler-oopt/run.sh 147 0.005058744115382433 14 52 72,147,0.005058744115382433,14,52,72,0.28421052631578947,0,None,n1719,16898297
1746534352,1746534376,24,bash /data/horse/ws/pwinkler-oopt/run.sh 106 0.0029495738031342627 5 41 66,106,0.0029495738031342627,5,41,66,0.2894736842105263,0,None,n1719,16898299
1746534384,1746534402,18,bash /data/horse/ws/pwinkler-oopt/run.sh 17 0.0067244382296688865 19 61 54,17,0.0067244382296688865,19,61,54,0.3631578947368421,0,None,n1719,16898301
1746534389,1746534407,18,bash /data/horse/ws/pwinkler-oopt/run.sh 73 0.0001646279687061906 16 31 27,73,0.0001646279687061906,16,31,27,0.4736842105263158,0,None,n1719,16898303
1746534412,1746534430,18,bash /data/horse/ws/pwinkler-oopt/run.sh 174 0.008889426305610687 30 96 84,174,0.008889426305610687,30,96,84,0.3157894736842105,0,None,n1719,16898304
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1746537131,1746537155,24,bash /data/horse/ws/pwinkler-oopt/run.sh 158 0.01 9 54 16,158,0.01,9,54,16,0.3631578947368421,0,None,n1693,16899189
1746537222,1746537246,24,bash /data/horse/ws/pwinkler-oopt/run.sh 165 0.01 10 21 61,165,0.01,10,21,61,0.19999999999999996,0,None,n1695,16899191
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1746556159,1746556191,32,bash /data/horse/ws/pwinkler-oopt/run.sh 41 0.01 4 41 32,41,0.01,4,41,32,0.3631578947368421,0,None,n1704,16911205
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1746568289,1746568301,12,bash /data/horse/ws/pwinkler-oopt/run.sh 181 0.007530052111167857 13 10 100,181,0.007530052111167857,13,10,100,0.2684210526315789,0,None,n1718,16913207
1746568352,1746568371,19,bash /data/horse/ws/pwinkler-oopt/run.sh 197 0.005755042939312985 23 11 18,197,0.005755042939312985,23,11,18,0.2789473684210526,0,None,n1720,16913222
1746568382,1746568401,19,bash /data/horse/ws/pwinkler-oopt/run.sh 198 0.008448069330515475 22 16 88,198,0.008448069330515475,22,16,88,0.2684210526315789,0,None,n1720,16913229
1746568445,1746568469,24,bash /data/horse/ws/pwinkler-oopt/run.sh 192 0.006854246695185101 11 95 24,192,0.006854246695185101,11,95,24,0.3631578947368421,0,None,n1720,16913231
1746568506,1746568531,25,bash /data/horse/ws/pwinkler-oopt/run.sh 198 0.006760587303112119 9 99 68,198,0.006760587303112119,9,99,68,0.2947368421052632,0,None,n1720,16913298
1746568569,1746568593,24,bash /data/horse/ws/pwinkler-oopt/run.sh 191 0.00999900215698292 31 37 44,191,0.00999900215698292,31,37,44,0.2894736842105263,0,None,n1720,16913353
1746568631,1746568668,37,bash /data/horse/ws/pwinkler-oopt/run.sh 191 0.006767322079922044 11 10 67,191,0.006767322079922044,11,10,67,0.3631578947368421,0,None,n1720,16913517
1746568690,1746568709,19,bash /data/horse/ws/pwinkler-oopt/run.sh 200 0.009130179879195661 24 100 19,200,0.009130179879195661,24,100,19,0.3631578947368421,0,None,n1718,16913547
1746568754,1746568784,30,bash /data/horse/ws/pwinkler-oopt/run.sh 198 0.01 19 19 20,198,0.01,19,19,20,0.2315789473684211,0,None,n1720,16913549
1746568784,1746568821,37,bash /data/horse/ws/pwinkler-oopt/run.sh 199 0.0061207156789596425 9 36 94,199,0.0061207156789596425,9,36,94,0.23684210526315785,0,None,n1720,16913554
1746568847,1746568896,49,bash /data/horse/ws/pwinkler-oopt/run.sh 166 0.006052328243896888 9 51 100,166,0.006052328243896888,9,51,100,0.2421052631578947,0,None,n1720,16913956
1746568910,1746568941,31,bash /data/horse/ws/pwinkler-oopt/run.sh 199 0.007480037307678853 19 10 63,199,0.007480037307678853,19,10,63,0.3631578947368421,0,None,n1720,16913958
1746568970,1746569001,31,bash /data/horse/ws/pwinkler-oopt/run.sh 134 0.006649065335040426 13 94 98,134,0.006649065335040426,13,94,98,0.28421052631578947,0,None,n1720,16913960
1746569032,1746569069,37,bash /data/horse/ws/pwinkler-oopt/run.sh 171 0.006060800778925074 6 88 41,171,0.006060800778925074,6,88,41,0.22631578947368425,0,None,n1720,16913962
1746569093,1746569130,37,bash /data/horse/ws/pwinkler-oopt/run.sh 199 0.007390091014643067 10 13 78,199,0.007390091014643067,10,13,78,0.2210526315789474,0,None,n1720,16913964
1746569154,1746569191,37,bash /data/horse/ws/pwinkler-oopt/run.sh 172 0.005118832947024147 5 16 95,172,0.005118832947024147,5,16,95,0.19999999999999996,0,None,n1720,16913967
1746569216,1746569247,31,bash /data/horse/ws/pwinkler-oopt/run.sh 196 0.006318060363255504 14 10 77,196,0.006318060363255504,14,10,77,0.21578947368421053,0,None,n1720,16913969
1746569278,1746569321,43,bash /data/horse/ws/pwinkler-oopt/run.sh 200 0.003110382722629967 4 88 76,200,0.003110382722629967,4,88,76,0.28421052631578947,0,None,n1720,16913970
1746569341,1746569371,30,bash /data/horse/ws/pwinkler-oopt/run.sh 160 0.007329839398934116 16 15 33,160,0.007329839398934116,16,15,33,0.21578947368421053,0,None,n1720,16913972

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Run-UUID: b652a409-f7ea-41f9-b1b0-41a697a652c4
  _________________________________________________
 /                                                 \
| OmniOpt2 - Tuning like a Jedi: Feel the force of  |
| the optimal values.                               |
 \                                                 /
  =================================================
                                                 \
                                                  \
                                                    ^__^
                                                    (oo)\_______
                                                    (__)\       )\/\
                                                        ||----w |
                                                        ||     ||


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 --generate_all_jobs_at_once --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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

Run-folder: runs/vergl_botorch/4





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=0 for live-results.

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BoTorchModel, best RESULT: 0.1947368421052632, completed 14 = ∑14/50, new result: 0.2421052631578947                     :   7%|▒░░░░░░░░░| 136/2000 3:17:55<25:58:18, 50.16s/it]

Runtime (end): 3 hours 20 minutes and 20 seconds, PID: 1597978
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.
BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 49/1 = ∑50/50, new result: 0.35789473684210527          :  15%|█▒░░░░░░░░| 301/2000 9:59:00<663:01:23, 1404.88s/it]

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2025-05-06 14:11:09: SOBOL, Started OmniOpt2 run...
2025-05-06 14:11:17: SOBOL, getting new HP set #1/50
2025-05-06 14:11:20: Sobol, getting new HP set #2/50 | ETA: 13s
2025-05-06 14:11:23: Sobol, getting new HP set #3/50 | ETA: 11s
2025-05-06 14:11:26: Sobol, getting new HP set #4/50 | ETA: 9s 
2025-05-06 14:11:31: Sobol, getting new HP set #5/50 | ETA: 9s 
2025-05-06 14:11:37: Sobol, getting new HP set #6/50 | ETA: 8s 
2025-05-06 14:11:41: Sobol, getting new HP set #7/50 | ETA: 7s 
2025-05-06 14:11:45: Sobol, getting new HP set #8/50 | ETA: 7s 
2025-05-06 14:11:49: Sobol, getting new HP set #9/50 | ETA: 7s 
2025-05-06 14:11:52: Sobol, getting new HP set #10/50 | ETA: 7s
2025-05-06 14:11:55: Sobol, getting new HP set #11/50 | ETA: 6s
2025-05-06 14:11:59: Sobol, getting new HP set #12/50 | ETA: 6s
2025-05-06 14:12:02: Sobol, getting new HP set #13/50 | ETA: 6s
2025-05-06 14:12:06: Sobol, getting new HP set #14/50 | ETA: 6s
2025-05-06 14:12:09: Sobol, getting new HP set #15/50 | ETA: 5s
2025-05-06 14:12:12: Sobol, getting new HP set #16/50 | ETA: 5s
2025-05-06 14:12:15: Sobol, getting new HP set #17/50 | ETA: 5s
2025-05-06 14:12:19: Sobol, getting new HP set #18/50 | ETA: 5s
2025-05-06 14:12:22: Sobol, getting new HP set #19/50 | ETA: 5s
2025-05-06 14:12:26: Sobol, getting new HP set #20/50 | ETA: 5s
2025-05-06 14:12:30: Sobol, getting new HP set #21/50 | ETA: 4s
2025-05-06 14:12:35: Sobol, getting new HP set #22/50 | ETA: 4s
2025-05-06 14:12:41: Sobol, getting new HP set #23/50 | ETA: 4s
2025-05-06 14:12:44: Sobol, getting new HP set #24/50 | ETA: 4s
2025-05-06 14:12:47: Sobol, getting new HP set #25/50 | ETA: 4s
2025-05-06 14:12:51: Sobol, getting new HP set #26/50 | ETA: 4s
2025-05-06 14:12:54: Sobol, getting new HP set #27/50 | ETA: 3s
2025-05-06 14:12:58: Sobol, getting new HP set #28/50 | ETA: 3s
2025-05-06 14:13:03: Sobol, getting new HP set #29/50 | ETA: 3s
2025-05-06 14:13:06: Sobol, getting new HP set #30/50 | ETA: 3s
2025-05-06 14:13:09: Sobol, getting new HP set #31/50 | ETA: 3s
2025-05-06 14:13:14: Sobol, getting new HP set #32/50 | ETA: 3s
2025-05-06 14:13:18: Sobol, getting new HP set #33/50 | ETA: 3s
2025-05-06 14:13:21: Sobol, getting new HP set #34/50 | ETA: 2s
2025-05-06 14:13:23: Sobol, getting new HP set #35/50 | ETA: 2s
2025-05-06 14:13:26: Sobol, getting new HP set #36/50 | ETA: 2s
2025-05-06 14:13:29: Sobol, getting new HP set #37/50 | ETA: 2s
2025-05-06 14:13:35: Sobol, getting new HP set #38/50 | ETA: 2s
2025-05-06 14:13:41: Sobol, getting new HP set #39/50 | ETA: 2s
2025-05-06 14:13:44: Sobol, getting new HP set #40/50 | ETA: 1s
2025-05-06 14:13:47: Sobol, getting new HP set #41/50 | ETA: 1s
2025-05-06 14:13:51: Sobol, getting new HP set #42/50 | ETA: 1s
2025-05-06 14:13:53: Sobol, getting new HP set #43/50 | ETA: 1s
2025-05-06 14:13:56: Sobol, getting new HP set #44/50 | ETA: 1s
2025-05-06 14:13:59: Sobol, getting new HP set #45/50 | ETA: 1s
2025-05-06 14:14:01: Sobol, getting new HP set #46/50 | ETA: 0s
2025-05-06 14:14:04: Sobol, getting new HP set #47/50 | ETA: 0s
2025-05-06 14:14:07: Sobol, getting new HP set #48/50 | ETA: 0s
2025-05-06 14:14:10: Sobol, getting new HP set #49/50 | ETA: 0s
2025-05-06 14:14:13: Sobol, getting new HP set #50/50 | ETA: 0s
2025-05-06 14:14:17: Sobol, eval start                         
2025-05-06 14:14:22: Sobol, starting new job                   
2025-05-06 14:14:28: Sobol, unknown 1 = ∑1/50, started new job 
2025-05-06 14:14:31: Sobol, pending 1 = ∑1/50, eval start      
2025-05-06 14:14:37: Sobol, pending 1 = ∑1/50, starting new job
2025-05-06 14:14:44: Sobol, running/unknown 1/1 = ∑2/50, started new job
2025-05-06 14:14:50: Sobol, running/pending 1/1 = ∑2/50, eval start     
2025-05-06 14:14:56: Sobol, running/pending 1/1 = ∑2/50, starting new job
2025-05-06 14:15:03: Sobol, running/pending/unknown 1/1/1 = ∑3/50, started new job
2025-05-06 14:15:08: Sobol, running/pending 1/2 = ∑3/50, eval start               
2025-05-06 14:15:16: Sobol, running 3 = ∑3/50, starting new job                   
2025-05-06 14:15:25: Sobol, running/unknown 3/1 = ∑4/50, started new job          
2025-05-06 14:15:31: Sobol, running/pending 3/1 = ∑4/50, eval start               
2025-05-06 14:15:37: Sobol, running/pending 3/1 = ∑4/50, starting new job         
2025-05-06 14:15:48: Sobol, running/unknown 4/1 = ∑5/50, started new job          
2025-05-06 14:15:55: Sobol, running/pending 4/1 = ∑5/50, eval start               
2025-05-06 14:16:00: Sobol, running/pending 4/1 = ∑5/50, starting new job         
2025-05-06 14:16:07: Sobol, running/pending/unknown 4/1/1 = ∑6/50, started new job
2025-05-06 14:16:13: Sobol, running 6 = ∑6/50, eval start                         
2025-05-06 14:16:19: Sobol, running 6 = ∑6/50, starting new job                   
2025-05-06 14:16:26: Sobol, running/unknown 6/1 = ∑7/50, started new job          
2025-05-06 14:16:31: Sobol, running/pending 6/1 = ∑7/50, eval start               
2025-05-06 14:16:37: Sobol, running/pending 6/1 = ∑7/50, starting new job         
2025-05-06 14:16:46: Sobol, running/unknown 7/1 = ∑8/50, started new job          
2025-05-06 14:16:52: Sobol, running/pending 7/1 = ∑8/50, eval start               
2025-05-06 14:16:57: Sobol, running/pending 7/1 = ∑8/50, starting new job         
2025-05-06 14:17:03: Sobol, running/completed/pending/unknown 2/5/1/1 = ∑9/50, started new job
2025-05-06 14:17:07: Sobol, completed/running/pending 6/1/2 = ∑9/50, eval start               
2025-05-06 14:17:12: Sobol, completed/running/pending 6/1/2 = ∑9/50, starting new job         
2025-05-06 14:17:18: Sobol, completed/running/unknown 7/2/1 = ∑10/50, started new job         
2025-05-06 14:17:24: Sobol, completed/running/pending 7/2/1 = ∑10/50, eval start              
2025-05-06 14:17:29: Sobol, completed/running/pending 7/2/1 = ∑10/50, starting new job        
2025-05-06 14:17:35: Sobol, completed/running/pending/unknown 7/2/1/1 = ∑11/50, started new job
2025-05-06 14:17:39: Sobol, completed/running/pending 7/2/2 = ∑11/50, eval start               
2025-05-06 14:17:48: Sobol, completed/running 8/3 = ∑11/50, starting new job                   
2025-05-06 14:17:55: Sobol, completed/running/unknown 9/2/1 = ∑12/50, started new job          
2025-05-06 14:17:59: Sobol, completed/running/pending 9/2/1 = ∑12/50, eval start               
2025-05-06 14:18:05: Sobol, completed/running/pending 9/2/1 = ∑12/50, starting new job         
2025-05-06 14:18:10: Sobol, completed/running/pending/unknown 9/2/1/1 = ∑13/50, started new job
2025-05-06 14:18:19: Sobol, completed/running 11/2 = ∑13/50, eval start                        
2025-05-06 14:18:25: Sobol, completed/running 11/2 = ∑13/50, starting new job                  
2025-05-06 14:18:31: Sobol, completed/running/unknown 11/2/1 = ∑14/50, started new job         
2025-05-06 14:18:37: Sobol, completed/running/pending 11/2/1 = ∑14/50, eval start              
2025-05-06 14:18:43: Sobol, completed/running/pending 11/2/1 = ∑14/50, starting new job        
2025-05-06 14:18:51: Sobol, completed/running/unknown 12/2/1 = ∑15/50, started new job         
2025-05-06 14:18:57: Sobol, completed/running/pending 13/1/1 = ∑15/50, eval start              
2025-05-06 14:19:03: Sobol, completed/running/pending 13/1/1 = ∑15/50, starting new job        
2025-05-06 14:19:10: Sobol, completed/running/pending/unknown 13/1/1/1 = ∑16/50, started new job
2025-05-06 14:19:17: Sobol, completed/running 13/3 = ∑16/50, eval start                         
2025-05-06 14:19:26: Sobol, completed/running 13/3 = ∑16/50, starting new job                   
2025-05-06 14:19:35: Sobol, completed/running/unknown 13/3/1 = ∑17/50, started new job          
2025-05-06 14:19:43: Sobol, completed/running 13/4 = ∑17/50, eval start                         
2025-05-06 14:19:52: Sobol, completed/running 13/4 = ∑17/50, starting new job                   
2025-05-06 14:19:59: Sobol, completed/running/unknown 13/4/1 = ∑18/50, started new job          
2025-05-06 14:20:04: Sobol, completed/running/pending 15/2/1 = ∑18/50, eval start               
2025-05-06 14:20:09: Sobol, completed/running/pending 15/2/1 = ∑18/50, starting new job         
2025-05-06 14:20:15: Sobol, completed/running/unknown 16/2/1 = ∑19/50, started new job          
2025-05-06 14:20:19: Sobol, completed/running/unknown 17/1/1 = ∑19/50, eval start               
2025-05-06 14:20:24: Sobol, completed/running/unknown 17/1/1 = ∑19/50, starting new job         
2025-05-06 14:20:30: Sobol, completed/running/pending/unknown 17/1/1/1 = ∑20/50, started new job
2025-05-06 14:20:35: Sobol, completed/running/pending 17/1/2 = ∑20/50, eval start               
2025-05-06 14:20:41: Sobol, completed/running/pending 17/1/2 = ∑20/50, starting new job         
2025-05-06 14:20:51: Sobol, completed/running/unknown 17/3/1 = ∑21/50, started new job          
2025-05-06 14:20:58: Sobol, completed/running/pending 17/3/1 = ∑21/50, eval start               
2025-05-06 14:21:06: Sobol, completed/running/pending 17/3/1 = ∑21/50, starting new job         
2025-05-06 14:21:13: Sobol, completed/running/pending/unknown 17/3/1/1 = ∑22/50, started new job
2025-05-06 14:21:22: Sobol, completed/running 18/4 = ∑22/50, eval start                         
2025-05-06 14:21:29: Sobol, completed/running 18/4 = ∑22/50, starting new job                   
2025-05-06 14:21:36: Sobol, completed/running/unknown 19/3/1 = ∑23/50, started new job          
2025-05-06 14:21:40: Sobol, completed/running/pending 19/3/1 = ∑23/50, eval start               
2025-05-06 14:21:47: Sobol, completed/running 20/3 = ∑23/50, starting new job                   
2025-05-06 14:21:54: Sobol, completed/running/unknown 22/1/1 = ∑24/50, started new job          
2025-05-06 14:21:58: Sobol, completed/running/pending 22/1/1 = ∑24/50, eval start               
2025-05-06 14:22:01: Sobol, completed/running/pending 22/1/1 = ∑24/50, starting new job         
2025-05-06 14:22:07: Sobol, completed/running/pending/unknown 22/1/1/1 = ∑25/50, started new job
2025-05-06 14:22:10: Sobol, completed/running/pending 22/1/2 = ∑25/50, eval start               
2025-05-06 14:22:14: Sobol, completed/running/pending 22/1/2 = ∑25/50, starting new job         
2025-05-06 14:22:20: Sobol, completed/running/unknown 22/3/1 = ∑26/50, started new job          
2025-05-06 14:22:25: Sobol, completed/running/pending 23/2/1 = ∑26/50, eval start               
2025-05-06 14:22:31: Sobol, completed/running/pending 23/2/1 = ∑26/50, starting new job         
2025-05-06 14:22:38: Sobol, completed/running/pending/unknown 23/2/1/1 = ∑27/50, started new job
2025-05-06 14:22:43: Sobol, completed/running/pending 23/2/2 = ∑27/50, eval start               
2025-05-06 14:22:51: Sobol, completed/running 24/3 = ∑27/50, starting new job                   
2025-05-06 14:22:57: Sobol, completed/running/unknown 24/3/1 = ∑28/50, started new job          
2025-05-06 14:23:02: Sobol, completed/running/pending 25/2/1 = ∑28/50, eval start               
2025-05-06 14:23:06: Sobol, completed/running/pending 25/2/1 = ∑28/50, starting new job         
2025-05-06 14:23:13: Sobol, completed/running/pending/unknown 26/1/1/1 = ∑29/50, started new job
2025-05-06 14:23:19: Sobol, completed/running 27/2 = ∑29/50, eval start                         
2025-05-06 14:23:25: Sobol, completed/running 27/2 = ∑29/50, starting new job                   
2025-05-06 14:23:32: Sobol, completed/running/unknown 27/2/1 = ∑30/50, started new job          
2025-05-06 14:23:37: Sobol, completed/running/pending 27/2/1 = ∑30/50, eval start               
2025-05-06 14:23:43: Sobol, completed/running/pending 27/2/1 = ∑30/50, starting new job         
2025-05-06 14:23:51: Sobol, completed/running/unknown 28/2/1 = ∑31/50, started new job          
2025-05-06 14:23:56: Sobol, completed/running/unknown 29/1/1 = ∑31/50, eval start               
2025-05-06 14:24:00: Sobol, completed/running/unknown 29/1/1 = ∑31/50, starting new job         
2025-05-06 14:24:06: Sobol, completed/running/pending/unknown 29/1/1/1 = ∑32/50, started new job
2025-05-06 14:24:10: Sobol, completed/pending 30/2 = ∑32/50, eval start                         
2025-05-06 14:24:14: Sobol, completed/pending 30/2 = ∑32/50, starting new job                   
2025-05-06 14:24:20: Sobol, completed/running/unknown 30/2/1 = ∑33/50, started new job          
2025-05-06 14:24:25: Sobol, completed/running/pending 30/2/1 = ∑33/50, eval start               
2025-05-06 14:24:31: Sobol, completed/running/pending 30/2/1 = ∑33/50, starting new job         
2025-05-06 14:24:39: Sobol, completed/running/pending/unknown 30/2/1/1 = ∑34/50, started new job
2025-05-06 14:24:46: Sobol, completed/running 30/4 = ∑34/50, eval start                         
2025-05-06 14:24:52: Sobol, completed/running 30/4 = ∑34/50, starting new job                   
2025-05-06 14:24:59: Sobol, completed/running/unknown 32/2/1 = ∑35/50, started new job          
2025-05-06 14:25:04: Sobol, completed/running/pending 32/2/1 = ∑35/50, eval start               
2025-05-06 14:25:10: Sobol, completed/running/pending 32/2/1 = ∑35/50, starting new job         
2025-05-06 14:25:15: Sobol, completed/running/pending/unknown 33/1/1/1 = ∑36/50, started new job
2025-05-06 14:25:20: Sobol, completed/running 34/2 = ∑36/50, eval start                         
2025-05-06 14:25:25: Sobol, completed/running 34/2 = ∑36/50, starting new job                   
2025-05-06 14:25:32: Sobol, completed/running/unknown 34/2/1 = ∑37/50, started new job          
2025-05-06 14:25:37: Sobol, completed/running/pending 34/2/1 = ∑37/50, eval start               
2025-05-06 14:25:44: Sobol, completed/running/pending 34/2/1 = ∑37/50, starting new job         
2025-05-06 14:25:51: Sobol, completed/running/unknown 36/1/1 = ∑38/50, started new job          
2025-05-06 14:25:58: Sobol, completed/running/pending 36/1/1 = ∑38/50, eval start               
2025-05-06 14:26:03: Sobol, completed/running/pending 36/1/1 = ∑38/50, starting new job         
2025-05-06 14:26:09: Sobol, completed/running/pending/unknown 36/1/1/1 = ∑39/50, started new job
2025-05-06 14:26:13: Sobol, completed/running/pending 36/1/2 = ∑39/50, eval start               
2025-05-06 14:26:19: Sobol, completed/running 37/2 = ∑39/50, starting new job                   
2025-05-06 14:26:26: Sobol, completed/running/unknown 37/2/1 = ∑40/50, started new job          
2025-05-06 14:26:32: Sobol, completed/running/pending 37/2/1 = ∑40/50, eval start               
2025-05-06 14:26:37: Sobol, completed/running/pending 37/2/1 = ∑40/50, starting new job         
2025-05-06 14:26:44: Sobol, completed/running/pending/unknown 38/1/1/1 = ∑41/50, started new job
2025-05-06 14:26:49: Sobol, completed/running 39/2 = ∑41/50, eval start                         
2025-05-06 14:26:54: Sobol, completed/running 39/2 = ∑41/50, starting new job                   
2025-05-06 14:27:02: Sobol, completed/running/unknown 39/2/1 = ∑42/50, started new job          
2025-05-06 14:27:07: Sobol, completed/running/pending 39/2/1 = ∑42/50, eval start               
2025-05-06 14:27:12: Sobol, completed/running/pending 39/2/1 = ∑42/50, starting new job         
2025-05-06 14:27:17: Sobol, completed/pending/unknown 41/1/1 = ∑43/50, started new job          
2025-05-06 14:27:23: Sobol, completed/running 41/2 = ∑43/50, eval start                         
2025-05-06 14:27:28: Sobol, completed/running 41/2 = ∑43/50, starting new job                   
2025-05-06 14:27:34: Sobol, completed/running/unknown 41/2/1 = ∑44/50, started new job          
2025-05-06 14:27:40: Sobol, completed/running/pending 41/2/1 = ∑44/50, eval start               
2025-05-06 14:27:45: Sobol, completed/running/pending 41/2/1 = ∑44/50, starting new job         
2025-05-06 14:27:52: Sobol, completed/running/unknown 43/1/1 = ∑45/50, started new job          
2025-05-06 14:27:57: Sobol, completed/running/pending 43/1/1 = ∑45/50, eval start               
2025-05-06 14:28:03: Sobol, completed/running/pending 43/1/1 = ∑45/50, starting new job         
2025-05-06 14:28:09: Sobol, completed/running/pending/unknown 43/1/1/1 = ∑46/50, started new job
2025-05-06 14:28:14: Sobol, completed/running/pending 43/1/2 = ∑46/50, eval start               
2025-05-06 14:28:18: Sobol, completed/running/pending 43/1/2 = ∑46/50, starting new job         
2025-05-06 14:28:25: Sobol, completed/running/unknown 44/2/1 = ∑47/50, started new job          
2025-05-06 14:28:30: Sobol, completed/running/pending 44/2/1 = ∑47/50, eval start               
2025-05-06 14:28:38: Sobol, completed/running/pending 44/2/1 = ∑47/50, starting new job         
2025-05-06 14:28:44: Sobol, completed/pending/unknown 46/1/1 = ∑48/50, started new job          
2025-05-06 14:28:48: Sobol, completed/pending 46/2 = ∑48/50, eval start                         
2025-05-06 14:28:53: Sobol, completed/pending 46/2 = ∑48/50, starting new job                   
2025-05-06 14:29:01: Sobol, completed/running/pending 46/2/1 = ∑49/50, started new job          
2025-05-06 14:29:07: Sobol, completed/running/pending 46/2/1 = ∑49/50, eval start               
2025-05-06 14:29:12: Sobol, completed/running/pending 46/2/1 = ∑49/50, starting new job         
2025-05-06 14:29:18: Sobol, completed/running/pending/unknown 47/1/1/1 = ∑50/50, started new job
2025-05-06 14:29:23: Sobol, completed/running 47/3 = ∑50/50, new result: 0.21578947368421053    
2025-05-06 14:29:41: Sobol, best RESULT: 0.21578947368421053, completed/running 47/2 = ∑49/50, new result: 0.35789473684210527
2025-05-06 14:29:53: Sobol, best RESULT: 0.21578947368421053, completed 48 = ∑48/50, new result: 0.37368421052631584          
2025-05-06 14:30:03: Sobol, best RESULT: 0.21578947368421053, completed 47 = ∑47/50, new result: 0.2789473684210526           
2025-05-06 14:30:12: Sobol, best RESULT: 0.21578947368421053, completed 46 = ∑46/50, new result: 0.4368421052631579           
2025-05-06 14:30:23: Sobol, best RESULT: 0.21578947368421053, completed 45 = ∑45/50, new result: 0.2894736842105263           
2025-05-06 14:30:35: Sobol, best RESULT: 0.21578947368421053, completed 44 = ∑44/50, new result: 0.3421052631578947           
2025-05-06 14:30:47: Sobol, best RESULT: 0.21578947368421053, completed 43 = ∑43/50, new result: 0.2210526315789474           
2025-05-06 14:30:58: Sobol, best RESULT: 0.21578947368421053, completed 42 = ∑42/50, new result: 0.3052631578947368           
2025-05-06 14:31:08: Sobol, best RESULT: 0.21578947368421053, completed 41 = ∑41/50, new result: 0.2789473684210526           
2025-05-06 14:31:17: Sobol, best RESULT: 0.21578947368421053, completed 40 = ∑40/50, new result: 0.4789473684210527           
2025-05-06 14:31:27: Sobol, best RESULT: 0.21578947368421053, completed 39 = ∑39/50, new result: 0.2789473684210526           
2025-05-06 14:31:42: Sobol, best RESULT: 0.21578947368421053, completed 38 = ∑38/50, new result: 0.3526315789473684           
2025-05-06 14:31:58: Sobol, best RESULT: 0.21578947368421053, completed 37 = ∑37/50, new result: 0.3894736842105263           
2025-05-06 14:32:08: Sobol, best RESULT: 0.21578947368421053, completed 36 = ∑36/50, new result: 0.3421052631578947           
2025-05-06 14:32:19: Sobol, best RESULT: 0.21578947368421053, completed 35 = ∑35/50, new result: 0.30000000000000004          
2025-05-06 14:32:33: Sobol, best RESULT: 0.21578947368421053, completed 34 = ∑34/50, new result: 0.33684210526315794          
2025-05-06 14:32:44: Sobol, best RESULT: 0.21578947368421053, completed 33 = ∑33/50, new result: 0.2578947368421053           
2025-05-06 14:32:55: Sobol, best RESULT: 0.21578947368421053, completed 32 = ∑32/50, new result: 0.30000000000000004          
2025-05-06 14:33:08: Sobol, best RESULT: 0.21578947368421053, completed 31 = ∑31/50, new result: 0.31052631578947365          
2025-05-06 14:33:23: Sobol, best RESULT: 0.21578947368421053, completed 30 = ∑30/50, new result: 0.3526315789473684           
2025-05-06 14:33:45: Sobol, best RESULT: 0.21578947368421053, completed 29 = ∑29/50, new result: 0.31052631578947365          
2025-05-06 14:34:01: Sobol, best RESULT: 0.21578947368421053, completed 28 = ∑28/50, new result: 0.3631578947368421           
2025-05-06 14:34:16: Sobol, best RESULT: 0.21578947368421053, completed 27 = ∑27/50, new result: 0.2315789473684211           
2025-05-06 14:34:29: Sobol, best RESULT: 0.21578947368421053, completed 26 = ∑26/50, new result: 0.3263157894736842           
2025-05-06 14:34:40: Sobol, best RESULT: 0.21578947368421053, completed 25 = ∑25/50, new result: 0.2684210526315789           
2025-05-06 14:34:51: Sobol, best RESULT: 0.21578947368421053, completed 24 = ∑24/50, new result: 0.3421052631578947           
2025-05-06 14:35:02: Sobol, best RESULT: 0.21578947368421053, completed 23 = ∑23/50, new result: 0.27368421052631575          
2025-05-06 14:35:13: Sobol, best RESULT: 0.21578947368421053, completed 22 = ∑22/50, new result: 0.28421052631578947          
2025-05-06 14:35:27: Sobol, best RESULT: 0.21578947368421053, completed 21 = ∑21/50, new result: 0.35789473684210527          
2025-05-06 14:35:45: Sobol, best RESULT: 0.21578947368421053, completed 20 = ∑20/50, new result: 0.2947368421052632           
2025-05-06 14:35:56: Sobol, best RESULT: 0.21578947368421053, completed 19 = ∑19/50, new result: 0.2947368421052632           
2025-05-06 14:36:08: Sobol, best RESULT: 0.21578947368421053, completed 18 = ∑18/50, new result: 0.38421052631578945          
2025-05-06 14:36:20: Sobol, best RESULT: 0.21578947368421053, completed 17 = ∑17/50, new result: 0.20526315789473681          
2025-05-06 14:36:35: Sobol, best RESULT: 0.20526315789473681, completed 16 = ∑16/50, new result: 0.3526315789473684           
2025-05-06 14:36:55: Sobol, best RESULT: 0.20526315789473681, completed 15 = ∑15/50, new result: 0.28421052631578947          
2025-05-06 14:37:13: Sobol, best RESULT: 0.20526315789473681, completed 14 = ∑14/50, new result: 0.2894736842105263           
2025-05-06 14:37:33: Sobol, best RESULT: 0.20526315789473681, completed 13 = ∑13/50, new result: 0.3631578947368421           
2025-05-06 14:37:53: Sobol, best RESULT: 0.20526315789473681, completed 12 = ∑12/50, new result: 0.4736842105263158           
2025-05-06 14:38:18: Sobol, best RESULT: 0.20526315789473681, completed 11 = ∑11/50, new result: 0.3157894736842105           
2025-05-06 14:38:41: Sobol, best RESULT: 0.20526315789473681, completed 10 = ∑10/50, new result: 0.32105263157894737          
2025-05-06 14:38:56: Sobol, best RESULT: 0.20526315789473681, completed 9 = ∑9/50, new result: 0.39473684210526316            
2025-05-06 14:39:07: Sobol, best RESULT: 0.20526315789473681, completed 8 = ∑8/50, new result: 0.3789473684210526             
2025-05-06 14:39:19: Sobol, best RESULT: 0.20526315789473681, completed 7 = ∑7/50, new result: 0.3263157894736842             
2025-05-06 14:39:31: Sobol, best RESULT: 0.20526315789473681, completed 6 = ∑6/50, new result: 0.30000000000000004            
2025-05-06 14:39:48: Sobol, best RESULT: 0.20526315789473681, completed 5 = ∑5/50, new result: 0.22631578947368425            
2025-05-06 14:40:00: Sobol, best RESULT: 0.20526315789473681, completed 4 = ∑4/50, new result: 0.33684210526315794            
2025-05-06 14:40:16: Sobol, best RESULT: 0.20526315789473681, completed 3 = ∑3/50, new result: 0.24736842105263157            
2025-05-06 14:40:44: Sobol, best RESULT: 0.20526315789473681, completed 2 = ∑2/50, new result: 0.3315789473684211             
2025-05-06 14:40:59: Sobol, best RESULT: 0.20526315789473681, completed 1 = ∑1/50, new result: 0.30000000000000004            
2025-05-06 14:41:12: Sobol, best RESULT: 0.20526315789473681, finishing jobs, finished 50 jobs                                
2025-05-06 14:41:20: Sobol, best RESULT: 0.20526315789473681, getting new HP set #1/50                                        
2025-05-06 14:41:44: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #2/50 | ETA: 11m 4s                   
2025-05-06 14:41:53: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #3/50 | ETA: 6m 14s                   
2025-05-06 14:42:08: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #4/50 | ETA: 5m 19s                   
2025-05-06 14:42:16: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #5/50 | ETA: 4m 22s                   
2025-05-06 14:42:23: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #6/50 | ETA: 3m 40s                   
2025-05-06 14:42:33: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #7/50 | ETA: 3m 12s                   
2025-05-06 14:42:47: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #8/50 | ETA: 2m 53s                   
2025-05-06 14:42:54: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #9/50 | ETA: 2m 37s                   
2025-05-06 14:43:02: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #10/50 | ETA: 2m 26s                  
2025-05-06 14:43:10: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #11/50 | ETA: 2m 15s                  
2025-05-06 14:43:20: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #12/50 | ETA: 2m 7s                   
2025-05-06 14:43:33: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #13/50 | ETA: 2m 1s                   
2025-05-06 14:43:42: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #14/50 | ETA: 1m 54s                  
2025-05-06 14:43:50: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #15/50 | ETA: 1m 48s                  
2025-05-06 14:43:59: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #16/50 | ETA: 1m 44s                  
2025-05-06 14:44:06: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #17/50 | ETA: 1m 39s                  
2025-05-06 14:44:15: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #18/50 | ETA: 1m 36s                  
2025-05-06 14:44:25: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #19/50 | ETA: 1m 31s                  
2025-05-06 14:44:36: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #20/50 | ETA: 1m 27s                  
2025-05-06 14:44:49: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #21/50 | ETA: 1m 24s                  
2025-05-06 14:44:59: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #22/50 | ETA: 1m 21s                  
2025-05-06 14:45:15: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #23/50 | ETA: 1m 20s                  
2025-05-06 14:45:25: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #24/50 | ETA: 1m 18s                  
2025-05-06 14:45:38: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #25/50 | ETA: 1m 15s                  
2025-05-06 14:45:50: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #26/50 | ETA: 1m 13s                  
2025-05-06 14:46:01: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #27/50 | ETA: 1m 10s                  
2025-05-06 14:46:12: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #28/50 | ETA: 1m 8s                   
2025-05-06 14:46:26: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #29/50 | ETA: 1m 6s                   
2025-05-06 14:46:39: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #30/50 | ETA: 1m 3s                   
2025-05-06 14:46:50: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #31/50 | ETA: 1m 1s                   
2025-05-06 14:47:05: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #32/50 | ETA: 58s                     
2025-05-06 14:47:19: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #33/50 | ETA: 55s                     
2025-05-06 14:47:33: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #34/50 | ETA: 53s                     
2025-05-06 14:47:43: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #35/50 | ETA: 50s                     
2025-05-06 14:47:54: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #36/50 | ETA: 47s                     
2025-05-06 14:48:07: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #37/50 | ETA: 45s                     
2025-05-06 14:48:28: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #38/50 | ETA: 42s                     
2025-05-06 14:48:43: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #39/50 | ETA: 40s                     
2025-05-06 14:48:53: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #40/50 | ETA: 37s                     
2025-05-06 14:49:06: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #41/50 | ETA: 34s                     
2025-05-06 14:49:21: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #42/50 | ETA: 31s                     
2025-05-06 14:49:37: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #43/50 | ETA: 28s                     
2025-05-06 14:49:50: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #44/50 | ETA: 24s                     
2025-05-06 14:50:03: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #45/50 | ETA: 21s                     
2025-05-06 14:50:20: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #46/50 | ETA: 17s                     
2025-05-06 14:50:32: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #47/50 | ETA: 14s                     
2025-05-06 14:50:52: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #48/50 | ETA: 10s                     
2025-05-06 14:51:06: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #49/50 | ETA: 7s                      
2025-05-06 14:51:23: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #50/50 | ETA: 3s                      
2025-05-06 14:51:38: BoTorchModel, best RESULT: 0.20526315789473681, eval start                                               
2025-05-06 14:51:48: BoTorchModel, best RESULT: 0.20526315789473681, starting new job                                         
2025-05-06 14:52:00: BoTorchModel, best RESULT: 0.20526315789473681, unknown 1 = ∑1/50, started new job                       
2025-05-06 14:52:07: BoTorchModel, best RESULT: 0.20526315789473681, pending 1 = ∑1/50, eval start                            
2025-05-06 14:52:24: BoTorchModel, best RESULT: 0.20526315789473681, running 1 = ∑1/50, starting new job                      
2025-05-06 14:52:34: BoTorchModel, best RESULT: 0.20526315789473681, running/unknown 1/1 = ∑2/50, started new job             
2025-05-06 14:52:44: BoTorchModel, best RESULT: 0.20526315789473681, running 2 = ∑2/50, eval start                            
2025-05-06 14:52:54: BoTorchModel, best RESULT: 0.20526315789473681, running 2 = ∑2/50, starting new job                      
2025-05-06 14:53:04: BoTorchModel, best RESULT: 0.20526315789473681, running/unknown 2/1 = ∑3/50, started new job             
2025-05-06 14:53:19: BoTorchModel, best RESULT: 0.20526315789473681, running 3 = ∑3/50, eval start                            
2025-05-06 14:53:31: BoTorchModel, best RESULT: 0.20526315789473681, running 3 = ∑3/50, starting new job                      
2025-05-06 14:53:40: BoTorchModel, best RESULT: 0.20526315789473681, running/unknown 3/1 = ∑4/50, started new job             
2025-05-06 14:53:50: BoTorchModel, best RESULT: 0.20526315789473681, running 4 = ∑4/50, eval start                            
2025-05-06 14:54:08: BoTorchModel, best RESULT: 0.20526315789473681, running/completed 3/1 = ∑4/50, starting new job          
2025-05-06 14:54:21: BoTorchModel, best RESULT: 0.20526315789473681, running/completed/unknown 2/2/1 = ∑5/50, started new job 
2025-05-06 14:54:31: BoTorchModel, best RESULT: 0.20526315789473681, running/completed/pending 2/2/1 = ∑5/50, eval start      
2025-05-06 14:54:40: BoTorchModel, best RESULT: 0.20526315789473681, running/completed/pending 2/2/1 = ∑5/50, starting new job
2025-05-06 14:55:01: BoTorchModel, best RESULT: 0.20526315789473681, running/completed/unknown 3/2/1 = ∑6/50, started new job 
2025-05-06 14:55:29: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 4/2 = ∑6/50, eval start                
2025-05-06 14:55:43: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 4/2 = ∑6/50, starting new job          
2025-05-06 14:55:56: BoTorchModel, best RESULT: 0.20526315789473681, completed/unknown 6/1 = ∑7/50, started new job           
2025-05-06 14:56:15: BoTorchModel, best RESULT: 0.20526315789473681, completed/pending 6/1 = ∑7/50, eval start                
2025-05-06 14:56:29: BoTorchModel, best RESULT: 0.20526315789473681, completed/pending 6/1 = ∑7/50, starting new job          
2025-05-06 14:56:44: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 6/1/1 = ∑8/50, started new job 
2025-05-06 14:56:56: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 7/1 = ∑8/50, eval start                
2025-05-06 14:57:08: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 7/1 = ∑8/50, starting new job          
2025-05-06 14:57:17: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 7/1/1 = ∑9/50, started new job 
2025-05-06 14:57:26: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 8/1 = ∑9/50, eval start                
2025-05-06 14:57:33: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 8/1 = ∑9/50, starting new job          
2025-05-06 14:57:43: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 8/1/1 = ∑10/50, started new job
2025-05-06 14:57:51: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 9/1 = ∑10/50, eval start               
2025-05-06 14:58:02: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 9/1 = ∑10/50, starting new job         
2025-05-06 14:58:12: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 9/1/1 = ∑11/50, started new job
2025-05-06 14:58:19: BoTorchModel, best RESULT: 0.20526315789473681, completed/pending 10/1 = ∑11/50, eval start              
2025-05-06 14:58:26: BoTorchModel, best RESULT: 0.20526315789473681, completed/pending 10/1 = ∑11/50, starting new job        
2025-05-06 14:58:34: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 10/1/1 = ∑12/50, started new job
2025-05-06 14:58:41: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 10/1/1 = ∑12/50, eval start     
2025-05-06 14:58:48: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 10/1/1 = ∑12/50, starting new job
2025-05-06 14:59:00: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 11/1/1 = ∑13/50, started new job 
2025-05-06 14:59:09: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 11/1/1 = ∑13/50, eval start      
2025-05-06 14:59:16: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 11/1/1 = ∑13/50, starting new job
2025-05-06 14:59:25: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 12/1/1 = ∑14/50, started new job 
2025-05-06 14:59:32: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 12/1/1 = ∑14/50, eval start      
2025-05-06 14:59:40: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 12/1/1 = ∑14/50, starting new job
2025-05-06 14:59:48: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending/unknown 12/1/1/1 = ∑15/50, started new job
2025-05-06 14:59:58: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 13/2 = ∑15/50, eval start                         
2025-05-06 15:00:08: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 13/2 = ∑15/50, starting new job                   
2025-05-06 15:00:16: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 13/2/1 = ∑16/50, started new job          
2025-05-06 15:00:24: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 15/1 = ∑16/50, eval start                         
2025-05-06 15:00:36: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 15/1 = ∑16/50, starting new job                   
2025-05-06 15:00:44: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 15/1/1 = ∑17/50, started new job          
2025-05-06 15:00:53: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 16/1 = ∑17/50, eval start                         
2025-05-06 15:01:12: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 16/1 = ∑17/50, starting new job                   
2025-05-06 15:01:22: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 16/1/1 = ∑18/50, started new job          
2025-05-06 15:01:31: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 17/1 = ∑18/50, eval start                         
2025-05-06 15:01:38: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 17/1 = ∑18/50, starting new job                   
2025-05-06 15:01:47: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 17/1/1 = ∑19/50, started new job          
2025-05-06 15:01:56: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 18/1 = ∑19/50, eval start                         
2025-05-06 15:02:03: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 18/1 = ∑19/50, starting new job                   
2025-05-06 15:02:12: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 18/1/1 = ∑20/50, started new job          
2025-05-06 15:02:20: BoTorchModel, best RESULT: 0.20526315789473681, completed/pending 19/1 = ∑20/50, eval start                         
2025-05-06 15:02:26: BoTorchModel, best RESULT: 0.20526315789473681, completed/pending 19/1 = ∑20/50, starting new job                   
2025-05-06 15:02:34: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 19/1/1 = ∑21/50, started new job          
2025-05-06 15:02:40: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 19/1/1 = ∑21/50, eval start               
2025-05-06 15:02:45: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 19/1/1 = ∑21/50, starting new job         
2025-05-06 15:02:55: BoTorchModel, best RESULT: 0.20526315789473681, completed/pending/unknown 20/1/1 = ∑22/50, started new job          
2025-05-06 15:03:03: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 20/1/1 = ∑22/50, eval start               
2025-05-06 15:03:10: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 20/1/1 = ∑22/50, starting new job         
2025-05-06 15:03:19: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending/unknown 20/1/1/1 = ∑23/50, started new job
2025-05-06 15:03:25: BoTorchModel, best RESULT: 0.20526315789473681, completed/pending 21/2 = ∑23/50, eval start                         
2025-05-06 15:03:35: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 21/2 = ∑23/50, starting new job                   
2025-05-06 15:03:45: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 21/2/1 = ∑24/50, started new job          
2025-05-06 15:03:54: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 21/2/1 = ∑24/50, eval start               
2025-05-06 15:04:03: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 21/2/1 = ∑24/50, starting new job         
2025-05-06 15:04:17: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 22/2/1 = ∑25/50, started new job          
2025-05-06 15:04:25: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 22/2/1 = ∑25/50, eval start               
2025-05-06 15:04:32: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 22/2/1 = ∑25/50, starting new job         
2025-05-06 15:04:42: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 22/3/1 = ∑26/50, started new job          
2025-05-06 15:04:53: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 23/2/1 = ∑26/50, eval start               
2025-05-06 15:05:03: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 23/2/1 = ∑26/50, starting new job         
2025-05-06 15:05:14: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 24/2/1 = ∑27/50, started new job          
2025-05-06 15:05:20: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 24/2/1 = ∑27/50, eval start               
2025-05-06 15:05:28: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 24/2/1 = ∑27/50, starting new job         
2025-05-06 15:05:42: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 25/2/1 = ∑28/50, started new job          
2025-05-06 15:05:51: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 26/1/1 = ∑28/50, eval start               
2025-05-06 15:06:00: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 26/1/1 = ∑28/50, starting new job         
2025-05-06 15:06:10: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 27/1/1 = ∑29/50, started new job          
2025-05-06 15:06:17: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 27/1/1 = ∑29/50, eval start               
2025-05-06 15:06:25: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 27/1/1 = ∑29/50, starting new job         
2025-05-06 15:06:34: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 27/2/1 = ∑30/50, started new job          
2025-05-06 15:06:42: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 27/2/1 = ∑30/50, eval start               
2025-05-06 15:06:50: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 27/2/1 = ∑30/50, starting new job         
2025-05-06 15:06:59: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending/unknown 28/1/1/1 = ∑31/50, started new job
2025-05-06 15:07:09: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 28/3 = ∑31/50, eval start                         
2025-05-06 15:07:19: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 28/3 = ∑31/50, starting new job                   
2025-05-06 15:07:28: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 30/1/1 = ∑32/50, started new job          
2025-05-06 15:07:39: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 30/2 = ∑32/50, eval start                         
2025-05-06 15:07:50: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 30/2 = ∑32/50, starting new job                   
2025-05-06 15:08:00: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 31/1/1 = ∑33/50, started new job          
2025-05-06 15:08:09: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 32/1 = ∑33/50, eval start                         
2025-05-06 15:08:17: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 32/1 = ∑33/50, starting new job                   
2025-05-06 15:08:27: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 32/1/1 = ∑34/50, started new job          
2025-05-06 15:08:36: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 32/2 = ∑34/50, eval start                         
2025-05-06 15:08:49: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 32/2 = ∑34/50, starting new job                   
2025-05-06 15:08:59: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 33/1/1 = ∑35/50, started new job          
2025-05-06 15:09:09: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 33/2 = ∑35/50, eval start                         
2025-05-06 15:09:18: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 33/2 = ∑35/50, starting new job                   
2025-05-06 15:09:29: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 34/1/1 = ∑36/50, started new job          
2025-05-06 15:09:39: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 35/1 = ∑36/50, eval start                         
2025-05-06 15:09:50: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 35/1 = ∑36/50, starting new job                   
2025-05-06 15:10:00: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 35/1/1 = ∑37/50, started new job          
2025-05-06 15:10:10: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 36/1 = ∑37/50, eval start                         
2025-05-06 15:10:18: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 36/1 = ∑37/50, starting new job                   
2025-05-06 15:10:29: BoTorchModel, best RESULT: 0.20526315789473681, completed/unknown 37/1 = ∑38/50, started new job                    
2025-05-06 15:10:40: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 37/1 = ∑38/50, eval start                         
2025-05-06 15:10:52: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 37/1 = ∑38/50, starting new job                   
2025-05-06 15:11:06: BoTorchModel, best RESULT: 0.20526315789473681, completed/unknown 38/1 = ∑39/50, started new job                    
2025-05-06 15:11:27: BoTorchModel, best RESULT: 0.20526315789473681, completed/pending 38/1 = ∑39/50, eval start                         
2025-05-06 15:11:43: BoTorchModel, best RESULT: 0.20526315789473681, completed/pending 38/1 = ∑39/50, starting new job                   
2025-05-06 15:12:04: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 38/1/1 = ∑40/50, started new job          
2025-05-06 15:12:21: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 38/2 = ∑40/50, eval start                         
2025-05-06 15:12:30: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 38/2 = ∑40/50, starting new job                   
2025-05-06 15:12:41: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 39/1/1 = ∑41/50, started new job          
2025-05-06 15:12:50: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 39/1/1 = ∑41/50, eval start               
2025-05-06 15:12:59: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 39/1/1 = ∑41/50, starting new job         
2025-05-06 15:13:09: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 39/2/1 = ∑42/50, started new job          
2025-05-06 15:13:19: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 39/2/1 = ∑42/50, eval start               
2025-05-06 15:13:29: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 39/2/1 = ∑42/50, starting new job         
2025-05-06 15:13:42: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 39/3/1 = ∑43/50, started new job          
2025-05-06 15:13:52: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 39/3/1 = ∑43/50, eval start               
2025-05-06 15:14:02: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 39/3/1 = ∑43/50, starting new job         
2025-05-06 15:14:14: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 40/3/1 = ∑44/50, started new job          
2025-05-06 15:14:24: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 40/3/1 = ∑44/50, eval start               
2025-05-06 15:14:34: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 40/3/1 = ∑44/50, starting new job         
2025-05-06 15:14:45: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 41/3/1 = ∑45/50, started new job          
2025-05-06 15:14:55: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 42/2/1 = ∑45/50, eval start               
2025-05-06 15:15:02: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 42/2/1 = ∑45/50, starting new job         
2025-05-06 15:15:11: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending/unknown 43/1/1/1 = ∑46/50, started new job
2025-05-06 15:15:21: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 43/2/1 = ∑46/50, eval start               
2025-05-06 15:15:30: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 43/2/1 = ∑46/50, starting new job         
2025-05-06 15:15:42: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 44/2/1 = ∑47/50, started new job          
2025-05-06 15:15:52: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 44/2/1 = ∑47/50, eval start               
2025-05-06 15:16:01: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 44/2/1 = ∑47/50, starting new job         
2025-05-06 15:16:10: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending/unknown 44/2/1/1 = ∑48/50, started new job
2025-05-06 15:16:18: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 44/4 = ∑48/50, eval start                         
2025-05-06 15:16:28: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 44/4 = ∑48/50, starting new job                   
2025-05-06 15:16:42: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 47/1/1 = ∑49/50, started new job          
2025-05-06 15:16:57: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 47/2 = ∑49/50, eval start                         
2025-05-06 15:17:05: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 47/2 = ∑49/50, starting new job                   
2025-05-06 15:17:16: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 48/1/1 = ∑50/50, started new job          
2025-05-06 15:17:33: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 48/1/1 = ∑50/50, new result: 0.3631578947368421
2025-05-06 15:18:00: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 47/2 = ∑49/50, new result: 0.28421052631578947         
2025-05-06 15:18:23: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 46/2 = ∑48/50, new result: 0.26315789473684215         
2025-05-06 15:18:46: BoTorchModel, best RESULT: 0.20526315789473681, completed 47 = ∑47/50, new result: 0.21052631578947367                   
2025-05-06 15:19:08: BoTorchModel, best RESULT: 0.20526315789473681, completed 46 = ∑46/50, new result: 0.3631578947368421                    
2025-05-06 15:19:26: BoTorchModel, best RESULT: 0.20526315789473681, completed 45 = ∑45/50, new result: 0.22631578947368425                   
2025-05-06 15:19:53: BoTorchModel, best RESULT: 0.20526315789473681, completed 44 = ∑44/50, new result: 0.3421052631578947                    
2025-05-06 15:20:10: BoTorchModel, best RESULT: 0.20526315789473681, completed 43 = ∑43/50, new result: 0.3631578947368421                    
2025-05-06 15:20:28: BoTorchModel, best RESULT: 0.20526315789473681, completed 42 = ∑42/50, new result: 0.3631578947368421                    
2025-05-06 15:20:48: BoTorchModel, best RESULT: 0.20526315789473681, completed 41 = ∑41/50, new result: 0.22631578947368425                   
2025-05-06 15:21:10: BoTorchModel, best RESULT: 0.20526315789473681, completed 40 = ∑40/50, new result: 0.2315789473684211                    
2025-05-06 15:21:27: BoTorchModel, best RESULT: 0.20526315789473681, completed 39 = ∑39/50, new result: 0.28421052631578947                   
2025-05-06 15:21:47: BoTorchModel, best RESULT: 0.20526315789473681, completed 38 = ∑38/50, new result: 0.3631578947368421                    
2025-05-06 15:22:04: BoTorchModel, best RESULT: 0.20526315789473681, completed 37 = ∑37/50, new result: 0.25263157894736843                   
2025-05-06 15:22:20: BoTorchModel, best RESULT: 0.20526315789473681, completed 36 = ∑36/50, new result: 0.25263157894736843                   
2025-05-06 15:22:38: BoTorchModel, best RESULT: 0.20526315789473681, completed 35 = ∑35/50, new result: 0.28421052631578947                   
2025-05-06 15:22:53: BoTorchModel, best RESULT: 0.20526315789473681, completed 34 = ∑34/50, new result: 0.2210526315789474                    
2025-05-06 15:23:10: BoTorchModel, best RESULT: 0.20526315789473681, completed 33 = ∑33/50, new result: 0.2315789473684211                    
2025-05-06 15:23:29: BoTorchModel, best RESULT: 0.20526315789473681, completed 32 = ∑32/50, new result: 0.30000000000000004                   
2025-05-06 15:23:46: BoTorchModel, best RESULT: 0.20526315789473681, completed 31 = ∑31/50, new result: 0.2210526315789474                    
2025-05-06 15:24:04: BoTorchModel, best RESULT: 0.20526315789473681, completed 30 = ∑30/50, new result: 0.3631578947368421                    
2025-05-06 15:24:23: BoTorchModel, best RESULT: 0.20526315789473681, completed 29 = ∑29/50, new result: 0.3631578947368421                    
2025-05-06 15:24:43: BoTorchModel, best RESULT: 0.20526315789473681, completed 28 = ∑28/50, new result: 0.3631578947368421                    
2025-05-06 15:24:59: BoTorchModel, best RESULT: 0.20526315789473681, completed 27 = ∑27/50, new result: 0.3157894736842105                    
2025-05-06 15:25:19: BoTorchModel, best RESULT: 0.20526315789473681, completed 26 = ∑26/50, new result: 0.3157894736842105                    
2025-05-06 15:25:40: BoTorchModel, best RESULT: 0.20526315789473681, completed 25 = ∑25/50, new result: 0.1947368421052632                    
2025-05-06 15:26:03: BoTorchModel, best RESULT: 0.1947368421052632, completed 24 = ∑24/50, new result: 0.2210526315789474                     
2025-05-06 15:26:28: BoTorchModel, best RESULT: 0.1947368421052632, completed 23 = ∑23/50, new result: 0.368421052631579                      
2025-05-06 15:26:46: BoTorchModel, best RESULT: 0.1947368421052632, completed 22 = ∑22/50, new result: 0.21578947368421053                    
2025-05-06 15:27:05: BoTorchModel, best RESULT: 0.1947368421052632, completed 21 = ∑21/50, new result: 0.22631578947368425                    
2025-05-06 15:27:28: BoTorchModel, best RESULT: 0.1947368421052632, completed 20 = ∑20/50, new result: 0.2789473684210526                     
2025-05-06 15:27:52: BoTorchModel, best RESULT: 0.1947368421052632, completed 19 = ∑19/50, new result: 0.3631578947368421                     
2025-05-06 15:28:13: BoTorchModel, best RESULT: 0.1947368421052632, completed 18 = ∑18/50, new result: 0.25263157894736843                    
2025-05-06 15:28:40: BoTorchModel, best RESULT: 0.1947368421052632, completed 17 = ∑17/50, new result: 0.3631578947368421                     
2025-05-06 15:28:56: BoTorchModel, best RESULT: 0.1947368421052632, completed 16 = ∑16/50, new result: 0.2421052631578947                     
2025-05-06 15:29:11: BoTorchModel, best RESULT: 0.1947368421052632, completed 15 = ∑15/50, new result: 0.3631578947368421                     
2025-05-06 15:29:28: BoTorchModel, best RESULT: 0.1947368421052632, completed 14 = ∑14/50, new result: 0.26315789473684215                    
2025-05-06 15:29:45: BoTorchModel, best RESULT: 0.1947368421052632, completed 13 = ∑13/50, new result: 0.35789473684210527                    
2025-05-06 15:30:01: BoTorchModel, best RESULT: 0.1947368421052632, completed 12 = ∑12/50, new result: 0.3631578947368421                     
2025-05-06 15:30:24: BoTorchModel, best RESULT: 0.1947368421052632, completed 11 = ∑11/50, new result: 0.3631578947368421                     
2025-05-06 15:30:40: BoTorchModel, best RESULT: 0.1947368421052632, completed 10 = ∑10/50, new result: 0.3631578947368421                     
2025-05-06 15:30:57: BoTorchModel, best RESULT: 0.1947368421052632, completed 9 = ∑9/50, new result: 0.19999999999999996                      
2025-05-06 15:31:21: BoTorchModel, best RESULT: 0.1947368421052632, completed 8 = ∑8/50, new result: 0.3631578947368421                       
2025-05-06 15:31:38: BoTorchModel, best RESULT: 0.1947368421052632, completed 7 = ∑7/50, new result: 0.4157894736842105                       
2025-05-06 15:31:58: BoTorchModel, best RESULT: 0.1947368421052632, completed 6 = ∑6/50, new result: 0.35789473684210527                      
2025-05-06 15:32:22: BoTorchModel, best RESULT: 0.1947368421052632, completed 5 = ∑5/50, new result: 0.19999999999999996                      
2025-05-06 15:32:41: BoTorchModel, best RESULT: 0.1947368421052632, completed 4 = ∑4/50, new result: 0.2421052631578947                       
2025-05-06 15:33:04: BoTorchModel, best RESULT: 0.1947368421052632, completed 3 = ∑3/50, new result: 0.23684210526315785                      
2025-05-06 15:33:24: BoTorchModel, best RESULT: 0.1947368421052632, completed 2 = ∑2/50, new result: 0.34736842105263155                      
2025-05-06 15:33:40: BoTorchModel, best RESULT: 0.1947368421052632, completed 1 = ∑1/50, new result: 0.3526315789473684                       
2025-05-06 15:33:55: BoTorchModel, best RESULT: 0.1947368421052632, finishing jobs, finished 50 jobs                                          
2025-05-06 15:34:04: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #1/50                                                  
2025-05-06 15:34:34: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #2/50 | ETA: 17m 48s                                   
2025-05-06 15:34:44: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #3/50 | ETA: 10m 12s                                   
2025-05-06 15:34:55: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #4/50 | ETA: 7m 45s                                    
2025-05-06 15:35:05: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #5/50 | ETA: 6m 18s                                    
2025-05-06 15:35:16: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #6/50 | ETA: 5m 17s                                    
2025-05-06 15:35:27: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #7/50 | ETA: 4m 40s                                    
2025-05-06 15:35:38: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #8/50 | ETA: 4m 17s                                    
2025-05-06 15:35:50: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #9/50 | ETA: 4m 0s                                     
2025-05-06 15:36:00: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #10/50 | ETA: 3m 41s                                   
2025-05-06 15:36:11: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #11/50 | ETA: 3m 26s                                   
2025-05-06 15:36:23: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #12/50 | ETA: 3m 16s                                   
2025-05-06 15:36:33: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #13/50 | ETA: 3m 7s                                    
2025-05-06 15:36:45: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #14/50 | ETA: 2m 58s                                   
2025-05-06 15:37:00: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #15/50 | ETA: 2m 53s                                   
2025-05-06 15:37:13: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #16/50 | ETA: 2m 47s                                   
2025-05-06 15:37:24: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #17/50 | ETA: 2m 38s                                   
2025-05-06 15:37:36: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #18/50 | ETA: 2m 32s                                   
2025-05-06 15:37:49: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #19/50 | ETA: 2m 27s                                   
2025-05-06 15:38:01: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #20/50 | ETA: 2m 21s                                   
2025-05-06 15:38:14: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #21/50 | ETA: 2m 14s                                   
2025-05-06 15:38:26: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #22/50 | ETA: 2m 10s                                   
2025-05-06 15:38:37: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #23/50 | ETA: 2m 4s                                    
2025-05-06 15:38:50: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #24/50 | ETA: 1m 59s                                   
2025-05-06 15:39:02: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #25/50 | ETA: 1m 54s                                   
2025-05-06 15:39:18: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #26/50 | ETA: 1m 50s                                   
2025-05-06 15:39:30: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #27/50 | ETA: 1m 45s                                   
2025-05-06 15:39:44: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #28/50 | ETA: 1m 41s                                   
2025-05-06 15:39:58: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #29/50 | ETA: 1m 36s                                   
2025-05-06 15:40:13: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #30/50 | ETA: 1m 32s                                   
2025-05-06 15:40:25: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #31/50 | ETA: 1m 27s                                   
2025-05-06 15:40:40: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #32/50 | ETA: 1m 23s                                   
2025-05-06 15:40:54: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #33/50 | ETA: 1m 19s                                   
2025-05-06 15:41:14: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #34/50 | ETA: 1m 14s                                   
2025-05-06 15:41:28: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #35/50 | ETA: 1m 11s                                   
2025-05-06 15:41:41: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #36/50 | ETA: 1m 6s                                    
2025-05-06 15:41:55: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #37/50 | ETA: 1m 2s                                    
2025-05-06 15:42:11: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #38/50 | ETA: 58s                                      
2025-05-06 15:42:24: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #39/50 | ETA: 54s                                      
2025-05-06 15:42:42: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #40/50 | ETA: 50s                                      
2025-05-06 15:42:57: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #41/50 | ETA: 45s                                      
2025-05-06 15:43:13: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #42/50 | ETA: 41s                                      
2025-05-06 15:43:36: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #43/50 | ETA: 37s                                      
2025-05-06 15:43:51: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #44/50 | ETA: 32s                                      
2025-05-06 15:44:08: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #45/50 | ETA: 28s                                      
2025-05-06 15:44:29: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #46/50 | ETA: 23s                                      
2025-05-06 15:44:46: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #47/50 | ETA: 19s                                      
2025-05-06 15:45:08: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #48/50 | ETA: 14s                                      
2025-05-06 15:45:32: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #49/50 | ETA: 9s                                       
2025-05-06 15:45:46: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #50/50 | ETA: 4s                                       
2025-05-06 15:46:01: BoTorchModel, best RESULT: 0.1947368421052632, eval start                                                                
2025-05-06 15:46:10: BoTorchModel, best RESULT: 0.1947368421052632, starting new job                                                          
2025-05-06 15:46:22: BoTorchModel, best RESULT: 0.1947368421052632, unknown 1 = ∑1/50, started new job                                        
2025-05-06 15:46:35: BoTorchModel, best RESULT: 0.1947368421052632, pending 1 = ∑1/50, eval start                                             
2025-05-06 15:46:47: BoTorchModel, best RESULT: 0.1947368421052632, pending 1 = ∑1/50, starting new job                                       
2025-05-06 15:47:00: BoTorchModel, best RESULT: 0.1947368421052632, running/unknown 1/1 = ∑2/50, started new job                              
2025-05-06 15:47:13: BoTorchModel, best RESULT: 0.1947368421052632, running/pending 1/1 = ∑2/50, eval start                                   
2025-05-06 15:47:25: BoTorchModel, best RESULT: 0.1947368421052632, running/pending 1/1 = ∑2/50, starting new job                             
2025-05-06 15:47:39: BoTorchModel, best RESULT: 0.1947368421052632, running/unknown 2/1 = ∑3/50, started new job                              
2025-05-06 15:47:48: BoTorchModel, best RESULT: 0.1947368421052632, running/pending 2/1 = ∑3/50, eval start                                   
2025-05-06 15:47:57: BoTorchModel, best RESULT: 0.1947368421052632, running/pending 2/1 = ∑3/50, starting new job                             
2025-05-06 15:48:16: BoTorchModel, best RESULT: 0.1947368421052632, running/unknown 3/1 = ∑4/50, started new job                              
2025-05-06 15:48:34: BoTorchModel, best RESULT: 0.1947368421052632, running 4 = ∑4/50, eval start                                             
2025-05-06 15:48:49: BoTorchModel, best RESULT: 0.1947368421052632, running 4 = ∑4/50, starting new job                                       
2025-05-06 15:49:08: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 1/3/1 = ∑5/50, started new job                  
2025-05-06 15:49:20: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 3/1/1 = ∑5/50, eval start                       
2025-05-06 15:49:35: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 4/1 = ∑5/50, starting new job                           
2025-05-06 15:49:52: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 4/1/1 = ∑6/50, started new job                  
2025-05-06 15:50:02: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 4/2 = ∑6/50, eval start                                 
2025-05-06 15:50:19: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 4/2 = ∑6/50, starting new job                           
2025-05-06 15:50:37: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 4/2/1 = ∑7/50, started new job                  
2025-05-06 15:50:53: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 5/1/1 = ∑7/50, eval start                       
2025-05-06 15:51:09: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 5/1/1 = ∑7/50, starting new job                 
2025-05-06 15:51:23: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 5/2/1 = ∑8/50, started new job                  
2025-05-06 15:51:36: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 5/3 = ∑8/50, eval start                                 
2025-05-06 15:51:51: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 5/3 = ∑8/50, starting new job                           
2025-05-06 15:52:06: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 5/3/1 = ∑9/50, started new job                  
2025-05-06 15:52:23: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 7/1/1 = ∑9/50, eval start                       
2025-05-06 15:52:46: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 7/2 = ∑9/50, starting new job                           
2025-05-06 15:53:03: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 7/2/1 = ∑10/50, started new job                 
2025-05-06 15:53:20: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 7/2/1 = ∑10/50, eval start                      
2025-05-06 15:53:36: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 7/2/1 = ∑10/50, starting new job                
2025-05-06 15:53:54: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 7/3/1 = ∑11/50, started new job                 
2025-05-06 15:54:11: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 8/3 = ∑11/50, eval start                                
2025-05-06 15:54:27: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 8/3 = ∑11/50, starting new job                          
2025-05-06 15:54:50: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 10/1/1 = ∑12/50, started new job                
2025-05-06 15:55:10: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 10/2 = ∑12/50, eval start                               
2025-05-06 15:55:31: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 10/2 = ∑12/50, starting new job                         
2025-05-06 15:55:50: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 10/2/1 = ∑13/50, started new job                
2025-05-06 15:56:07: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 10/3 = ∑13/50, eval start                               
2025-05-06 15:56:29: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 10/3 = ∑13/50, starting new job                         
2025-05-06 15:56:55: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 11/2/1 = ∑14/50, started new job                
2025-05-06 15:57:11: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 11/3 = ∑14/50, eval start                               
2025-05-06 15:57:24: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 11/3 = ∑14/50, starting new job                         
2025-05-06 15:57:44: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 13/1/1 = ∑15/50, started new job                
2025-05-06 15:58:07: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 13/2 = ∑15/50, eval start                               
2025-05-06 15:58:21: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 13/2 = ∑15/50, starting new job                         
2025-05-06 15:58:34: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 14/1/1 = ∑16/50, started new job                
2025-05-06 15:58:50: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 14/1/1 = ∑16/50, eval start                     
2025-05-06 15:59:10: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 15/1 = ∑16/50, starting new job                         
2025-05-06 15:59:30: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 15/1/1 = ∑17/50, started new job                
2025-05-06 15:59:48: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 15/1/1 = ∑17/50, eval start                     
2025-05-06 16:00:06: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 15/1/1 = ∑17/50, starting new job               
2025-05-06 16:00:23: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 15/2/1 = ∑18/50, started new job                
2025-05-06 16:00:39: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 16/2 = ∑18/50, eval start                               
2025-05-06 16:01:02: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 16/2 = ∑18/50, starting new job                         
2025-05-06 16:01:18: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 17/1/1 = ∑19/50, started new job                
2025-05-06 16:01:34: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 18/1 = ∑19/50, eval start                               
2025-05-06 16:01:50: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 18/1 = ∑19/50, starting new job                         
2025-05-06 16:02:13: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 18/1/1 = ∑20/50, started new job                
2025-05-06 16:02:27: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 18/1/1 = ∑20/50, eval start                     
2025-05-06 16:02:40: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 18/1/1 = ∑20/50, starting new job               
2025-05-06 16:02:57: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 18/2/1 = ∑21/50, started new job                
2025-05-06 16:03:19: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 18/3 = ∑21/50, eval start                               
2025-05-06 16:03:37: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 18/3 = ∑21/50, starting new job                         
2025-05-06 16:03:57: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 20/1/1 = ∑22/50, started new job                
2025-05-06 16:04:24: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 21/1 = ∑22/50, eval start                               
2025-05-06 16:04:43: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 21/1 = ∑22/50, starting new job                         
2025-05-06 16:05:06: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 21/1/1 = ∑23/50, started new job                
2025-05-06 16:05:31: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 21/2 = ∑23/50, eval start                               
2025-05-06 16:05:54: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 21/2 = ∑23/50, starting new job                         
2025-05-06 16:06:16: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 22/1/1 = ∑24/50, started new job                
2025-05-06 16:06:37: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 22/1/1 = ∑24/50, eval start                     
2025-05-06 16:06:54: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 22/1/1 = ∑24/50, starting new job               
2025-05-06 16:07:17: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 23/1/1 = ∑25/50, started new job                
2025-05-06 16:07:37: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 23/1/1 = ∑25/50, eval start                     
2025-05-06 16:08:05: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 23/2 = ∑25/50, starting new job                         
2025-05-06 16:08:40: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 24/1/1 = ∑26/50, started new job                
2025-05-06 16:09:09: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 25/1 = ∑26/50, eval start                               
2025-05-06 16:09:45: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 25/1 = ∑26/50, starting new job                         
2025-05-06 16:10:13: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 25/1/1 = ∑27/50, started new job                
2025-05-06 16:10:43: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 25/1/1 = ∑27/50, eval start                     
2025-05-06 16:11:25: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 25/2 = ∑27/50, starting new job                         
2025-05-06 16:11:56: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 25/2/1 = ∑28/50, started new job                
2025-05-06 16:12:27: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 25/3 = ∑28/50, eval start                               
2025-05-06 16:12:52: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 25/3 = ∑28/50, starting new job                         
2025-05-06 16:13:23: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 25/3/1 = ∑29/50, started new job                
2025-05-06 16:13:49: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 25/4 = ∑29/50, eval start                               
2025-05-06 16:14:25: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 26/3 = ∑29/50, starting new job                         
2025-05-06 16:14:59: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 26/3/1 = ∑30/50, started new job                
2025-05-06 16:15:28: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 27/3 = ∑30/50, eval start                               
2025-05-06 16:15:48: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 27/3 = ∑30/50, starting new job                         
2025-05-06 16:16:09: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 27/3/1 = ∑31/50, started new job                
2025-05-06 16:16:52: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 27/4 = ∑31/50, eval start                               
2025-05-06 16:17:18: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 27/4 = ∑31/50, starting new job                         
2025-05-06 16:17:46: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 27/4/1 = ∑32/50, started new job                
2025-05-06 16:18:15: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 28/4 = ∑32/50, eval start                               
2025-05-06 16:18:38: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 28/4 = ∑32/50, starting new job                         
2025-05-06 16:19:08: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 29/3/1 = ∑33/50, started new job                
2025-05-06 16:19:37: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 30/3 = ∑33/50, eval start                               
2025-05-06 16:20:14: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 30/3 = ∑33/50, starting new job                         
2025-05-06 16:20:44: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 31/2/1 = ∑34/50, started new job                
2025-05-06 16:21:25: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 31/3 = ∑34/50, eval start                               
2025-05-06 16:22:00: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 31/3 = ∑34/50, starting new job                         
2025-05-06 16:22:42: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 31/3/1 = ∑35/50, started new job                
2025-05-06 16:23:27: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 31/4 = ∑35/50, eval start                               
2025-05-06 16:24:02: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 31/4 = ∑35/50, starting new job                         
2025-05-06 16:25:01: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 32/3/1 = ∑36/50, started new job                
2025-05-06 16:25:52: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 32/4 = ∑36/50, eval start                               
2025-05-06 16:26:28: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 32/4 = ∑36/50, starting new job                         
2025-05-06 16:27:15: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 34/2/1 = ∑37/50, started new job                
2025-05-06 16:27:56: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 34/3 = ∑37/50, eval start                               
2025-05-06 16:28:34: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 34/3 = ∑37/50, starting new job                         
2025-05-06 16:29:06: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 34/3/1 = ∑38/50, started new job                
2025-05-06 16:29:38: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 34/4 = ∑38/50, eval start                               
2025-05-06 16:30:37: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 34/4 = ∑38/50, starting new job                         
2025-05-06 16:32:02: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 34/4/1 = ∑39/50, started new job                
2025-05-06 16:32:37: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 34/5 = ∑39/50, eval start                               
2025-05-06 16:33:12: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 34/5 = ∑39/50, starting new job                         
2025-05-06 16:33:48: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 34/5/1 = ∑40/50, started new job                
2025-05-06 16:34:14: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 34/6 = ∑40/50, eval start                               
2025-05-06 16:34:53: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 34/6 = ∑40/50, starting new job                         
2025-05-06 16:35:26: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 34/6/1 = ∑41/50, started new job                
2025-05-06 16:35:52: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 34/7 = ∑41/50, eval start                               
2025-05-06 16:36:10: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 34/7 = ∑41/50, starting new job                         
2025-05-06 16:36:36: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 34/7/1 = ∑42/50, started new job                
2025-05-06 16:37:08: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 34/8 = ∑42/50, eval start                               
2025-05-06 16:37:36: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 34/8 = ∑42/50, starting new job                         
2025-05-06 16:38:02: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 35/7/1 = ∑43/50, started new job                
2025-05-06 16:38:24: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 35/8 = ∑43/50, eval start                               
2025-05-06 16:38:49: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 35/8 = ∑43/50, starting new job                         
2025-05-06 16:39:15: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 35/8/1 = ∑44/50, started new job                
2025-05-06 16:39:41: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 35/9 = ∑44/50, eval start                               
2025-05-06 16:40:07: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 35/9 = ∑44/50, starting new job                         
2025-05-06 16:40:35: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 36/8/1 = ∑45/50, started new job                
2025-05-06 16:40:56: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 36/9 = ∑45/50, eval start                               
2025-05-06 16:41:28: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 36/9 = ∑45/50, starting new job                         
2025-05-06 16:41:48: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 36/9/1 = ∑46/50, started new job                
2025-05-06 16:42:22: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 41/5 = ∑46/50, eval start                               
2025-05-06 16:43:03: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 41/5 = ∑46/50, starting new job                         
2025-05-06 16:43:37: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 43/3/1 = ∑47/50, started new job                
2025-05-06 16:44:05: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 44/3 = ∑47/50, eval start                               
2025-05-06 16:44:29: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 44/3 = ∑47/50, starting new job                         
2025-05-06 16:45:09: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 44/3/1 = ∑48/50, started new job                
2025-05-06 16:45:52: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 44/4 = ∑48/50, eval start                               
2025-05-06 16:46:29: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 44/4 = ∑48/50, starting new job                         
2025-05-06 16:47:05: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 44/4/1 = ∑49/50, started new job                
2025-05-06 16:47:35: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 45/4 = ∑49/50, eval start                               
2025-05-06 16:48:10: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 45/4 = ∑49/50, starting new job                         
2025-05-06 16:48:41: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 45/4/1 = ∑50/50, started new job                
2025-05-06 16:49:20: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 45/5 = ∑50/50, new result: 0.35789473684210527          
2025-05-06 16:50:56: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 44/5 = ∑49/50, new result: 0.3052631578947368           
2025-05-06 16:52:55: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 45/3 = ∑48/50, new result: 0.2894736842105263           
2025-05-06 16:54:16: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 44/3 = ∑47/50, new result: 0.2894736842105263           
2025-05-06 16:55:38: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 45/1 = ∑46/50, new result: 0.26315789473684215          
2025-05-06 16:57:20: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 44/1 = ∑45/50, new result: 0.3052631578947368           
2025-05-06 16:58:54: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 43/1 = ∑44/50, new result: 0.2315789473684211           
2025-05-06 17:00:32: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 42/1 = ∑43/50, new result: 0.2210526315789474           
2025-05-06 17:02:17: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 41/1 = ∑42/50, new result: 0.23684210526315785          
2025-05-06 17:04:10: BoTorchModel, best RESULT: 0.1947368421052632, completed 41 = ∑41/50, new result: 0.32105263157894737                    
2025-05-06 17:06:00: BoTorchModel, best RESULT: 0.1947368421052632, completed 40 = ∑40/50, new result: 0.30000000000000004                    
2025-05-06 17:07:06: BoTorchModel, best RESULT: 0.1947368421052632, completed 39 = ∑39/50, new result: 0.33684210526315794                    
2025-05-06 17:08:07: BoTorchModel, best RESULT: 0.1947368421052632, completed 38 = ∑38/50, new result: 0.2421052631578947                     
2025-05-06 17:09:07: BoTorchModel, best RESULT: 0.1947368421052632, completed 37 = ∑37/50, new result: 0.3052631578947368                     
2025-05-06 17:09:57: BoTorchModel, best RESULT: 0.1947368421052632, completed 36 = ∑36/50, new result: 0.37368421052631584                    
2025-05-06 17:10:44: BoTorchModel, best RESULT: 0.1947368421052632, completed 35 = ∑35/50, new result: 0.2789473684210526                     
2025-05-06 17:11:39: BoTorchModel, best RESULT: 0.1947368421052632, completed 34 = ∑34/50, new result: 0.2947368421052632                     
2025-05-06 17:12:39: BoTorchModel, best RESULT: 0.1947368421052632, completed 33 = ∑33/50, new result: 0.3526315789473684                     
2025-05-06 17:13:38: BoTorchModel, best RESULT: 0.1947368421052632, completed 32 = ∑32/50, new result: 0.27368421052631575                    
2025-05-06 17:14:31: BoTorchModel, best RESULT: 0.1947368421052632, completed 31 = ∑31/50, new result: 0.3631578947368421                     
2025-05-06 17:15:20: BoTorchModel, best RESULT: 0.1947368421052632, completed 30 = ∑30/50, new result: 0.33684210526315794                    
2025-05-06 17:16:26: BoTorchModel, best RESULT: 0.1947368421052632, completed 29 = ∑29/50, new result: 0.24736842105263157                    
2025-05-06 17:17:18: BoTorchModel, best RESULT: 0.1947368421052632, completed 28 = ∑28/50, new result: 0.2947368421052632                     
2025-05-06 17:18:08: BoTorchModel, best RESULT: 0.1947368421052632, completed 27 = ∑27/50, new result: 0.31052631578947365                    
2025-05-06 17:18:48: BoTorchModel, best RESULT: 0.1947368421052632, completed 26 = ∑26/50, new result: 0.2315789473684211                     
2025-05-06 17:19:32: BoTorchModel, best RESULT: 0.1947368421052632, completed 25 = ∑25/50, new result: 0.31052631578947365                    
2025-05-06 17:20:24: BoTorchModel, best RESULT: 0.1947368421052632, completed 24 = ∑24/50, new result: 0.3263157894736842                     
2025-05-06 17:21:34: BoTorchModel, best RESULT: 0.1947368421052632, completed 23 = ∑23/50, new result: 0.27368421052631575                    
2025-05-06 17:22:37: BoTorchModel, best RESULT: 0.1947368421052632, completed 22 = ∑22/50, new result: 0.3157894736842105                     
2025-05-06 17:23:25: BoTorchModel, best RESULT: 0.1947368421052632, completed 21 = ∑21/50, new result: 0.3421052631578947                     
2025-05-06 17:24:10: BoTorchModel, best RESULT: 0.1947368421052632, completed 20 = ∑20/50, new result: 0.23684210526315785                    
2025-05-06 17:24:56: BoTorchModel, best RESULT: 0.1947368421052632, completed 19 = ∑19/50, new result: 0.32105263157894737                    
2025-05-06 17:25:33: BoTorchModel, best RESULT: 0.1947368421052632, completed 18 = ∑18/50, new result: 0.22631578947368425                    
2025-05-06 17:26:17: BoTorchModel, best RESULT: 0.1947368421052632, completed 17 = ∑17/50, new result: 0.2315789473684211                     
2025-05-06 17:27:11: BoTorchModel, best RESULT: 0.1947368421052632, completed 16 = ∑16/50, new result: 0.3263157894736842                     
2025-05-06 17:28:04: BoTorchModel, best RESULT: 0.1947368421052632, completed 15 = ∑15/50, new result: 0.2578947368421053                     
2025-05-06 17:29:05: BoTorchModel, best RESULT: 0.1947368421052632, completed 14 = ∑14/50, new result: 0.2421052631578947                     
2025-05-06 17:30:14: BoTorchModel, best RESULT: 0.1947368421052632, completed 13 = ∑13/50, new result: 0.2421052631578947                     
2025-05-06 17:31:07: BoTorchModel, best RESULT: 0.1947368421052632, completed 12 = ∑12/50, new result: 0.3052631578947368                     
2025-05-06 17:32:08: BoTorchModel, best RESULT: 0.1947368421052632, completed 11 = ∑11/50, new result: 0.2578947368421053                     
2025-05-06 17:32:59: BoTorchModel, best RESULT: 0.1947368421052632, completed 10 = ∑10/50, new result: 0.27368421052631575                    
2025-05-06 17:33:43: BoTorchModel, best RESULT: 0.1947368421052632, completed 9 = ∑9/50, new result: 0.27368421052631575                      
2025-05-06 17:34:25: BoTorchModel, best RESULT: 0.1947368421052632, completed 8 = ∑8/50, new result: 0.3631578947368421                       
2025-05-06 17:35:06: BoTorchModel, best RESULT: 0.1947368421052632, completed 7 = ∑7/50, new result: 0.3421052631578947                       
2025-05-06 17:35:45: BoTorchModel, best RESULT: 0.1947368421052632, completed 6 = ∑6/50, new result: 0.30000000000000004                      
2025-05-06 17:36:22: BoTorchModel, best RESULT: 0.1947368421052632, completed 5 = ∑5/50, new result: 0.2894736842105263                       
2025-05-06 17:36:59: BoTorchModel, best RESULT: 0.1947368421052632, completed 4 = ∑4/50, new result: 0.25263157894736843                      
2025-05-06 17:37:39: BoTorchModel, best RESULT: 0.1947368421052632, completed 3 = ∑3/50, new result: 0.2789473684210526                       
2025-05-06 17:38:09: BoTorchModel, best RESULT: 0.1947368421052632, completed 2 = ∑2/50, new result: 0.27368421052631575                      
2025-05-06 17:38:44: BoTorchModel, best RESULT: 0.1947368421052632, completed 1 = ∑1/50, new result: 0.3631578947368421                       
2025-05-06 17:39:20: BoTorchModel, best RESULT: 0.1947368421052632, finishing jobs, finished 50 jobs                                          
2025-05-06 17:39:38: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #1/50                                                  
2025-05-06 17:40:08: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #2/50 | ETA: 9m 37s                                    
2025-05-06 17:40:31: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #3/50 | ETA: 6m 36s                                    
2025-05-06 17:40:52: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #4/50 | ETA: 5m 27s                                    
2025-05-06 17:41:16: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #5/50 | ETA: 4m 57s                                    
2025-05-06 17:41:37: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #6/50 | ETA: 4m 30s                                    
2025-05-06 17:42:04: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #7/50 | ETA: 4m 24s                                    
2025-05-06 17:42:25: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #8/50 | ETA: 4m 13s                                    
2025-05-06 17:42:53: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #9/50 | ETA: 4m 2s                                     
2025-05-06 17:43:17: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #10/50 | ETA: 3m 52s                                   
2025-05-06 17:43:39: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #11/50 | ETA: 3m 45s                                   
2025-05-06 17:44:02: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #12/50 | ETA: 3m 35s                                   
2025-05-06 17:44:23: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #13/50 | ETA: 3m 24s                                   
2025-05-06 17:44:53: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #14/50 | ETA: 3m 17s                                   
2025-05-06 17:45:17: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #15/50 | ETA: 3m 10s                                   
2025-05-06 17:45:42: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #16/50 | ETA: 3m 2s                                    
2025-05-06 17:46:10: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #17/50 | ETA: 2m 55s                                   
2025-05-06 17:46:42: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #18/50 | ETA: 2m 51s                                   
2025-05-06 17:47:05: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #19/50 | ETA: 2m 45s                                   
2025-05-06 17:47:25: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #20/50 | ETA: 2m 38s                                   
2025-05-06 17:47:47: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #21/50 | ETA: 2m 35s                                   
2025-05-06 17:48:06: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #22/50 | ETA: 2m 30s                                   
2025-05-06 17:48:23: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #23/50 | ETA: 2m 24s                                   
2025-05-06 17:48:42: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #24/50 | ETA: 2m 18s                                   
2025-05-06 17:49:03: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #25/50 | ETA: 2m 14s                                   
2025-05-06 17:49:28: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #26/50 | ETA: 2m 8s                                    
2025-05-06 17:49:50: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #27/50 | ETA: 2m 3s                                    
2025-05-06 17:50:07: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #28/50 | ETA: 1m 58s                                   
2025-05-06 17:50:24: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #29/50 | ETA: 1m 52s                                   
2025-05-06 17:50:43: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #30/50 | ETA: 1m 47s                                   
2025-05-06 17:51:01: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #31/50 | ETA: 1m 42s                                   
2025-05-06 17:51:20: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #32/50 | ETA: 1m 37s                                   
2025-05-06 17:51:49: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #33/50 | ETA: 1m 32s                                   
2025-05-06 17:52:05: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #34/50 | ETA: 1m 27s                                   
2025-05-06 17:52:26: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #35/50 | ETA: 1m 22s                                   
2025-05-06 17:52:44: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #36/50 | ETA: 1m 17s                                   
2025-05-06 17:53:03: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #37/50 | ETA: 1m 12s                                   
2025-05-06 17:53:29: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #38/50 | ETA: 1m 8s                                    
2025-05-06 17:53:47: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #39/50 | ETA: 1m 3s                                    
2025-05-06 17:54:07: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #40/50 | ETA: 58s                                      
2025-05-06 17:54:31: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #41/50 | ETA: 53s                                      
2025-05-06 17:54:54: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #42/50 | ETA: 47s                                      
2025-05-06 17:55:16: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #43/50 | ETA: 42s                                      
2025-05-06 17:55:46: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #44/50 | ETA: 37s                                      
2025-05-06 17:56:12: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #45/50 | ETA: 32s                                      
2025-05-06 17:56:36: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #46/50 | ETA: 27s                                      
2025-05-06 17:56:55: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #47/50 | ETA: 21s                                      
2025-05-06 17:57:15: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #48/50 | ETA: 16s                                      
2025-05-06 17:57:37: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #49/50 | ETA: 11s                                      
2025-05-06 17:58:01: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #50/50 | ETA: 5s                                       
2025-05-06 17:58:23: BoTorchModel, best RESULT: 0.1947368421052632, eval start                                                                
2025-05-06 17:58:40: BoTorchModel, best RESULT: 0.1947368421052632, starting new job                                                          
2025-05-06 17:59:00: BoTorchModel, best RESULT: 0.1947368421052632, unknown 1 = ∑1/50, started new job                                        
2025-05-06 17:59:23: BoTorchModel, best RESULT: 0.1947368421052632, running 1 = ∑1/50, eval start                                             
2025-05-06 17:59:42: BoTorchModel, best RESULT: 0.1947368421052632, running 1 = ∑1/50, starting new job                                       
2025-05-06 18:00:01: BoTorchModel, best RESULT: 0.1947368421052632, running/unknown 1/1 = ∑2/50, started new job                              
2025-05-06 18:00:21: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 1/1 = ∑2/50, eval start                                 
2025-05-06 18:00:37: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 1/1 = ∑2/50, starting new job                           
2025-05-06 18:00:52: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 1/1/1 = ∑3/50, started new job                  
2025-05-06 18:01:16: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 1/2 = ∑3/50, eval start                                 
2025-05-06 18:01:31: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 1/2 = ∑3/50, starting new job                           
2025-05-06 18:01:49: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 3/1 = ∑4/50, started new job                            
2025-05-06 18:02:09: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 3/1 = ∑4/50, eval start                                 
2025-05-06 18:02:27: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 3/1 = ∑4/50, starting new job                           
2025-05-06 18:02:52: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 3/1/1 = ∑5/50, started new job                  
2025-05-06 18:03:16: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 4/1 = ∑5/50, eval start                                 
2025-05-06 18:03:30: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 4/1 = ∑5/50, starting new job                           
2025-05-06 18:03:47: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 4/1/1 = ∑6/50, started new job                  
2025-05-06 18:04:02: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 5/1 = ∑6/50, eval start                                 
2025-05-06 18:04:16: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 5/1 = ∑6/50, starting new job                           
2025-05-06 18:04:32: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 5/1/1 = ∑7/50, started new job                  
2025-05-06 18:04:50: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 5/2 = ∑7/50, eval start                                 
2025-05-06 18:05:09: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 6/1 = ∑7/50, starting new job                           
2025-05-06 18:05:27: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 7/1 = ∑8/50, started new job                            
2025-05-06 18:05:40: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 7/1 = ∑8/50, eval start                                 
2025-05-06 18:05:58: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 7/1 = ∑8/50, starting new job                           
2025-05-06 18:06:13: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 7/1/1 = ∑9/50, started new job                  
2025-05-06 18:06:24: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 8/1 = ∑9/50, eval start                                 
2025-05-06 18:06:35: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 8/1 = ∑9/50, starting new job                           
2025-05-06 18:06:55: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 8/1/1 = ∑10/50, started new job                 
2025-05-06 18:07:08: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 8/1/1 = ∑10/50, eval start                      
2025-05-06 18:07:21: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 8/1/1 = ∑10/50, starting new job                
2025-05-06 18:07:35: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 8/2/1 = ∑11/50, started new job                 
2025-05-06 18:07:54: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 10/1 = ∑11/50, eval start                               
2025-05-06 18:08:10: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 10/1 = ∑11/50, starting new job                         
2025-05-06 18:08:24: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 10/1/1 = ∑12/50, started new job                
2025-05-06 18:08:35: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 11/1 = ∑12/50, eval start                               
2025-05-06 18:08:55: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 11/1 = ∑12/50, starting new job                         
2025-05-06 18:09:12: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 11/1/1 = ∑13/50, started new job                
2025-05-06 18:09:26: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 11/2 = ∑13/50, eval start                               
2025-05-06 18:09:44: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 11/2 = ∑13/50, starting new job                         
2025-05-06 18:10:06: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 12/1/1 = ∑14/50, started new job                
2025-05-06 18:10:27: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 13/1 = ∑14/50, eval start                               
2025-05-06 18:10:49: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 13/1 = ∑14/50, starting new job                         
2025-05-06 18:11:13: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 13/1/1 = ∑15/50, started new job                
2025-05-06 18:11:36: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 13/2 = ∑15/50, eval start                               
2025-05-06 18:12:03: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 14/1 = ∑15/50, starting new job                         
2025-05-06 18:12:29: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 14/1/1 = ∑16/50, started new job                
2025-05-06 18:12:55: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 15/1 = ∑16/50, eval start                               
2025-05-06 18:13:18: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 15/1 = ∑16/50, starting new job                         
2025-05-06 18:13:45: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 15/1/1 = ∑17/50, started new job                
2025-05-06 18:14:13: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 16/1 = ∑17/50, eval start                               
2025-05-06 18:14:44: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 16/1 = ∑17/50, starting new job                         
2025-05-06 18:15:14: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 16/1/1 = ∑18/50, started new job                
2025-05-06 18:15:44: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 17/1 = ∑18/50, eval start                               
2025-05-06 18:16:07: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 17/1 = ∑18/50, starting new job                         
2025-05-06 18:16:38: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 17/1/1 = ∑19/50, started new job                
2025-05-06 18:17:08: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 18/1 = ∑19/50, eval start                               
2025-05-06 18:17:36: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 18/1 = ∑19/50, starting new job                         
2025-05-06 18:18:06: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 19/1 = ∑20/50, started new job                          
2025-05-06 18:18:34: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 19/1 = ∑20/50, eval start                               
2025-05-06 18:19:04: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 19/1 = ∑20/50, starting new job                         
2025-05-06 18:19:41: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 20/1 = ∑21/50, started new job                          
2025-05-06 18:20:13: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 20/1 = ∑21/50, eval start                               
2025-05-06 18:20:35: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 20/1 = ∑21/50, starting new job                         
2025-05-06 18:21:02: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 21/1 = ∑22/50, started new job                          
2025-05-06 18:21:25: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 21/1 = ∑22/50, eval start                               
2025-05-06 18:21:54: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 21/1 = ∑22/50, starting new job                         
2025-05-06 18:22:41: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 21/1/1 = ∑23/50, started new job                
2025-05-06 18:23:19: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 21/2 = ∑23/50, eval start                               
2025-05-06 18:24:06: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 21/2 = ∑23/50, starting new job                         
2025-05-06 18:24:50: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 21/2/1 = ∑24/50, started new job                
2025-05-06 18:25:25: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 21/3 = ∑24/50, eval start                               
2025-05-06 18:26:07: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 21/3 = ∑24/50, starting new job                         
2025-05-06 18:26:41: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 21/3/1 = ∑25/50, started new job                
2025-05-06 18:27:19: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 21/4 = ∑25/50, eval start                               
2025-05-06 18:28:05: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 22/3 = ∑25/50, starting new job                         
2025-05-06 18:28:54: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 22/3/1 = ∑26/50, started new job                
2025-05-06 18:29:37: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 22/4 = ∑26/50, eval start                               
2025-05-06 18:30:14: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 22/4 = ∑26/50, starting new job                         
2025-05-06 18:30:58: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 22/4/1 = ∑27/50, started new job                
2025-05-06 18:31:42: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 22/5 = ∑27/50, eval start                               
2025-05-06 18:32:26: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 22/5 = ∑27/50, starting new job                         
2025-05-06 18:33:20: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 22/5/1 = ∑28/50, started new job                
2025-05-06 18:34:25: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 22/6 = ∑28/50, eval start                               
2025-05-06 18:35:11: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 22/6 = ∑28/50, starting new job                         
2025-05-06 18:35:52: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 22/6/1 = ∑29/50, started new job                
2025-05-06 18:36:44: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 22/7 = ∑29/50, eval start                               
2025-05-06 18:37:38: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 22/7 = ∑29/50, starting new job                         
2025-05-06 18:38:24: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 22/7/1 = ∑30/50, started new job                
2025-05-06 18:38:53: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 22/7/1 = ∑30/50, eval start                     
2025-05-06 18:39:21: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 22/7/1 = ∑30/50, starting new job               
2025-05-06 18:39:52: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 22/8/1 = ∑31/50, started new job                
2025-05-06 18:40:13: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 23/7/1 = ∑31/50, eval start                     
2025-05-06 18:40:50: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 23/8 = ∑31/50, starting new job                         
2025-05-06 18:41:27: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 23/8/1 = ∑32/50, started new job                
2025-05-06 18:41:52: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 23/9 = ∑32/50, eval start                               
2025-05-06 18:42:25: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 23/9 = ∑32/50, starting new job                         
2025-05-06 18:43:46: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 23/9/1 = ∑33/50, started new job                
2025-05-06 18:44:14: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 24/9 = ∑33/50, eval start                               
2025-05-06 18:44:46: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 24/9 = ∑33/50, starting new job                         
2025-05-06 18:45:08: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 24/9/1 = ∑34/50, started new job                
2025-05-06 18:45:39: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 24/10 = ∑34/50, eval start                              
2025-05-06 18:46:12: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 25/9 = ∑34/50, starting new job                         
2025-05-06 18:47:02: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 25/9/1 = ∑35/50, started new job                
2025-05-06 18:47:29: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 25/10 = ∑35/50, eval start                              
2025-05-06 18:47:53: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 25/10 = ∑35/50, starting new job                        
2025-05-06 18:48:22: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 32/3/1 = ∑36/50, started new job                
2025-05-06 18:48:46: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 34/2 = ∑36/50, eval start                               
2025-05-06 18:49:12: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 34/2 = ∑36/50, starting new job                         
2025-05-06 18:49:35: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 34/2/1 = ∑37/50, started new job                
2025-05-06 18:50:00: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 35/2 = ∑37/50, eval start                               
2025-05-06 18:50:26: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 35/2 = ∑37/50, starting new job                         
2025-05-06 18:50:55: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 35/2/1 = ∑38/50, started new job                
2025-05-06 18:51:28: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 36/2 = ∑38/50, eval start                               
2025-05-06 18:51:52: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 36/2 = ∑38/50, starting new job                         
2025-05-06 18:52:17: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 37/1/1 = ∑39/50, started new job                
2025-05-06 18:52:42: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 38/1 = ∑39/50, eval start                               
2025-05-06 18:53:11: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 38/1 = ∑39/50, starting new job                         
2025-05-06 18:53:44: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 39/1 = ∑40/50, started new job                          
2025-05-06 18:54:16: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 39/1 = ∑40/50, eval start                               
2025-05-06 18:54:37: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 39/1 = ∑40/50, starting new job                         
2025-05-06 18:55:01: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 39/1/1 = ∑41/50, started new job                
2025-05-06 18:55:28: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 40/1 = ∑41/50, eval start                               
2025-05-06 18:55:52: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 40/1 = ∑41/50, starting new job                         
2025-05-06 18:56:17: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 40/1/1 = ∑42/50, started new job                
2025-05-06 18:56:39: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 41/1 = ∑42/50, eval start                               
2025-05-06 18:57:01: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 41/1 = ∑42/50, starting new job                         
2025-05-06 18:57:31: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 42/1 = ∑43/50, started new job                          
2025-05-06 18:57:57: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 42/1 = ∑43/50, eval start                               
2025-05-06 18:58:25: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 42/1 = ∑43/50, starting new job                         
2025-05-06 18:58:49: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 42/1/1 = ∑44/50, started new job                
2025-05-06 18:59:20: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 43/1 = ∑44/50, eval start                               
2025-05-06 18:59:53: BoTorchModel, best RESULT: 0.1947368421052632, completed 44 = ∑44/50, starting new job                                   
2025-05-06 19:00:26: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 44/1 = ∑45/50, started new job                          
2025-05-06 19:00:47: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 44/1 = ∑45/50, eval start                               
2025-05-06 19:01:08: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 44/1 = ∑45/50, starting new job                         
2025-05-06 19:01:43: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 45/1 = ∑46/50, started new job                          
2025-05-06 19:02:12: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 45/1 = ∑46/50, eval start                               
2025-05-06 19:02:40: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 45/1 = ∑46/50, starting new job                         
2025-05-06 19:02:59: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 45/1/1 = ∑47/50, started new job                
2025-05-06 19:03:20: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 46/1 = ∑47/50, eval start                               
2025-05-06 19:03:45: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 46/1 = ∑47/50, starting new job                         
2025-05-06 19:04:06: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 47/1 = ∑48/50, started new job                          
2025-05-06 19:04:25: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 47/1 = ∑48/50, eval start                               
2025-05-06 19:04:53: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 47/1 = ∑48/50, starting new job                         
2025-05-06 19:05:09: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 48/1 = ∑49/50, started new job                          
2025-05-06 19:05:29: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 48/1 = ∑49/50, eval start                               
2025-05-06 19:05:56: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 48/1 = ∑49/50, starting new job                         
2025-05-06 19:06:15: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 49/1 = ∑50/50, started new job                          
2025-05-06 19:06:50: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 49/1 = ∑50/50, new result: 0.1947368421052632           
2025-05-06 19:07:42: BoTorchModel, best RESULT: 0.1947368421052632, completed 49 = ∑49/50, new result: 0.21052631578947367                    
2025-05-06 19:08:22: BoTorchModel, best RESULT: 0.1947368421052632, completed 48 = ∑48/50, new result: 0.3052631578947368                     
2025-05-06 19:09:05: BoTorchModel, best RESULT: 0.1947368421052632, completed 47 = ∑47/50, new result: 0.2315789473684211                     
2025-05-06 19:09:49: BoTorchModel, best RESULT: 0.1947368421052632, completed 46 = ∑46/50, new result: 0.30000000000000004                    
2025-05-06 19:10:31: BoTorchModel, best RESULT: 0.1947368421052632, completed 45 = ∑45/50, new result: 0.4631578947368421                     
2025-05-06 19:11:21: BoTorchModel, best RESULT: 0.1947368421052632, completed 44 = ∑44/50, new result: 0.3789473684210526                     
2025-05-06 19:12:12: BoTorchModel, best RESULT: 0.1947368421052632, completed 43 = ∑43/50, new result: 0.3157894736842105                     
2025-05-06 19:12:58: BoTorchModel, best RESULT: 0.1947368421052632, completed 42 = ∑42/50, new result: 0.2421052631578947                     
2025-05-06 19:13:58: BoTorchModel, best RESULT: 0.1947368421052632, completed 41 = ∑41/50, new result: 0.3052631578947368                     
2025-05-06 19:14:38: BoTorchModel, best RESULT: 0.1947368421052632, completed 40 = ∑40/50, new result: 0.31052631578947365                    
2025-05-06 19:15:15: BoTorchModel, best RESULT: 0.1947368421052632, completed 39 = ∑39/50, new result: 0.2789473684210526                     
2025-05-06 19:15:55: BoTorchModel, best RESULT: 0.1947368421052632, completed 38 = ∑38/50, new result: 0.3894736842105263                     
2025-05-06 19:16:28: BoTorchModel, best RESULT: 0.1947368421052632, completed 37 = ∑37/50, new result: 0.31052631578947365                    
2025-05-06 19:17:02: BoTorchModel, best RESULT: 0.1947368421052632, completed 36 = ∑36/50, new result: 0.35789473684210527                    
2025-05-06 19:17:31: BoTorchModel, best RESULT: 0.1947368421052632, completed 35 = ∑35/50, new result: 0.3631578947368421                     
2025-05-06 19:18:07: BoTorchModel, best RESULT: 0.1947368421052632, completed 34 = ∑34/50, new result: 0.3263157894736842                     
2025-05-06 19:18:50: BoTorchModel, best RESULT: 0.1947368421052632, completed 33 = ∑33/50, new result: 0.4052631578947369                     
2025-05-06 19:19:21: BoTorchModel, best RESULT: 0.1947368421052632, completed 32 = ∑32/50, new result: 0.28421052631578947                    
2025-05-06 19:20:00: BoTorchModel, best RESULT: 0.1947368421052632, completed 31 = ∑31/50, new result: 0.3631578947368421                     
2025-05-06 19:20:38: BoTorchModel, best RESULT: 0.1947368421052632, completed 30 = ∑30/50, new result: 0.39473684210526316                    
2025-05-06 19:21:19: BoTorchModel, best RESULT: 0.1947368421052632, completed 29 = ∑29/50, new result: 0.20526315789473681                    
2025-05-06 19:22:02: BoTorchModel, best RESULT: 0.1947368421052632, completed 28 = ∑28/50, new result: 0.4789473684210527                     
2025-05-06 19:22:48: BoTorchModel, best RESULT: 0.1947368421052632, completed 27 = ∑27/50, new result: 0.3263157894736842                     
2025-05-06 19:23:29: BoTorchModel, best RESULT: 0.1947368421052632, completed 26 = ∑26/50, new result: 0.3526315789473684                     
2025-05-06 19:24:15: BoTorchModel, best RESULT: 0.1947368421052632, completed 25 = ∑25/50, new result: 0.3315789473684211                     
2025-05-06 19:24:49: BoTorchModel, best RESULT: 0.1947368421052632, completed 24 = ∑24/50, new result: 0.2947368421052632                     
2025-05-06 19:25:23: BoTorchModel, best RESULT: 0.1947368421052632, completed 23 = ∑23/50, new result: 0.2947368421052632                     
2025-05-06 19:25:59: BoTorchModel, best RESULT: 0.1947368421052632, completed 22 = ∑22/50, new result: 0.35789473684210527                    
2025-05-06 19:26:37: BoTorchModel, best RESULT: 0.1947368421052632, completed 21 = ∑21/50, new result: 0.35789473684210527                    
2025-05-06 19:27:10: BoTorchModel, best RESULT: 0.1947368421052632, completed 20 = ∑20/50, new result: 0.2789473684210526                     
2025-05-06 19:27:53: BoTorchModel, best RESULT: 0.1947368421052632, completed 19 = ∑19/50, new result: 0.3631578947368421                     
2025-05-06 19:28:39: BoTorchModel, best RESULT: 0.1947368421052632, completed 18 = ∑18/50, new result: 0.3894736842105263                     
2025-05-06 19:29:21: BoTorchModel, best RESULT: 0.1947368421052632, completed 17 = ∑17/50, new result: 0.20526315789473681                    
2025-05-06 19:30:02: BoTorchModel, best RESULT: 0.1947368421052632, completed 16 = ∑16/50, new result: 0.21578947368421053                    
2025-05-06 19:30:39: BoTorchModel, best RESULT: 0.1947368421052632, completed 15 = ∑15/50, new result: 0.25263157894736843                    
2025-05-06 19:31:17: BoTorchModel, best RESULT: 0.1947368421052632, completed 14 = ∑14/50, new result: 0.27368421052631575                    
2025-05-06 19:31:51: BoTorchModel, best RESULT: 0.1947368421052632, completed 13 = ∑13/50, new result: 0.2684210526315789                     
2025-05-06 19:32:28: BoTorchModel, best RESULT: 0.1947368421052632, completed 12 = ∑12/50, new result: 0.3421052631578947                     
2025-05-06 19:33:06: BoTorchModel, best RESULT: 0.1947368421052632, completed 11 = ∑11/50, new result: 0.3052631578947368                     
2025-05-06 19:33:42: BoTorchModel, best RESULT: 0.1947368421052632, completed 10 = ∑10/50, new result: 0.368421052631579                      
2025-05-06 19:34:15: BoTorchModel, best RESULT: 0.1947368421052632, completed 9 = ∑9/50, new result: 0.21578947368421053                      
2025-05-06 19:34:50: BoTorchModel, best RESULT: 0.1947368421052632, completed 8 = ∑8/50, new result: 0.3157894736842105                       
2025-05-06 19:35:28: BoTorchModel, best RESULT: 0.1947368421052632, completed 7 = ∑7/50, new result: 0.34736842105263155                      
2025-05-06 19:36:01: BoTorchModel, best RESULT: 0.1947368421052632, completed 6 = ∑6/50, new result: 0.3157894736842105                       
2025-05-06 19:36:32: BoTorchModel, best RESULT: 0.1947368421052632, completed 5 = ∑5/50, new result: 0.24736842105263157                      
2025-05-06 19:37:05: BoTorchModel, best RESULT: 0.1947368421052632, completed 4 = ∑4/50, new result: 0.3526315789473684                       
2025-05-06 19:37:32: BoTorchModel, best RESULT: 0.1947368421052632, completed 3 = ∑3/50, new result: 0.2315789473684211                       
2025-05-06 19:38:03: BoTorchModel, best RESULT: 0.1947368421052632, completed 2 = ∑2/50, new result: 0.30000000000000004                      
2025-05-06 19:38:31: BoTorchModel, best RESULT: 0.1947368421052632, completed 1 = ∑1/50, new result: 0.34736842105263155                      
2025-05-06 19:39:01: BoTorchModel, best RESULT: 0.1947368421052632, finishing jobs, finished 50 jobs                                          
2025-05-06 19:39:16: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #1/50                                                  
2025-05-06 19:39:46: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #2/50 | ETA: 11m 42s                                   
2025-05-06 19:40:13: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #3/50 | ETA: 9m 50s                                    
2025-05-06 19:40:39: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #4/50 | ETA: 8m 47s                                    
2025-05-06 19:41:05: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #5/50 | ETA: 7m 47s                                    
2025-05-06 19:41:28: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #6/50 | ETA: 7m 8s                                     
2025-05-06 19:41:52: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #7/50 | ETA: 6m 46s                                    
2025-05-06 19:42:14: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #8/50 | ETA: 6m 20s                                    
2025-05-06 19:42:35: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #9/50 | ETA: 6m 2s                                     
2025-05-06 19:42:54: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #10/50 | ETA: 5m 46s                                   
2025-05-06 19:43:15: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #11/50 | ETA: 5m 34s                                   
2025-05-06 19:43:36: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #12/50 | ETA: 5m 20s                                   
2025-05-06 19:43:57: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #13/50 | ETA: 5m 7s                                    
2025-05-06 19:44:20: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #14/50 | ETA: 4m 54s                                   
2025-05-06 19:44:41: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #15/50 | ETA: 4m 42s                                   
2025-05-06 19:45:06: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #16/50 | ETA: 4m 31s                                   
2025-05-06 19:45:39: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #17/50 | ETA: 4m 27s                                   
2025-05-06 19:46:07: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #18/50 | ETA: 4m 16s                                   
2025-05-06 19:46:33: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #19/50 | ETA: 4m 8s                                    
2025-05-06 19:46:58: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #20/50 | ETA: 3m 59s                                   
2025-05-06 19:47:28: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #21/50 | ETA: 3m 51s                                   
2025-05-06 19:47:51: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #22/50 | ETA: 3m 42s                                   
2025-05-06 19:48:18: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #23/50 | ETA: 3m 34s                                   
2025-05-06 19:48:41: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #24/50 | ETA: 3m 26s                                   
2025-05-06 19:49:07: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #25/50 | ETA: 3m 19s                                   
2025-05-06 19:49:32: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #26/50 | ETA: 3m 11s                                   
2025-05-06 19:49:56: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #27/50 | ETA: 3m 3s                                    
2025-05-06 19:50:20: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #28/50 | ETA: 2m 55s                                   
2025-05-06 19:50:43: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #29/50 | ETA: 2m 47s                                   
2025-05-06 19:51:08: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #30/50 | ETA: 2m 39s                                   
2025-05-06 19:51:33: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #31/50 | ETA: 2m 31s                                   
2025-05-06 19:51:58: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #32/50 | ETA: 2m 24s                                   
2025-05-06 19:52:22: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #33/50 | ETA: 2m 16s                                   
2025-05-06 19:52:53: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #34/50 | ETA: 2m 8s                                    
2025-05-06 19:53:21: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #35/50 | ETA: 2m 1s                                    
2025-05-06 19:53:46: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #36/50 | ETA: 1m 53s                                   
2025-05-06 19:54:13: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #37/50 | ETA: 1m 46s                                   
2025-05-06 19:54:36: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #38/50 | ETA: 1m 38s                                   
2025-05-06 19:55:08: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #39/50 | ETA: 1m 31s                                   
2025-05-06 19:55:31: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #40/50 | ETA: 1m 23s                                   
2025-05-06 19:55:54: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #41/50 | ETA: 1m 16s                                   
2025-05-06 19:56:20: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #42/50 | ETA: 1m 8s                                    
2025-05-06 19:56:47: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #43/50 | ETA: 1m 1s                                    
2025-05-06 19:57:15: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #44/50 | ETA: 53s                                      
2025-05-06 19:57:42: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #45/50 | ETA: 46s                                      
2025-05-06 19:58:12: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #46/50 | ETA: 38s                                      
2025-05-06 19:58:38: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #47/50 | ETA: 31s                                      
2025-05-06 19:59:05: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #48/50 | ETA: 23s                                      
2025-05-06 19:59:29: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #49/50 | ETA: 15s                                      
2025-05-06 19:59:54: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #50/50 | ETA: 7s                                       
2025-05-06 20:00:22: BoTorchModel, best RESULT: 0.1947368421052632, eval start                                                                
2025-05-06 20:00:37: BoTorchModel, best RESULT: 0.1947368421052632, starting new job                                                          
2025-05-06 20:01:04: BoTorchModel, best RESULT: 0.1947368421052632, unknown 1 = ∑1/50, started new job                                        
2025-05-06 20:01:22: BoTorchModel, best RESULT: 0.1947368421052632, running 1 = ∑1/50, eval start                                             
2025-05-06 20:01:41: BoTorchModel, best RESULT: 0.1947368421052632, running 1 = ∑1/50, starting new job                                       
2025-05-06 20:01:59: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 1/1 = ∑2/50, started new job                            
2025-05-06 20:02:14: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 1/1 = ∑2/50, eval start                                 
2025-05-06 20:02:29: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 1/1 = ∑2/50, starting new job                           
2025-05-06 20:02:49: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 2/1 = ∑3/50, started new job                            
2025-05-06 20:03:04: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 2/1 = ∑3/50, eval start                                 
2025-05-06 20:03:17: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 2/1 = ∑3/50, starting new job                           
2025-05-06 20:03:31: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 2/1/1 = ∑4/50, started new job                  
2025-05-06 20:03:43: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 3/1 = ∑4/50, eval start                                 
2025-05-06 20:03:56: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 3/1 = ∑4/50, starting new job                           
2025-05-06 20:04:10: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 3/1/1 = ∑5/50, started new job                  
2025-05-06 20:04:22: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 4/1 = ∑5/50, eval start                                 
2025-05-06 20:04:35: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 4/1 = ∑5/50, starting new job                           
2025-05-06 20:04:50: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 5/1 = ∑6/50, started new job                            
2025-05-06 20:05:03: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 5/1 = ∑6/50, eval start                                 
2025-05-06 20:05:16: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 5/1 = ∑6/50, starting new job                           
2025-05-06 20:05:30: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 6/1 = ∑7/50, started new job                            
2025-05-06 20:05:43: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 6/1 = ∑7/50, eval start                                 
2025-05-06 20:05:54: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 6/1 = ∑7/50, starting new job                           
2025-05-06 20:06:08: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 6/1/1 = ∑8/50, started new job                  
2025-05-06 20:06:21: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 6/1/1 = ∑8/50, eval start                       
2025-05-06 20:06:34: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 6/1/1 = ∑8/50, starting new job                 
2025-05-06 20:06:48: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 7/1/1 = ∑9/50, started new job                  
2025-05-06 20:07:00: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 8/1 = ∑9/50, eval start                                 
2025-05-06 20:07:13: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 8/1 = ∑9/50, starting new job                           
2025-05-06 20:07:28: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 9/1 = ∑10/50, started new job                           
2025-05-06 20:07:40: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 9/1 = ∑10/50, eval start                                
2025-05-06 20:07:53: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 9/1 = ∑10/50, starting new job                          
2025-05-06 20:08:06: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 10/1 = ∑11/50, started new job                          
2025-05-06 20:08:18: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 10/1 = ∑11/50, eval start                               
2025-05-06 20:08:31: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 10/1 = ∑11/50, starting new job                         
2025-05-06 20:08:45: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 10/1/1 = ∑12/50, started new job                
2025-05-06 20:09:00: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 10/1/1 = ∑12/50, eval start                     
2025-05-06 20:09:13: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 10/1/1 = ∑12/50, starting new job               
2025-05-06 20:09:27: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 12/1 = ∑13/50, started new job                          
2025-05-06 20:09:39: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 12/1 = ∑13/50, eval start                               
2025-05-06 20:09:52: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 12/1 = ∑13/50, starting new job                         
2025-05-06 20:10:06: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 13/1 = ∑14/50, started new job                          
2025-05-06 20:10:20: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 13/1 = ∑14/50, eval start                               
2025-05-06 20:10:33: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 13/1 = ∑14/50, starting new job                         
2025-05-06 20:10:46: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 14/1 = ∑15/50, started new job                          
2025-05-06 20:10:59: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 14/1 = ∑15/50, eval start                               
2025-05-06 20:11:11: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 14/1 = ∑15/50, starting new job                         
2025-05-06 20:11:25: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 14/1/1 = ∑16/50, started new job                
2025-05-06 20:11:38: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 15/1 = ∑16/50, eval start                               
2025-05-06 20:11:50: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 15/1 = ∑16/50, starting new job                         
2025-05-06 20:12:06: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 15/1/1 = ∑17/50, started new job                
2025-05-06 20:12:20: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 16/1 = ∑17/50, eval start                               
2025-05-06 20:12:37: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 16/1 = ∑17/50, starting new job                         
2025-05-06 20:12:53: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 17/1 = ∑18/50, started new job                          
2025-05-06 20:13:07: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 17/1 = ∑18/50, eval start                               
2025-05-06 20:13:22: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 17/1 = ∑18/50, starting new job                         
2025-05-06 20:13:37: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 17/1/1 = ∑19/50, started new job                
2025-05-06 20:13:52: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 18/1 = ∑19/50, eval start                               
2025-05-06 20:14:07: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 18/1 = ∑19/50, starting new job                         
2025-05-06 20:14:23: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 19/1 = ∑20/50, started new job                          
2025-05-06 20:14:36: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 19/1 = ∑20/50, eval start                               
2025-05-06 20:14:52: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 19/1 = ∑20/50, starting new job                         
2025-05-06 20:15:08: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 19/1/1 = ∑21/50, started new job                
2025-05-06 20:15:22: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 20/1 = ∑21/50, eval start                               
2025-05-06 20:15:36: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 20/1 = ∑21/50, starting new job                         
2025-05-06 20:15:55: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 21/1 = ∑22/50, started new job                          
2025-05-06 20:16:10: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 21/1 = ∑22/50, eval start                               
2025-05-06 20:16:25: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 21/1 = ∑22/50, starting new job                         
2025-05-06 20:16:42: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 21/1/1 = ∑23/50, started new job                
2025-05-06 20:16:59: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 22/1 = ∑23/50, eval start                               
2025-05-06 20:17:16: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 22/1 = ∑23/50, starting new job                         
2025-05-06 20:17:34: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 23/1 = ∑24/50, started new job                          
2025-05-06 20:17:50: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 23/1 = ∑24/50, eval start                               
2025-05-06 20:18:04: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 23/1 = ∑24/50, starting new job                         
2025-05-06 20:18:20: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 24/1 = ∑25/50, started new job                          
2025-05-06 20:18:33: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 24/1 = ∑25/50, eval start                               
2025-05-06 20:18:51: BoTorchModel, best RESULT: 0.1947368421052632, completed 25 = ∑25/50, starting new job                                   
2025-05-06 20:19:05: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 25/1 = ∑26/50, started new job                          
2025-05-06 20:19:19: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 25/1 = ∑26/50, eval start                               
2025-05-06 20:19:33: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 25/1 = ∑26/50, starting new job                         
2025-05-06 20:19:50: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 25/1/1 = ∑27/50, started new job                
2025-05-06 20:20:08: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 26/1 = ∑27/50, eval start                               
2025-05-06 20:20:25: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 26/1 = ∑27/50, starting new job                         
2025-05-06 20:20:42: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 27/1 = ∑28/50, started new job                          
2025-05-06 20:20:59: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 27/1 = ∑28/50, eval start                               
2025-05-06 20:21:14: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 27/1 = ∑28/50, starting new job                         
2025-05-06 20:21:34: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 28/1 = ∑29/50, started new job                          
2025-05-06 20:21:52: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 28/1 = ∑29/50, eval start                               
2025-05-06 20:22:07: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 28/1 = ∑29/50, starting new job                         
2025-05-06 20:22:25: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 29/1 = ∑30/50, started new job                          
2025-05-06 20:22:51: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 29/1 = ∑30/50, eval start                               
2025-05-06 20:23:08: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 29/1 = ∑30/50, starting new job                         
2025-05-06 20:23:24: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 29/1/1 = ∑31/50, started new job                
2025-05-06 20:23:45: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 29/2 = ∑31/50, eval start                               
2025-05-06 20:24:01: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 29/2 = ∑31/50, starting new job                         
2025-05-06 20:24:19: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 30/1/1 = ∑32/50, started new job                
2025-05-06 20:24:34: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 30/1/1 = ∑32/50, eval start                     
2025-05-06 20:24:55: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 30/2 = ∑32/50, starting new job                         
2025-05-06 20:25:12: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 30/2/1 = ∑33/50, started new job                
2025-05-06 20:25:32: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 30/3 = ∑33/50, eval start                               
2025-05-06 20:25:51: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 30/3 = ∑33/50, starting new job                         
2025-05-06 20:26:07: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 31/2/1 = ∑34/50, started new job                
2025-05-06 20:26:21: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 31/3 = ∑34/50, eval start                               
2025-05-06 20:26:37: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 31/3 = ∑34/50, starting new job                         
2025-05-06 20:27:00: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 31/3/1 = ∑35/50, started new job                
2025-05-06 20:27:16: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 31/3/1 = ∑35/50, eval start                     
2025-05-06 20:27:33: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 31/3/1 = ∑35/50, starting new job               
2025-05-06 20:27:54: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 31/4/1 = ∑36/50, started new job                
2025-05-06 20:28:10: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 31/4/1 = ∑36/50, eval start                     
2025-05-06 20:28:29: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 31/5 = ∑36/50, starting new job                         
2025-05-06 20:28:49: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 31/5/1 = ∑37/50, started new job                
2025-05-06 20:29:05: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 31/6 = ∑37/50, eval start                               
2025-05-06 20:29:22: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 31/6 = ∑37/50, starting new job                         
2025-05-06 20:29:44: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 31/6/1 = ∑38/50, started new job                
2025-05-06 20:30:02: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 33/5 = ∑38/50, eval start                               
2025-05-06 20:30:19: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 33/5 = ∑38/50, starting new job                         
2025-05-06 20:30:39: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 33/5/1 = ∑39/50, started new job                
2025-05-06 20:30:56: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 33/5/1 = ∑39/50, eval start                     
2025-05-06 20:31:11: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 33/5/1 = ∑39/50, starting new job               
2025-05-06 20:31:31: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 33/6/1 = ∑40/50, started new job                
2025-05-06 20:31:46: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 33/7 = ∑40/50, eval start                               
2025-05-06 20:32:01: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 33/7 = ∑40/50, starting new job                         
2025-05-06 20:32:20: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 33/7/1 = ∑41/50, started new job                
2025-05-06 20:32:35: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 33/7/1 = ∑41/50, eval start                     
2025-05-06 20:32:51: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 33/7/1 = ∑41/50, starting new job               
2025-05-06 20:33:09: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 33/8/1 = ∑42/50, started new job                
2025-05-06 20:33:25: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 33/8/1 = ∑42/50, eval start                     
2025-05-06 20:33:45: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 33/9 = ∑42/50, starting new job                         
2025-05-06 20:34:04: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 33/9/1 = ∑43/50, started new job                
2025-05-06 20:34:23: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 33/10 = ∑43/50, eval start                              
2025-05-06 20:34:39: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 33/10 = ∑43/50, starting new job                        
2025-05-06 20:34:55: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 33/10/1 = ∑44/50, started new job               
2025-05-06 20:35:12: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 33/11 = ∑44/50, eval start                              
2025-05-06 20:35:29: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 33/11 = ∑44/50, starting new job                        
2025-05-06 20:35:51: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 34/10/1 = ∑45/50, started new job               
2025-05-06 20:36:11: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 34/10/1 = ∑45/50, eval start                    
2025-05-06 20:36:28: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 34/10/1 = ∑45/50, starting new job              
2025-05-06 20:36:46: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 44/1/1 = ∑46/50, started new job                
2025-05-06 20:37:07: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 45/1 = ∑46/50, eval start                               
2025-05-06 20:37:23: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 45/1 = ∑46/50, starting new job                         
2025-05-06 20:37:42: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 46/1 = ∑47/50, started new job                          
2025-05-06 20:37:59: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 46/1 = ∑47/50, eval start                               
2025-05-06 20:38:18: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 46/1 = ∑47/50, starting new job                         
2025-05-06 20:38:34: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 47/1 = ∑48/50, started new job                          
2025-05-06 20:38:51: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 47/1 = ∑48/50, eval start                               
2025-05-06 20:39:11: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 47/1 = ∑48/50, starting new job                         
2025-05-06 20:39:33: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 48/1 = ∑49/50, started new job                          
2025-05-06 20:39:53: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 48/1 = ∑49/50, eval start                               
2025-05-06 20:40:12: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 48/1 = ∑49/50, starting new job                         
2025-05-06 20:40:31: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 49/1 = ∑50/50, started new job                          
2025-05-06 20:40:52: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 49/1 = ∑50/50, new result: 0.368421052631579            
2025-05-06 20:41:32: BoTorchModel, best RESULT: 0.1947368421052632, completed 49 = ∑49/50, new result: 0.30000000000000004                    
2025-05-06 20:42:09: BoTorchModel, best RESULT: 0.1947368421052632, completed 48 = ∑48/50, new result: 0.25263157894736843                    
2025-05-06 20:42:42: BoTorchModel, best RESULT: 0.1947368421052632, completed 47 = ∑47/50, new result: 0.3631578947368421                     
2025-05-06 20:43:16: BoTorchModel, best RESULT: 0.1947368421052632, completed 46 = ∑46/50, new result: 0.3631578947368421                     
2025-05-06 20:43:51: BoTorchModel, best RESULT: 0.1947368421052632, completed 45 = ∑45/50, new result: 0.18947368421052635                    
2025-05-06 20:44:25: BoTorchModel, best RESULT: 0.18947368421052635, completed 44 = ∑44/50, new result: 0.3052631578947368                    
2025-05-06 20:44:58: BoTorchModel, best RESULT: 0.18947368421052635, completed 43 = ∑43/50, new result: 0.2578947368421053                    
2025-05-06 20:45:29: BoTorchModel, best RESULT: 0.18947368421052635, completed 42 = ∑42/50, new result: 0.3631578947368421                    
2025-05-06 20:46:00: BoTorchModel, best RESULT: 0.18947368421052635, completed 41 = ∑41/50, new result: 0.3631578947368421                    
2025-05-06 20:46:30: BoTorchModel, best RESULT: 0.18947368421052635, completed 40 = ∑40/50, new result: 0.3631578947368421                    
2025-05-06 20:47:03: BoTorchModel, best RESULT: 0.18947368421052635, completed 39 = ∑39/50, new result: 0.35789473684210527                   
2025-05-06 20:47:38: BoTorchModel, best RESULT: 0.18947368421052635, completed 38 = ∑38/50, new result: 0.3631578947368421                    
2025-05-06 20:48:09: BoTorchModel, best RESULT: 0.18947368421052635, completed 37 = ∑37/50, new result: 0.2421052631578947                    
2025-05-06 20:48:41: BoTorchModel, best RESULT: 0.18947368421052635, completed 36 = ∑36/50, new result: 0.33684210526315794                   
2025-05-06 20:49:14: BoTorchModel, best RESULT: 0.18947368421052635, completed 35 = ∑35/50, new result: 0.35789473684210527                   
2025-05-06 20:49:52: BoTorchModel, best RESULT: 0.18947368421052635, completed 34 = ∑34/50, new result: 0.22631578947368425                   
2025-05-06 20:50:25: BoTorchModel, best RESULT: 0.18947368421052635, completed 33 = ∑33/50, new result: 0.3631578947368421                    
2025-05-06 20:51:04: BoTorchModel, best RESULT: 0.18947368421052635, completed 32 = ∑32/50, new result: 0.24736842105263157                   
2025-05-06 20:51:37: BoTorchModel, best RESULT: 0.18947368421052635, completed 31 = ∑31/50, new result: 0.33684210526315794                   
2025-05-06 20:52:16: BoTorchModel, best RESULT: 0.18947368421052635, completed 30 = ∑30/50, new result: 0.3631578947368421                    
2025-05-06 20:52:55: BoTorchModel, best RESULT: 0.18947368421052635, completed 29 = ∑29/50, new result: 0.23684210526315785                   
2025-05-06 20:53:30: BoTorchModel, best RESULT: 0.18947368421052635, completed 28 = ∑28/50, new result: 0.32105263157894737                   
2025-05-06 20:54:10: BoTorchModel, best RESULT: 0.18947368421052635, completed 27 = ∑27/50, new result: 0.3315789473684211                    
2025-05-06 20:54:44: BoTorchModel, best RESULT: 0.18947368421052635, completed 26 = ∑26/50, new result: 0.34736842105263155                   
2025-05-06 20:55:36: BoTorchModel, best RESULT: 0.18947368421052635, completed 25 = ∑25/50, new result: 0.34736842105263155                   
2025-05-06 20:56:19: BoTorchModel, best RESULT: 0.18947368421052635, completed 24 = ∑24/50, new result: 0.2789473684210526                    
2025-05-06 20:56:59: BoTorchModel, best RESULT: 0.18947368421052635, completed 23 = ∑23/50, new result: 0.35789473684210527                   
2025-05-06 20:57:54: BoTorchModel, best RESULT: 0.18947368421052635, completed 22 = ∑22/50, new result: 0.2315789473684211                    
2025-05-06 20:58:43: BoTorchModel, best RESULT: 0.18947368421052635, completed 21 = ∑21/50, new result: 0.22631578947368425                   
2025-05-06 20:59:36: BoTorchModel, best RESULT: 0.18947368421052635, completed 20 = ∑20/50, new result: 0.26315789473684215                   
2025-05-06 21:00:31: BoTorchModel, best RESULT: 0.18947368421052635, completed 19 = ∑19/50, new result: 0.3631578947368421                    
2025-05-06 21:01:30: BoTorchModel, best RESULT: 0.18947368421052635, completed 18 = ∑18/50, new result: 0.3421052631578947                    
2025-05-06 21:02:29: BoTorchModel, best RESULT: 0.18947368421052635, completed 17 = ∑17/50, new result: 0.28421052631578947                   
2025-05-06 21:03:18: BoTorchModel, best RESULT: 0.18947368421052635, completed 16 = ∑16/50, new result: 0.28421052631578947                   
2025-05-06 21:03:58: BoTorchModel, best RESULT: 0.18947368421052635, completed 15 = ∑15/50, new result: 0.3631578947368421                    
2025-05-06 21:04:35: BoTorchModel, best RESULT: 0.18947368421052635, completed 14 = ∑14/50, new result: 0.2210526315789474                    
2025-05-06 21:05:12: BoTorchModel, best RESULT: 0.18947368421052635, completed 13 = ∑13/50, new result: 0.3052631578947368                    
2025-05-06 21:05:46: BoTorchModel, best RESULT: 0.18947368421052635, completed 12 = ∑12/50, new result: 0.2421052631578947                    
2025-05-06 21:06:25: BoTorchModel, best RESULT: 0.18947368421052635, completed 11 = ∑11/50, new result: 0.3052631578947368                    
2025-05-06 21:07:03: BoTorchModel, best RESULT: 0.18947368421052635, completed 10 = ∑10/50, new result: 0.21578947368421053                   
2025-05-06 21:07:36: BoTorchModel, best RESULT: 0.18947368421052635, completed 9 = ∑9/50, new result: 0.3052631578947368                      
2025-05-06 21:08:11: BoTorchModel, best RESULT: 0.18947368421052635, completed 8 = ∑8/50, new result: 0.33684210526315794                     
2025-05-06 21:08:46: BoTorchModel, best RESULT: 0.18947368421052635, completed 7 = ∑7/50, new result: 0.2421052631578947                      
2025-05-06 21:09:23: BoTorchModel, best RESULT: 0.18947368421052635, completed 6 = ∑6/50, new result: 0.3315789473684211                      
2025-05-06 21:09:58: BoTorchModel, best RESULT: 0.18947368421052635, completed 5 = ∑5/50, new result: 0.3631578947368421                      
2025-05-06 21:10:34: BoTorchModel, best RESULT: 0.18947368421052635, completed 4 = ∑4/50, new result: 0.2315789473684211                      
2025-05-06 21:11:15: BoTorchModel, best RESULT: 0.18947368421052635, completed 3 = ∑3/50, new result: 0.35789473684210527                     
2025-05-06 21:11:57: BoTorchModel, best RESULT: 0.18947368421052635, completed 2 = ∑2/50, new result: 0.23684210526315785                     
2025-05-06 21:12:38: BoTorchModel, best RESULT: 0.18947368421052635, completed 1 = ∑1/50, new result: 0.19999999999999996                     
2025-05-06 21:13:14: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs, finished 50 jobs                                         
2025-05-06 21:13:34: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #1/50                                                 
2025-05-06 21:14:12: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #2/50 | ETA: 14m 1s                                   
2025-05-06 21:14:37: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #3/50 | ETA: 10m 22s                                  
2025-05-06 21:15:03: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #4/50 | ETA: 8m 59s                                   
2025-05-06 21:15:28: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #5/50 | ETA: 8m 8s                                    
2025-05-06 21:16:00: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #6/50 | ETA: 7m 40s                                   
2025-05-06 21:16:28: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #7/50 | ETA: 7m 23s                                   
2025-05-06 21:16:56: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #8/50 | ETA: 7m 5s                                    
2025-05-06 21:17:21: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #9/50 | ETA: 6m 47s                                   
2025-05-06 21:17:54: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #10/50 | ETA: 6m 36s                                  
2025-05-06 21:18:22: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #11/50 | ETA: 6m 22s                                  
2025-05-06 21:18:53: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #12/50 | ETA: 6m 9s                                   
2025-05-06 21:19:20: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #13/50 | ETA: 5m 58s                                  
2025-05-06 21:19:51: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #14/50 | ETA: 5m 46s                                  
2025-05-06 21:20:17: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #15/50 | ETA: 5m 35s                                  
2025-05-06 21:20:52: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #16/50 | ETA: 5m 26s                                  
2025-05-06 21:21:21: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #17/50 | ETA: 5m 17s                                  
2025-05-06 21:21:52: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #18/50 | ETA: 5m 6s                                   
2025-05-06 21:22:20: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #19/50 | ETA: 4m 55s                                  
2025-05-06 21:22:52: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #20/50 | ETA: 4m 47s                                  
2025-05-06 21:23:22: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #21/50 | ETA: 4m 37s                                  
2025-05-06 21:23:51: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #22/50 | ETA: 4m 28s                                  
2025-05-06 21:24:18: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #23/50 | ETA: 4m 19s                                  
2025-05-06 21:24:46: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #24/50 | ETA: 4m 10s                                  
2025-05-06 21:25:10: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #25/50 | ETA: 4m 0s                                   
2025-05-06 21:25:40: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #26/50 | ETA: 3m 50s                                  
2025-05-06 21:26:04: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #27/50 | ETA: 3m 41s                                  
2025-05-06 21:26:30: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #28/50 | ETA: 3m 31s                                  
2025-05-06 21:26:55: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #29/50 | ETA: 3m 22s                                  
2025-05-06 21:27:21: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #30/50 | ETA: 3m 14s                                  
2025-05-06 21:27:50: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #31/50 | ETA: 3m 5s                                   
2025-05-06 21:28:16: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #32/50 | ETA: 2m 55s                                  
2025-05-06 21:28:46: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #33/50 | ETA: 2m 46s                                  
2025-05-06 21:29:11: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #34/50 | ETA: 2m 37s                                  
2025-05-06 21:29:40: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #35/50 | ETA: 2m 28s                                  
2025-05-06 21:30:05: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #36/50 | ETA: 2m 19s                                  
2025-05-06 21:30:33: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #37/50 | ETA: 2m 10s                                  
2025-05-06 21:31:00: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #38/50 | ETA: 2m 1s                                   
2025-05-06 21:31:29: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #39/50 | ETA: 1m 52s                                  
2025-05-06 21:31:55: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #40/50 | ETA: 1m 43s                                  
2025-05-06 21:32:24: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #41/50 | ETA: 1m 34s                                  
2025-05-06 21:32:52: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #42/50 | ETA: 1m 25s                                  
2025-05-06 21:33:23: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #43/50 | ETA: 1m 15s                                  
2025-05-06 21:33:48: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #44/50 | ETA: 1m 6s                                   
2025-05-06 21:34:20: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #45/50 | ETA: 57s                                     
2025-05-06 21:34:45: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #46/50 | ETA: 47s                                     
2025-05-06 21:35:11: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #47/50 | ETA: 38s                                     
2025-05-06 21:35:37: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #48/50 | ETA: 28s                                     
2025-05-06 21:36:05: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #49/50 | ETA: 19s                                     
2025-05-06 21:36:29: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #50/50 | ETA: 9s                                      
2025-05-06 21:36:55: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                               
2025-05-06 21:37:09: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                         
2025-05-06 21:37:25: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1 = ∑1/50, started new job                                       
2025-05-06 21:37:39: BoTorchModel, best RESULT: 0.18947368421052635, pending 1 = ∑1/50, eval start                                            
2025-05-06 21:37:57: BoTorchModel, best RESULT: 0.18947368421052635, running 1 = ∑1/50, starting new job                                      
2025-05-06 21:38:14: BoTorchModel, best RESULT: 0.18947368421052635, running/unknown 1/1 = ∑2/50, started new job                             
2025-05-06 21:38:30: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1 = ∑2/50, eval start                                
2025-05-06 21:38:47: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1 = ∑2/50, starting new job                          
2025-05-06 21:39:04: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 1/1/1 = ∑3/50, started new job                 
2025-05-06 21:39:19: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 2/1 = ∑3/50, eval start                                
2025-05-06 21:39:36: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 2/1 = ∑3/50, starting new job                          
2025-05-06 21:39:54: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 3/1 = ∑4/50, started new job                           
2025-05-06 21:40:09: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 3/1 = ∑4/50, eval start                                
2025-05-06 21:40:27: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 3/1 = ∑4/50, starting new job                          
2025-05-06 21:40:49: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 4/1 = ∑5/50, started new job                           
2025-05-06 21:41:04: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 4/1 = ∑5/50, eval start                                
2025-05-06 21:41:19: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 4/1 = ∑5/50, starting new job                          
2025-05-06 21:41:37: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 4/1/1 = ∑6/50, started new job                 
2025-05-06 21:41:55: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 5/1 = ∑6/50, eval start                                
2025-05-06 21:42:10: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 5/1 = ∑6/50, starting new job                          
2025-05-06 21:42:28: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 6/1 = ∑7/50, started new job                           
2025-05-06 21:42:47: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 6/1 = ∑7/50, eval start                                
2025-05-06 21:43:04: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 6/1 = ∑7/50, starting new job                          
2025-05-06 21:43:20: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 6/1/1 = ∑8/50, started new job                 
2025-05-06 21:43:38: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 7/1 = ∑8/50, eval start                                
2025-05-06 21:43:54: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 7/1 = ∑8/50, starting new job                          
2025-05-06 21:44:10: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 7/1/1 = ∑9/50, started new job                 
2025-05-06 21:44:26: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 8/1 = ∑9/50, eval start                                
2025-05-06 21:44:43: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 8/1 = ∑9/50, starting new job                          
2025-05-06 21:45:00: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 8/1/1 = ∑10/50, started new job                
2025-05-06 21:45:16: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/pending 8/1/1 = ∑10/50, eval start                     
2025-05-06 21:45:31: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/pending 8/1/1 = ∑10/50, starting new job               
2025-05-06 21:45:50: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 9/1/1 = ∑11/50, started new job                
2025-05-06 21:46:04: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 9/2 = ∑11/50, eval start                               
2025-05-06 21:46:20: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 9/2 = ∑11/50, starting new job                         
2025-05-06 21:46:38: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 10/1/1 = ∑12/50, started new job               
2025-05-06 21:46:53: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 11/1 = ∑12/50, eval start                              
2025-05-06 21:47:08: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 11/1 = ∑12/50, starting new job                        
2025-05-06 21:47:25: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 11/1/1 = ∑13/50, started new job               
2025-05-06 21:47:45: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 11/2 = ∑13/50, eval start                              
2025-05-06 21:48:04: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 11/2 = ∑13/50, starting new job                        
2025-05-06 21:48:25: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 12/1/1 = ∑14/50, started new job               
2025-05-06 21:48:46: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 13/1 = ∑14/50, eval start                              
2025-05-06 21:49:03: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 13/1 = ∑14/50, starting new job                        
2025-05-06 21:49:21: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 14/1 = ∑15/50, started new job                         
2025-05-06 21:49:39: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 14/1 = ∑15/50, eval start                              
2025-05-06 21:49:55: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 14/1 = ∑15/50, starting new job                        
2025-05-06 21:50:12: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 14/1/1 = ∑16/50, started new job               
2025-05-06 21:50:28: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 15/1 = ∑16/50, eval start                              
2025-05-06 21:50:45: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 15/1 = ∑16/50, starting new job                        
2025-05-06 21:51:03: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 15/1/1 = ∑17/50, started new job               
2025-05-06 21:51:18: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/pending 15/1/1 = ∑17/50, eval start                    
2025-05-06 21:51:35: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/pending 15/1/1 = ∑17/50, starting new job              
2025-05-06 21:51:55: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 16/1/1 = ∑18/50, started new job               
2025-05-06 21:52:11: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 16/2 = ∑18/50, eval start                              
2025-05-06 21:52:29: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 17/1 = ∑18/50, starting new job                        
2025-05-06 21:52:49: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 17/1/1 = ∑19/50, started new job               
2025-05-06 21:53:08: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 18/1 = ∑19/50, eval start                              
2025-05-06 21:53:25: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 18/1 = ∑19/50, starting new job                        
2025-05-06 21:53:42: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 18/1/1 = ∑20/50, started new job               
2025-05-06 21:53:59: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 19/1 = ∑20/50, eval start                              
2025-05-06 21:54:16: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 19/1 = ∑20/50, starting new job                        
2025-05-06 21:54:33: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 19/1/1 = ∑21/50, started new job               
2025-05-06 21:54:52: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 20/1 = ∑21/50, eval start                              
2025-05-06 21:55:08: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 20/1 = ∑21/50, starting new job                        
2025-05-06 21:55:27: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 20/1/1 = ∑22/50, started new job               
2025-05-06 21:55:42: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 21/1 = ∑22/50, eval start                              
2025-05-06 21:56:02: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 21/1 = ∑22/50, starting new job                        
2025-05-06 21:56:19: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 21/1/1 = ∑23/50, started new job               
2025-05-06 21:56:35: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 22/1 = ∑23/50, eval start                              
2025-05-06 21:56:55: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 22/1 = ∑23/50, starting new job                        
2025-05-06 21:57:13: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 22/1/1 = ∑24/50, started new job               
2025-05-06 21:57:30: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 23/1 = ∑24/50, eval start                              
2025-05-06 21:57:47: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 23/1 = ∑24/50, starting new job                        
2025-05-06 21:58:08: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 23/1/1 = ∑25/50, started new job               
2025-05-06 21:58:25: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 23/2 = ∑25/50, eval start                              
2025-05-06 21:58:41: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 23/2 = ∑25/50, starting new job                        
2025-05-06 21:59:02: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 25/1 = ∑26/50, started new job                         
2025-05-06 21:59:20: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 25/1 = ∑26/50, eval start                              
2025-05-06 21:59:38: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 25/1 = ∑26/50, starting new job                        
2025-05-06 21:59:59: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 25/1/1 = ∑27/50, started new job               
2025-05-06 22:00:15: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 26/1 = ∑27/50, eval start                              
2025-05-06 22:00:35: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 26/1 = ∑27/50, starting new job                        
2025-05-06 22:00:55: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 26/1/1 = ∑28/50, started new job               
2025-05-06 22:01:11: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 27/1 = ∑28/50, eval start                              
2025-05-06 22:01:28: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 27/1 = ∑28/50, starting new job                        
2025-05-06 22:01:47: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 27/1/1 = ∑29/50, started new job               
2025-05-06 22:02:05: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/pending 27/1/1 = ∑29/50, eval start                    
2025-05-06 22:02:22: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/pending 27/1/1 = ∑29/50, starting new job              
2025-05-06 22:02:39: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 28/1/1 = ∑30/50, started new job               
2025-05-06 22:02:57: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 28/2 = ∑30/50, eval start                              
2025-05-06 22:03:15: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 28/2 = ∑30/50, starting new job                        
2025-05-06 22:03:33: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 30/1 = ∑31/50, started new job                         
2025-05-06 22:03:50: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 30/1 = ∑31/50, eval start                              
2025-05-06 22:04:08: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 30/1 = ∑31/50, starting new job                        
2025-05-06 22:04:25: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 30/1/1 = ∑32/50, started new job               
2025-05-06 22:04:43: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 31/1 = ∑32/50, eval start                              
2025-05-06 22:05:00: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 31/1 = ∑32/50, starting new job                        
2025-05-06 22:05:18: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 31/1/1 = ∑33/50, started new job               
2025-05-06 22:05:36: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 31/2 = ∑33/50, eval start                              
2025-05-06 22:05:53: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 31/2 = ∑33/50, starting new job                        
2025-05-06 22:06:11: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 33/1 = ∑34/50, started new job                         
2025-05-06 22:06:27: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 33/1 = ∑34/50, eval start                              
2025-05-06 22:06:46: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 33/1 = ∑34/50, starting new job                        
2025-05-06 22:07:05: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 33/1/1 = ∑35/50, started new job               
2025-05-06 22:07:21: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 34/1 = ∑35/50, eval start                              
2025-05-06 22:07:44: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 34/1 = ∑35/50, starting new job                        
2025-05-06 22:08:03: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 34/1/1 = ∑36/50, started new job               
2025-05-06 22:08:18: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/pending 34/1/1 = ∑36/50, eval start                    
2025-05-06 22:08:40: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 35/1 = ∑36/50, starting new job                        
2025-05-06 22:09:00: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 35/1/1 = ∑37/50, started new job               
2025-05-06 22:09:18: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/pending 35/1/1 = ∑37/50, eval start                    
2025-05-06 22:09:39: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 36/1 = ∑37/50, starting new job                        
2025-05-06 22:09:58: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 36/1/1 = ∑38/50, started new job               
2025-05-06 22:10:16: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 36/2 = ∑38/50, eval start                              
2025-05-06 22:10:39: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 37/1 = ∑38/50, starting new job                        
2025-05-06 22:10:59: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 38/1 = ∑39/50, started new job                         
2025-05-06 22:11:17: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 38/1 = ∑39/50, eval start                              
2025-05-06 22:11:38: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 38/1 = ∑39/50, starting new job                        
2025-05-06 22:11:59: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 38/1/1 = ∑40/50, started new job               
2025-05-06 22:12:19: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 39/1 = ∑40/50, eval start                              
2025-05-06 22:12:40: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 39/1 = ∑40/50, starting new job                        
2025-05-06 22:12:59: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 39/1/1 = ∑41/50, started new job               
2025-05-06 22:13:20: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 40/1 = ∑41/50, eval start                              
2025-05-06 22:13:43: BoTorchModel, best RESULT: 0.18947368421052635, completed 41 = ∑41/50, starting new job                                  
2025-05-06 22:14:06: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 41/1 = ∑42/50, started new job                         
2025-05-06 22:14:27: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 41/1 = ∑42/50, eval start                              
2025-05-06 22:14:44: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 41/1 = ∑42/50, starting new job                        
2025-05-06 22:15:05: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 42/1 = ∑43/50, started new job                         
2025-05-06 22:15:27: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 42/1 = ∑43/50, eval start                              
2025-05-06 22:15:46: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 42/1 = ∑43/50, starting new job                        
2025-05-06 22:16:07: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 43/1 = ∑44/50, started new job                         
2025-05-06 22:16:29: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 43/1 = ∑44/50, eval start                              
2025-05-06 22:16:49: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 43/1 = ∑44/50, starting new job                        
2025-05-06 22:17:11: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 44/1 = ∑45/50, started new job                         
2025-05-06 22:17:36: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 44/1 = ∑45/50, eval start                              
2025-05-06 22:18:00: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 44/1 = ∑45/50, starting new job                        
2025-05-06 22:18:24: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 45/1 = ∑46/50, started new job                         
2025-05-06 22:18:44: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 45/1 = ∑46/50, eval start                              
2025-05-06 22:19:05: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 45/1 = ∑46/50, starting new job                        
2025-05-06 22:19:28: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 46/1 = ∑47/50, started new job                         
2025-05-06 22:19:47: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 46/1 = ∑47/50, eval start                              
2025-05-06 22:20:14: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 46/1 = ∑47/50, starting new job                        
2025-05-06 22:20:37: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 47/1 = ∑48/50, started new job                         
2025-05-06 22:20:55: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 47/1 = ∑48/50, eval start                              
2025-05-06 22:21:14: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 47/1 = ∑48/50, starting new job                        
2025-05-06 22:21:34: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 48/1 = ∑49/50, started new job                         
2025-05-06 22:21:52: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 48/1 = ∑49/50, eval start                              
2025-05-06 22:22:12: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 48/1 = ∑49/50, starting new job                        
2025-05-06 22:22:36: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 48/1/1 = ∑50/50, started new job               
2025-05-06 22:22:59: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 49/1 = ∑50/50, new result: 0.19999999999999996         
2025-05-06 22:23:44: BoTorchModel, best RESULT: 0.18947368421052635, completed 49 = ∑49/50, new result: 0.2684210526315789                    
2025-05-06 22:24:20: BoTorchModel, best RESULT: 0.18947368421052635, completed 48 = ∑48/50, new result: 0.28421052631578947                   
2025-05-06 22:24:56: BoTorchModel, best RESULT: 0.18947368421052635, completed 47 = ∑47/50, new result: 0.24736842105263157                   
2025-05-06 22:25:30: BoTorchModel, best RESULT: 0.18947368421052635, completed 46 = ∑46/50, new result: 0.26315789473684215                   
2025-05-06 22:26:06: BoTorchModel, best RESULT: 0.18947368421052635, completed 45 = ∑45/50, new result: 0.20526315789473681                   
2025-05-06 22:26:44: BoTorchModel, best RESULT: 0.18947368421052635, completed 44 = ∑44/50, new result: 0.35789473684210527                   
2025-05-06 22:27:20: BoTorchModel, best RESULT: 0.18947368421052635, completed 43 = ∑43/50, new result: 0.26315789473684215                   
2025-05-06 22:27:56: BoTorchModel, best RESULT: 0.18947368421052635, completed 42 = ∑42/50, new result: 0.33684210526315794                   
2025-05-06 22:28:33: BoTorchModel, best RESULT: 0.18947368421052635, completed 41 = ∑41/50, new result: 0.2210526315789474                    
2025-05-06 22:29:08: BoTorchModel, best RESULT: 0.18947368421052635, completed 40 = ∑40/50, new result: 0.24736842105263157                   
2025-05-06 22:29:43: BoTorchModel, best RESULT: 0.18947368421052635, completed 39 = ∑39/50, new result: 0.2578947368421053                    
2025-05-06 22:30:17: BoTorchModel, best RESULT: 0.18947368421052635, completed 38 = ∑38/50, new result: 0.41052631578947374                   
2025-05-06 22:30:52: BoTorchModel, best RESULT: 0.18947368421052635, completed 37 = ∑37/50, new result: 0.26315789473684215                   
2025-05-06 22:31:31: BoTorchModel, best RESULT: 0.18947368421052635, completed 36 = ∑36/50, new result: 0.1842105263157895                    
2025-05-06 22:32:07: BoTorchModel, best RESULT: 0.1842105263157895, completed 35 = ∑35/50, new result: 0.22631578947368425                    
2025-05-06 22:32:47: BoTorchModel, best RESULT: 0.1842105263157895, completed 34 = ∑34/50, new result: 0.34736842105263155                    
2025-05-06 22:33:25: BoTorchModel, best RESULT: 0.1842105263157895, completed 33 = ∑33/50, new result: 0.2947368421052632                     
2025-05-06 22:34:01: BoTorchModel, best RESULT: 0.1842105263157895, completed 32 = ∑32/50, new result: 0.20526315789473681                    
2025-05-06 22:34:42: BoTorchModel, best RESULT: 0.1842105263157895, completed 31 = ∑31/50, new result: 0.2578947368421053                     
2025-05-06 22:35:23: BoTorchModel, best RESULT: 0.1842105263157895, completed 30 = ∑30/50, new result: 0.3631578947368421                     
2025-05-06 22:35:59: BoTorchModel, best RESULT: 0.1842105263157895, completed 29 = ∑29/50, new result: 0.3631578947368421                     
2025-05-06 22:36:38: BoTorchModel, best RESULT: 0.1842105263157895, completed 28 = ∑28/50, new result: 0.22631578947368425                    
2025-05-06 22:37:16: BoTorchModel, best RESULT: 0.1842105263157895, completed 27 = ∑27/50, new result: 0.2315789473684211                     
2025-05-06 22:37:50: BoTorchModel, best RESULT: 0.1842105263157895, completed 26 = ∑26/50, new result: 0.1947368421052632                     
2025-05-06 22:38:25: BoTorchModel, best RESULT: 0.1842105263157895, completed 25 = ∑25/50, new result: 0.28421052631578947                    
2025-05-06 22:38:59: BoTorchModel, best RESULT: 0.1842105263157895, completed 24 = ∑24/50, new result: 0.25263157894736843                    
2025-05-06 22:39:34: BoTorchModel, best RESULT: 0.1842105263157895, completed 23 = ∑23/50, new result: 0.3631578947368421                     
2025-05-06 22:40:11: BoTorchModel, best RESULT: 0.1842105263157895, completed 22 = ∑22/50, new result: 0.3052631578947368                     
2025-05-06 22:40:47: BoTorchModel, best RESULT: 0.1842105263157895, completed 21 = ∑21/50, new result: 0.3052631578947368                     
2025-05-06 22:41:32: BoTorchModel, best RESULT: 0.1842105263157895, completed 20 = ∑20/50, new result: 0.2210526315789474                     
2025-05-06 22:42:16: BoTorchModel, best RESULT: 0.1842105263157895, completed 19 = ∑19/50, new result: 0.28421052631578947                    
2025-05-06 22:42:59: BoTorchModel, best RESULT: 0.1842105263157895, completed 18 = ∑18/50, new result: 0.3263157894736842                     
2025-05-06 22:43:37: BoTorchModel, best RESULT: 0.1842105263157895, completed 17 = ∑17/50, new result: 0.25263157894736843                    
2025-05-06 22:44:16: BoTorchModel, best RESULT: 0.1842105263157895, completed 16 = ∑16/50, new result: 0.28421052631578947                    
2025-05-06 22:44:51: BoTorchModel, best RESULT: 0.1842105263157895, completed 15 = ∑15/50, new result: 0.20526315789473681                    
2025-05-06 22:45:32: BoTorchModel, best RESULT: 0.1842105263157895, completed 14 = ∑14/50, new result: 0.3052631578947368                     
2025-05-06 22:46:11: BoTorchModel, best RESULT: 0.1842105263157895, completed 13 = ∑13/50, new result: 0.34736842105263155                    
2025-05-06 22:46:46: BoTorchModel, best RESULT: 0.1842105263157895, completed 12 = ∑12/50, new result: 0.25263157894736843                    
2025-05-06 22:47:22: BoTorchModel, best RESULT: 0.1842105263157895, completed 11 = ∑11/50, new result: 0.24736842105263157                    
2025-05-06 22:47:59: BoTorchModel, best RESULT: 0.1842105263157895, completed 10 = ∑10/50, new result: 0.21578947368421053                    
2025-05-06 22:48:34: BoTorchModel, best RESULT: 0.1842105263157895, completed 9 = ∑9/50, new result: 0.21052631578947367                      
2025-05-06 22:49:09: BoTorchModel, best RESULT: 0.1842105263157895, completed 8 = ∑8/50, new result: 0.32105263157894737                      
2025-05-06 22:49:43: BoTorchModel, best RESULT: 0.1842105263157895, completed 7 = ∑7/50, new result: 0.2578947368421053                       
2025-05-06 22:50:18: BoTorchModel, best RESULT: 0.1842105263157895, completed 6 = ∑6/50, new result: 0.24736842105263157                      
2025-05-06 22:50:51: BoTorchModel, best RESULT: 0.1842105263157895, completed 5 = ∑5/50, new result: 0.2894736842105263                       
2025-05-06 22:51:25: BoTorchModel, best RESULT: 0.1842105263157895, completed 4 = ∑4/50, new result: 0.2894736842105263                       
2025-05-06 22:52:02: BoTorchModel, best RESULT: 0.1842105263157895, completed 3 = ∑3/50, new result: 0.35789473684210527                      
2025-05-06 22:52:36: BoTorchModel, best RESULT: 0.1842105263157895, completed 2 = ∑2/50, new result: 0.26315789473684215                      
2025-05-06 22:53:13: BoTorchModel, best RESULT: 0.1842105263157895, completed 1 = ∑1/50, new result: 0.3631578947368421                       
2025-05-06 22:53:50: BoTorchModel, best RESULT: 0.1842105263157895, finishing jobs, finished 50 jobs                                          
2025-05-06 22:54:12: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #1/50                                                  
2025-05-06 22:54:48: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #2/50 | ETA: 14m 24s                                   
2025-05-06 22:55:21: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #3/50 | ETA: 11m 55s                                   
2025-05-06 22:55:50: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #4/50 | ETA: 11m 19s                                   
2025-05-06 22:56:24: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #5/50 | ETA: 11m 0s                                    
2025-05-06 22:56:54: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #6/50 | ETA: 10m 38s                                   
2025-05-06 22:57:26: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #7/50 | ETA: 10m 21s                                   
2025-05-06 22:58:00: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #8/50 | ETA: 9m 59s                                    
2025-05-06 22:58:30: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #9/50 | ETA: 9m 37s                                    
2025-05-06 22:59:04: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #10/50 | ETA: 9m 22s                                   
2025-05-06 22:59:36: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #11/50 | ETA: 9m 2s                                    
2025-05-06 23:00:09: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #12/50 | ETA: 8m 49s                                   
2025-05-06 23:00:43: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #13/50 | ETA: 8m 33s                                   
2025-05-06 23:01:17: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #14/50 | ETA: 8m 14s                                   
2025-05-06 23:01:50: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #15/50 | ETA: 8m 1s                                    
2025-05-06 23:02:21: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #16/50 | ETA: 7m 49s                                   
2025-05-06 23:02:52: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #17/50 | ETA: 7m 34s                                   
2025-05-06 23:03:25: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #18/50 | ETA: 7m 21s                                   
2025-05-06 23:04:01: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #19/50 | ETA: 7m 8s                                    
2025-05-06 23:04:34: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #20/50 | ETA: 6m 55s                                   
2025-05-06 23:05:03: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #21/50 | ETA: 6m 39s                                   
2025-05-06 23:05:36: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #22/50 | ETA: 6m 26s                                   
2025-05-06 23:06:09: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #23/50 | ETA: 6m 12s                                   
2025-05-06 23:06:41: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #24/50 | ETA: 6m 0s                                    
2025-05-06 23:07:14: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #25/50 | ETA: 5m 46s                                   
2025-05-06 23:07:46: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #26/50 | ETA: 5m 33s                                   
2025-05-06 23:08:16: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #27/50 | ETA: 5m 19s                                   
2025-05-06 23:08:56: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #28/50 | ETA: 5m 6s                                    
2025-05-06 23:09:32: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #29/50 | ETA: 4m 53s                                   
2025-05-06 23:10:05: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #30/50 | ETA: 4m 40s                                   
2025-05-06 23:10:40: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #31/50 | ETA: 4m 28s                                   
2025-05-06 23:11:11: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #32/50 | ETA: 4m 14s                                   
2025-05-06 23:11:47: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #33/50 | ETA: 4m 1s                                    
2025-05-06 23:12:20: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #34/50 | ETA: 3m 47s                                   
2025-05-06 23:12:57: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #35/50 | ETA: 3m 34s                                   
2025-05-06 23:13:28: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #36/50 | ETA: 3m 21s                                   
2025-05-06 23:14:02: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #37/50 | ETA: 3m 7s                                    
2025-05-06 23:14:36: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #38/50 | ETA: 2m 54s                                   
2025-05-06 23:15:09: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #39/50 | ETA: 2m 41s                                   
2025-05-06 23:15:45: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #40/50 | ETA: 2m 28s                                   
2025-05-06 23:16:19: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #41/50 | ETA: 2m 15s                                   
2025-05-06 23:16:52: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #42/50 | ETA: 2m 2s                                    
2025-05-06 23:17:25: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #43/50 | ETA: 1m 48s                                   
2025-05-06 23:17:58: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #44/50 | ETA: 1m 35s                                   
2025-05-06 23:18:38: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #45/50 | ETA: 1m 21s                                   
2025-05-06 23:19:16: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #46/50 | ETA: 1m 8s                                    
2025-05-06 23:19:48: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #47/50 | ETA: 54s                                      
2025-05-06 23:20:25: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #48/50 | ETA: 41s                                      
2025-05-06 23:20:58: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #49/50 | ETA: 27s                                      
2025-05-06 23:21:34: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #50/50 | ETA: 13s                                      
2025-05-06 23:22:06: BoTorchModel, best RESULT: 0.1842105263157895, eval start                                                                
2025-05-06 23:22:24: BoTorchModel, best RESULT: 0.1842105263157895, starting new job                                                          
2025-05-06 23:22:42: BoTorchModel, best RESULT: 0.1842105263157895, unknown 1 = ∑1/50, started new job                                        
2025-05-06 23:23:03: BoTorchModel, best RESULT: 0.1842105263157895, running 1 = ∑1/50, eval start                                             
2025-05-06 23:23:22: BoTorchModel, best RESULT: 0.1842105263157895, running 1 = ∑1/50, starting new job                                       
2025-05-06 23:23:42: BoTorchModel, best RESULT: 0.1842105263157895, running/unknown 1/1 = ∑2/50, started new job                              
2025-05-06 23:24:02: BoTorchModel, best RESULT: 0.1842105263157895, running 2 = ∑2/50, eval start                                             
2025-05-06 23:24:21: BoTorchModel, best RESULT: 0.1842105263157895, running 2 = ∑2/50, starting new job                                       
2025-05-06 23:24:40: BoTorchModel, best RESULT: 0.1842105263157895, running/unknown 2/1 = ∑3/50, started new job                              
2025-05-06 23:24:58: BoTorchModel, best RESULT: 0.1842105263157895, running/completed 2/1 = ∑3/50, eval start                                 
2025-05-06 23:25:17: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 2/1 = ∑3/50, starting new job                           
2025-05-06 23:25:37: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/unknown 2/1/1 = ∑4/50, started new job                  
2025-05-06 23:26:00: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 3/1 = ∑4/50, eval start                                 
2025-05-06 23:26:23: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 3/1 = ∑4/50, starting new job                           
2025-05-06 23:26:45: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/unknown 3/1/1 = ∑5/50, started new job                  
2025-05-06 23:27:04: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 4/1 = ∑5/50, eval start                                 
2025-05-06 23:27:24: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 4/1 = ∑5/50, starting new job                           
2025-05-06 23:27:47: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/unknown 4/1/1 = ∑6/50, started new job                  
2025-05-06 23:28:05: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 5/1 = ∑6/50, eval start                                 
2025-05-06 23:28:23: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 5/1 = ∑6/50, starting new job                           
2025-05-06 23:28:45: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 6/1 = ∑7/50, started new job                            
2025-05-06 23:29:04: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 6/1 = ∑7/50, eval start                                 
2025-05-06 23:29:23: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 6/1 = ∑7/50, starting new job                           
2025-05-06 23:29:45: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/unknown 6/1/1 = ∑8/50, started new job                  
2025-05-06 23:30:04: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 6/2 = ∑8/50, eval start                                 
2025-05-06 23:30:22: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 6/2 = ∑8/50, starting new job                           
2025-05-06 23:30:41: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 8/1 = ∑9/50, started new job                            
2025-05-06 23:30:59: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 8/1 = ∑9/50, eval start                                 
2025-05-06 23:31:17: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 8/1 = ∑9/50, starting new job                           
2025-05-06 23:31:41: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/unknown 8/1/1 = ∑10/50, started new job                 
2025-05-06 23:32:32: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 9/1 = ∑10/50, eval start                                
2025-05-06 23:32:52: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 9/1 = ∑10/50, starting new job                          
2025-05-06 23:33:11: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 10/1 = ∑11/50, started new job                          
2025-05-06 23:33:32: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 10/1 = ∑11/50, eval start                               
2025-05-06 23:33:49: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 10/1 = ∑11/50, starting new job                         
2025-05-06 23:34:10: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/unknown 10/1/1 = ∑12/50, started new job                
2025-05-06 23:34:29: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/pending 10/1/1 = ∑12/50, eval start                     
2025-05-06 23:34:47: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/pending 10/1/1 = ∑12/50, starting new job               
2025-05-06 23:35:06: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/unknown 11/1/1 = ∑13/50, started new job                
2025-05-06 23:35:25: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 12/1 = ∑13/50, eval start                               
2025-05-06 23:35:42: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 12/1 = ∑13/50, starting new job                         
2025-05-06 23:36:02: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/unknown 12/1/1 = ∑14/50, started new job                
2025-05-06 23:36:22: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 12/2 = ∑14/50, eval start                               
2025-05-06 23:36:40: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 12/2 = ∑14/50, starting new job                         
2025-05-06 23:37:01: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 14/1 = ∑15/50, started new job                          
2025-05-06 23:37:20: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 14/1 = ∑15/50, eval start                               
2025-05-06 23:37:38: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 14/1 = ∑15/50, starting new job                         
2025-05-06 23:38:00: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/unknown 14/1/1 = ∑16/50, started new job                
2025-05-06 23:38:20: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 15/1 = ∑16/50, eval start                               
2025-05-06 23:38:41: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 15/1 = ∑16/50, starting new job                         
2025-05-06 23:39:01: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/unknown 15/1/1 = ∑17/50, started new job                
2025-05-06 23:39:20: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 16/1 = ∑17/50, eval start                               
2025-05-06 23:39:39: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 16/1 = ∑17/50, starting new job                         
2025-05-06 23:39:56: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/unknown 16/1/1 = ∑18/50, started new job                
2025-05-06 23:40:13: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 17/1 = ∑18/50, eval start                               
2025-05-06 23:40:30: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 17/1 = ∑18/50, starting new job                         
2025-05-06 23:40:48: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 18/1 = ∑19/50, started new job                          
2025-05-06 23:41:06: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 18/1 = ∑19/50, eval start                               
2025-05-06 23:41:22: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 18/1 = ∑19/50, starting new job                         
2025-05-06 23:41:41: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/unknown 18/1/1 = ∑20/50, started new job                
2025-05-06 23:41:59: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 19/1 = ∑20/50, eval start                               
2025-05-06 23:42:15: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 19/1 = ∑20/50, starting new job                         
2025-05-06 23:42:33: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 20/1 = ∑21/50, started new job                          
2025-05-06 23:42:51: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 20/1 = ∑21/50, eval start                               
2025-05-06 23:43:09: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 20/1 = ∑21/50, starting new job                         
2025-05-06 23:43:27: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 21/1 = ∑22/50, started new job                          
2025-05-06 23:43:43: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 21/1 = ∑22/50, eval start                               
2025-05-06 23:44:01: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 21/1 = ∑22/50, starting new job                         
2025-05-06 23:44:20: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 22/1 = ∑23/50, started new job                          
2025-05-06 23:44:37: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 22/1 = ∑23/50, eval start                               
2025-05-06 23:44:54: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 22/1 = ∑23/50, starting new job                         
2025-05-06 23:45:12: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 23/1 = ∑24/50, started new job                          
2025-05-06 23:45:29: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 23/1 = ∑24/50, eval start                               
2025-05-06 23:45:45: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 23/1 = ∑24/50, starting new job                         
2025-05-06 23:46:02: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 24/1 = ∑25/50, started new job                          
2025-05-06 23:46:19: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 24/1 = ∑25/50, eval start                               
2025-05-06 23:46:37: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 24/1 = ∑25/50, starting new job                         
2025-05-06 23:46:54: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 25/1 = ∑26/50, started new job                          
2025-05-06 23:47:11: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 25/1 = ∑26/50, eval start                               
2025-05-06 23:47:28: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 25/1 = ∑26/50, starting new job                         
2025-05-06 23:47:46: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/unknown 25/1/1 = ∑27/50, started new job                
2025-05-06 23:48:04: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 26/1 = ∑27/50, eval start                               
2025-05-06 23:48:20: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 26/1 = ∑27/50, starting new job                         
2025-05-06 23:48:38: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 27/1 = ∑28/50, started new job                          
2025-05-06 23:48:54: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 27/1 = ∑28/50, eval start                               
2025-05-06 23:49:11: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 27/1 = ∑28/50, starting new job                         
2025-05-06 23:49:28: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/unknown 27/1/1 = ∑29/50, started new job                
2025-05-06 23:49:44: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 28/1 = ∑29/50, eval start                               
2025-05-06 23:50:01: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 28/1 = ∑29/50, starting new job                         
2025-05-06 23:50:19: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 29/1 = ∑30/50, started new job                          
2025-05-06 23:50:36: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 29/1 = ∑30/50, eval start                               
2025-05-06 23:50:54: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 29/1 = ∑30/50, starting new job                         
2025-05-06 23:51:12: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 30/1 = ∑31/50, started new job                          
2025-05-06 23:51:29: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 30/1 = ∑31/50, eval start                               
2025-05-06 23:51:46: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 30/1 = ∑31/50, starting new job                         
2025-05-06 23:52:05: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 31/1 = ∑32/50, started new job                          
2025-05-06 23:52:22: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 31/1 = ∑32/50, eval start                               
2025-05-06 23:52:39: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 31/1 = ∑32/50, starting new job                         
2025-05-06 23:52:57: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 32/1 = ∑33/50, started new job                          
2025-05-06 23:53:15: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 32/1 = ∑33/50, eval start                               
2025-05-06 23:53:32: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 32/1 = ∑33/50, starting new job                         
2025-05-06 23:53:50: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 33/1 = ∑34/50, started new job                          
2025-05-06 23:54:08: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 33/1 = ∑34/50, eval start                               
2025-05-06 23:54:26: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 33/1 = ∑34/50, starting new job                         
2025-05-06 23:54:52: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 34/1 = ∑35/50, started new job                          
2025-05-06 23:55:10: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 34/1 = ∑35/50, eval start                               
2025-05-06 23:55:28: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 34/1 = ∑35/50, starting new job                         
2025-05-06 23:55:48: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 35/1 = ∑36/50, started new job                          
2025-05-06 23:56:06: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 35/1 = ∑36/50, eval start                               
2025-05-06 23:56:26: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 35/1 = ∑36/50, starting new job                         
2025-05-06 23:56:46: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 36/1 = ∑37/50, started new job                          
2025-05-06 23:57:06: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 36/1 = ∑37/50, eval start                               
2025-05-06 23:57:25: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 36/1 = ∑37/50, starting new job                         
2025-05-06 23:57:46: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/unknown 36/1/1 = ∑38/50, started new job                
2025-05-06 23:58:04: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 37/1 = ∑38/50, eval start                               
2025-05-06 23:58:22: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 37/1 = ∑38/50, starting new job                         
2025-05-06 23:58:41: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 38/1 = ∑39/50, started new job                          
2025-05-06 23:59:00: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 38/1 = ∑39/50, eval start                               
2025-05-06 23:59:18: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 38/1 = ∑39/50, starting new job                         
2025-05-06 23:59:38: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/unknown 38/1/1 = ∑40/50, started new job                
2025-05-06 23:59:57: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 39/1 = ∑40/50, eval start                               
2025-05-07 00:00:16: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 39/1 = ∑40/50, starting new job                         
2025-05-07 00:00:36: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 40/1 = ∑41/50, started new job                          
2025-05-07 00:00:55: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 40/1 = ∑41/50, eval start                               
2025-05-07 00:01:15: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 40/1 = ∑41/50, starting new job                         
2025-05-07 00:01:35: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/unknown 40/1/1 = ∑42/50, started new job                
2025-05-07 00:01:55: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 41/1 = ∑42/50, eval start                               
2025-05-07 00:02:14: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 41/1 = ∑42/50, starting new job                         
2025-05-07 00:02:34: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 42/1 = ∑43/50, started new job                          
2025-05-07 00:02:54: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 42/1 = ∑43/50, eval start                               
2025-05-07 00:03:13: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 42/1 = ∑43/50, starting new job                         
2025-05-07 00:03:33: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 43/1 = ∑44/50, started new job                          
2025-05-07 00:03:52: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 43/1 = ∑44/50, eval start                               
2025-05-07 00:04:12: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 43/1 = ∑44/50, starting new job                         
2025-05-07 00:04:32: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 44/1 = ∑45/50, started new job                          
2025-05-07 00:04:51: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 44/1 = ∑45/50, eval start                               
2025-05-07 00:05:11: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 44/1 = ∑45/50, starting new job                         
2025-05-07 00:05:32: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/unknown 44/1/1 = ∑46/50, started new job                
2025-05-07 00:05:51: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 45/1 = ∑46/50, eval start                               
2025-05-07 00:06:10: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 45/1 = ∑46/50, starting new job                         
2025-05-07 00:06:31: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/unknown 45/1/1 = ∑47/50, started new job                
2025-05-07 00:06:50: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 46/1 = ∑47/50, eval start                               
2025-05-07 00:07:10: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 46/1 = ∑47/50, starting new job                         
2025-05-07 00:07:31: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 47/1 = ∑48/50, started new job                          
2025-05-07 00:07:51: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 47/1 = ∑48/50, eval start                               
2025-05-07 00:08:10: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 47/1 = ∑48/50, starting new job                         
2025-05-07 00:08:30: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/unknown 47/1/1 = ∑49/50, started new job                
2025-05-07 00:08:50: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 48/1 = ∑49/50, eval start                               
2025-05-07 00:09:10: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 48/1 = ∑49/50, starting new job                         
2025-05-07 00:09:31: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/unknown 48/1/1 = ∑50/50, started new job                
2025-05-07 00:09:50: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 49/1 = ∑50/50, new result: 0.35789473684210527          

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timestamp,ram_usage_mb,cpu_usage_percent
1746533465,619.28515625,34.3
1746533469,619.54296875,36.5
1746533473,619.54296875,35.2
1746533473,619.54296875,31.8
1746533473,619.54296875,28.0
1746533473,619.54296875,33.6
1746533473,619.54296875,48.4
1746535280,641.20703125,35.4
1746535280,641.20703125,28.0
1746535280,641.20703125,37.0
1746538443,699.9921875,42.6
1746538443,699.9921875,34.0
1746538443,699.9921875,32.6
1746538443,699.9921875,39.4
1746545977,714.21484375,33.6
1746545977,714.21484375,38.6
1746545977,714.21484375,39.1
1746545977,714.21484375,33.3
1746553154,731.48828125,37.6
1746553154,731.48828125,50.0
1746553154,731.48828125,37.5
1746553154,731.48828125,50.0
1746558812,758.86328125,39.7
1746558812,758.86328125,43.6
1746558812,758.86328125,40.3
1746558812,758.86328125,36.4
1746564851,788.62890625,39.4
1746564851,788.62890625,43.3
1746564851,788.62890625,38.3
1746564851,788.62890625,40.9

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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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			@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;
				color: #007bff;
			}
			
			.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 {
					font-size: 2em;
				}
			}
			
			.header_button {
				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;
			}
			

			/*! 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 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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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13h1'/%3E%3Cpath stroke='%23dbe3f8' d='M2 14h1'/%3E%3Cpath stroke='%23b7c6f1' d='M3 14h1'/%3E%3Cpath stroke='%23b8c9f2' d='M4 14h1m3 0h1'/%3E%3Cpath stroke='%23b2c8f4' d='M11 14h1'/%3E%3Cpath stroke='%23b1c6f3' d='M12 14h1'/%3E%3Cpath stroke='%23b0c4f2' d='M13 14h1'/%3E%3Cpath stroke='%23d9e3f6' d='M14 14h1'/%3E%3Cpath stroke='%23aec0d6' d='M16 14h1'/%3E%3Cpath stroke='%23c3d4e7' d='M1 15h1'/%3E%3Cpath stroke='%23aec4e5' d='M15 15h1'/%3E%3Cpath stroke='%23edf1f3' d='M1 16h1'/%3E%3Cpath stroke='%23aac0e1' d='M2 16h1'/%3E%3Cpath stroke='%2394b1d9' d='M3 16h1'/%3E%3Cpath stroke='%2388a7d8' d='M4 16h1'/%3E%3Cpath stroke='%2383a4d3' d='M5 16h1'/%3E%3Cpath stroke='%237da0d4' d='M6 16h1m3 0h3'/%3E%3Cpath stroke='%237e9fd2' d='M7 16h1'/%3E%3Cpath stroke='%237c9fd3' d='M8 16h2'/%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: vertical: end{
				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 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stroke='%23aecafa' d='M13 11h1'/%3E%3Cpath stroke='%23b1c8f3' d='M14 11h1'/%3E%3Cpath stroke='%23acc2f5' d='M2 12h1'/%3E%3Cpath stroke='%23c1d2fb' d='M5 12h1'/%3E%3Cpath stroke='%23bed1fc' d='M6 12h2'/%3E%3Cpath stroke='%23bdd3fb' d='M8 12h1'/%3E%3Cpath stroke='%23b6d1fb' d='M10 12h1'/%3E%3Cpath stroke='%23afccfb' d='M12 12h1'/%3E%3Cpath stroke='%23adc9f9' d='M13 12h1m-2 1h1'/%3E%3Cpath stroke='%23b1c5f3' d='M14 12h1'/%3E%3Cpath stroke='%23aac0f3' d='M2 13h1'/%3E%3Cpath stroke='%23b7cbf9' d='M3 13h1'/%3E%3Cpath stroke='%23b9cefb' d='M4 13h1'/%3E%3Cpath stroke='%23bbcef9' d='M7 13h1'/%3E%3Cpath stroke='%23b9cffb' d='M8 13h1'/%3E%3Cpath stroke='%23b2cdfb' d='M10 13h1'/%3E%3Cpath stroke='%23b0cbf9' d='M11 13h1'/%3E%3Cpath stroke='%23aec8f7' d='M13 13h1'/%3E%3Cpath stroke='%23b0c5f2' d='M14 13h1'/%3E%3Cpath stroke='%23dbe3f8' d='M2 14h1'/%3E%3Cpath stroke='%23b7c6f1' d='M3 14h1'/%3E%3Cpath stroke='%23b8c9f2' d='M4 14h1m3 0h1'/%3E%3Cpath stroke='%23b2c8f4' d='M11 14h1'/%3E%3Cpath 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			}
			
			: :-webkit-scrollbar-button: horizontal: start{
				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 2h1M1 9h1'/%3E%3Cpath stroke='%23b5c8f7' d='M11 2h1'/%3E%3Cpath stroke='%23b3c7f5' d='M12 2h1'/%3E%3Cpath stroke='%23afc5f4' 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			}
			
			: :-webkit-scrollbar-button: horizontal: end{
				width: 17px;
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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 special_col_names = ["trial_index","arm_name","trial_status","generation_method","generation_node","hostname","run_time","start_time","exit_code","signal","end_time","program_string"]

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			        1746562179.3560297,
			        50,
			        37,
			        74
			    ],
			    [
			        1746562198.4534714,
			        50,
			        38,
			        76
			    ],
			    [
			        1746562216.526343,
			        50,
			        38,
			        76
			    ],
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			        50,
			        38,
			        76
			    ],
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			        50,
			        39,
			        78
			    ],
			    [
			        1746562277.5661924,
			        50,
			        39,
			        78
			    ],
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			        50,
			        39,
			        78
			    ],
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			        50,
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			        80
			    ],
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			        50,
			        40,
			        80
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			        50,
			        40,
			        80
			    ],
			    [
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			        50,
			        41,
			        82
			    ],
			    [
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			        50,
			        41,
			        82
			    ],
			    [
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			        50,
			        41,
			        82
			    ],
			    [
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			        50,
			        42,
			        84
			    ],
			    [
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			        50,
			        42,
			        84
			    ],
			    [
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			        50,
			        42,
			        84
			    ],
			    [
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			        50,
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			        86
			    ],
			    [
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			        50,
			        43,
			        86
			    ],
			    [
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			        50,
			        43,
			        86
			    ],
			    [
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			        50,
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			        88
			    ],
			    [
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			        50,
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			        88
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			        50,
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			        88
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			    [
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			        50,
			        45,
			        90
			    ],
			    [
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			        50,
			        45,
			        90
			    ],
			    [
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			        50,
			        45,
			        90
			    ],
			    [
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			        50,
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			        92
			    ],
			    [
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			        50,
			        46,
			        92
			    ],
			    [
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			        50,
			        46,
			        92
			    ],
			    [
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			        50,
			        47,
			        94
			    ],
			    [
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			        50,
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			    ],
			    [
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			        50,
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			        94
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			    [
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			        50,
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			        96
			    ],
			    [
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			        50,
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			        96
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			    [
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			        50,
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			    [
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			        50,
			        49,
			        98
			    ],
			    [
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			        50,
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			    [
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			        50,
			        49,
			        98
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			    [
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			        50,
			        50,
			        100
			    ],
			    [
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			        50,
			        50,
			        100
			    ],
			    [
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			        50,
			        49,
			        98
			    ],
			    [
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			        50,
			        48,
			        96
			    ],
			    [
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			        50,
			        47,
			        94
			    ],
			    [
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			        50,
			        46,
			        92
			    ],
			    [
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			        50,
			        45,
			        90
			    ],
			    [
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			        50,
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			    ],
			    [
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			        50,
			        43,
			        86
			    ],
			    [
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			        50,
			        42,
			        84
			    ],
			    [
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			        50,
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			        82
			    ],
			    [
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			        50,
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			    [
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			        50,
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			    ],
			    [
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			        50,
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			    [
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			        50,
			        37,
			        74
			    ],
			    [
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			        50,
			        36,
			        72
			    ],
			    [
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			        50,
			        35,
			        70
			    ],
			    [
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			        50,
			        34,
			        68
			    ],
			    [
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			        50,
			        33,
			        66
			    ],
			    [
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			        50,
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			        64
			    ],
			    [
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			        50,
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			    ],
			    [
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			        50,
			        30,
			        60
			    ],
			    [
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			        50,
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			    ],
			    [
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			    ],
			    [
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			        50,
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			    ],
			    [
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			        50,
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			        50,
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			        50,
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			        38
			    ],
			    [
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			        50,
			        18,
			        36
			    ],
			    [
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			        50,
			        17,
			        34
			    ],
			    [
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			        50,
			        16,
			        32
			    ],
			    [
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			        50,
			        15,
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			    [
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			        50,
			        14,
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			    [
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			        50,
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			    ],
			    [
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			        50,
			        12,
			        24
			    ],
			    [
			        1746564442.587112,
			        50,
			        11,
			        22
			    ],
			    [
			        1746564479.6545825,
			        50,
			        10,
			        20
			    ],
			    [
			        1746564514.567038,
			        50,
			        9,
			        18
			    ],
			    [
			        1746564549.3796878,
			        50,
			        8,
			        16
			    ],
			    [
			        1746564583.8735964,
			        50,
			        7,
			        14
			    ],
			    [
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			        50,
			        6,
			        12
			    ],
			    [
			        1746564651.461022,
			        50,
			        5,
			        10
			    ],
			    [
			        1746564685.218942,
			        50,
			        4,
			        8
			    ],
			    [
			        1746564722.3917916,
			        50,
			        3,
			        6
			    ],
			    [
			        1746564756.7353556,
			        50,
			        2,
			        4
			    ],
			    [
			        1746564793.1183658,
			        50,
			        1,
			        2
			    ],
			    [
			        1746564830.9023192,
			        50,
			        0,
			        0
			    ]
			];
			var tab_main_worker_cpu_ram_csv_json = [
			    [
			        1746533465,
			        619.28515625,
			        34.3
			    ],
			    [
			        1746533469,
			        619.54296875,
			        36.5
			    ],
			    [
			        1746533473,
			        619.54296875,
			        35.2
			    ],
			    [
			        1746533473,
			        619.54296875,
			        31.8
			    ],
			    [
			        1746533473,
			        619.54296875,
			        28
			    ],
			    [
			        1746533473,
			        619.54296875,
			        33.6
			    ],
			    [
			        1746533473,
			        619.54296875,
			        48.4
			    ],
			    [
			        1746535280,
			        641.20703125,
			        35.4
			    ],
			    [
			        1746535280,
			        641.20703125,
			        28
			    ],
			    [
			        1746535280,
			        641.20703125,
			        37
			    ],
			    [
			        1746538443,
			        699.9921875,
			        42.6
			    ],
			    [
			        1746538443,
			        699.9921875,
			        34
			    ],
			    [
			        1746538443,
			        699.9921875,
			        32.6
			    ],
			    [
			        1746538443,
			        699.9921875,
			        39.4
			    ],
			    [
			        1746545977,
			        714.21484375,
			        33.6
			    ],
			    [
			        1746545977,
			        714.21484375,
			        38.6
			    ],
			    [
			        1746545977,
			        714.21484375,
			        39.1
			    ],
			    [
			        1746545977,
			        714.21484375,
			        33.3
			    ],
			    [
			        1746553154,
			        731.48828125,
			        37.6
			    ],
			    [
			        1746553154,
			        731.48828125,
			        50
			    ],
			    [
			        1746553154,
			        731.48828125,
			        37.5
			    ],
			    [
			        1746553154,
			        731.48828125,
			        50
			    ],
			    [
			        1746558812,
			        758.86328125,
			        39.7
			    ],
			    [
			        1746558812,
			        758.86328125,
			        43.6
			    ],
			    [
			        1746558812,
			        758.86328125,
			        40.3
			    ],
			    [
			        1746558812,
			        758.86328125,
			        36.4
			    ],
			    [
			        1746564851,
			        788.62890625,
			        39.4
			    ],
			    [
			        1746564851,
			        788.62890625,
			        43.3
			    ],
			    [
			        1746564851,
			        788.62890625,
			        38.3
			    ],
			    [
			        1746564851,
			        788.62890625,
			        40.9
			    ]
			];
			var tab_main_worker_cpu_ram_headers_json = [
			    "timestamp",
			    "ram_usage_mb",
			    "cpu_usage_percent"
			];
			
			"use strict";
			
			function add_default_layout_data (layout) {
				layout["width"] = get_graph_width();
				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 load_pareto_graph() {
				if($("#tab_pareto_fronts").data("loaded") == "true") {
					return;
				}
			
				var data = pareto_front_data;
			
				if (!data || typeof data !== "object") {
					console.error("Invalid data format for pareto_front_data");
					return;
				}
			
				if (!Object.keys(data).length) {
					console.warn("No data found in pareto_front_data");
					return;
				}
			
				let categories = Object.keys(data);
				let allMetrics = new Set();
			
				function extractMetrics(obj, prefix = "") {
					let keys = Object.keys(obj);
					for (let key of keys) {
						let newPrefix = prefix ? `${prefix} -> ${key}` : key;
						if (typeof obj[key] === "object" && !Array.isArray(obj[key])) {
							extractMetrics(obj[key], newPrefix);
						} else {
							if (!newPrefix.includes("param_dicts") && !newPrefix.includes(" -> sems -> ") && !newPrefix.includes("absolute_metrics")) {
								allMetrics.add(newPrefix);
							}
						}
					}
				}
			
				for (let cat of categories) {
					extractMetrics(data[cat]);
				}
			
				allMetrics = Array.from(allMetrics);
			
				function extractValues(obj, metricPath, values) {
					let parts = metricPath.split(" -> ");
					let data = obj;
					for (let part of parts) {
						if (data && typeof data === "object") {
							data = data[part];
						} else {
							return;
						}
					}
					if (Array.isArray(data)) {
						values.push(...data);
					}
				}
			
				let graphContainer = document.getElementById("pareto_front_graphs_container");
				graphContainer.classList.add("invert_in_dark_mode");
				graphContainer.innerHTML = "";
			
				var already_plotted = [];
			
				for (let i = 0; i < allMetrics.length; i++) {
					for (let j = i + 1; j < allMetrics.length; j++) {
						let xMetric = allMetrics[i];
						let yMetric = allMetrics[j];
			
						let xValues = [];
						let yValues = [];
			
						for (let cat of categories) {
							let metricData = data[cat];
							extractValues(metricData, xMetric, xValues);
							extractValues(metricData, yMetric, yValues);
						}
			
						xValues = xValues.filter(v => v !== undefined && v !== null);
						yValues = yValues.filter(v => v !== undefined && v !== null);
			
						let cleanXMetric = xMetric.replace(/.* -> /g, "");
						let cleanYMetric = yMetric.replace(/.* -> /g, "");
			
						let plot_key = `${cleanXMetric}-${cleanYMetric}`;
			
						if (xValues.length > 0 && yValues.length > 0 && xValues.length === yValues.length && !already_plotted.includes(plot_key)) {
							let div = document.createElement("div");
							div.id = `pareto_front_graph_${i}_${j}`;
							div.style.marginBottom = "20px";
							graphContainer.appendChild(div);
			
							let layout = {
								title: `${cleanXMetric} vs ${cleanYMetric}`,
								xaxis: {
									title: get_axis_title_data(cleanXMetric)
								},
								yaxis: {
									title: get_axis_title_data(cleanYMetric)
								},
								hovermode: "closest"
							};
			
							let trace = {
								x: xValues,
								y: yValues,
								mode: "markers",
								marker: {
									size: get_marker_size(),
								},
								type: "scatter",
								name: `${cleanXMetric} vs ${cleanYMetric}`
							};
			
							Plotly.newPlot(div.id, [trace], add_default_layout_data(layout));
			
							already_plotted.push(plot_key);
						}
					}
				}
			
				if (typeof apply_theme_based_on_system_preferences === 'function') {
					apply_theme_based_on_system_preferences();
				}
			
				$("#tab_pareto_fronts").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 color = el.textContent.includes("Manual") ? "green" :
						el.textContent.includes("Sobol") ? "orange" :
						el.textContent.includes("SAASBO") ? "pink" :
						el.textContent.includes("Uniform") ? "lightblue" :
						el.textContent.includes("Legacy_GPEI") ? "Sienna" :
						el.textContent.includes("BO_MIXED") ? "Aqua" :
						el.textContent.includes("RANDOMFOREST") ? "DarkSeaGreen" :
						el.textContent.includes("EXTERNAL_GENERATOR") ? "Purple" :
						el.textContent.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" : "";
					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;
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					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;
			
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					let logMin = Math.min(...logValues);
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					cells.forEach(el => {
						let value = parseFloat(el.textContent);
						if (isNaN(value) || value <= 0) return;
			
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						el.style.backgroundColor = `rgb(${red}, ${green}, 0)`;
						el.classList.add("invert_in_dark_mode");
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			function _colorize_table_entries_by_generation_node_or_hostname() {
				["hostname", "generation_node"].forEach(element => {
					let selector_query = '[data-column-id="' + element + '"]:not(.gridjs-th)';
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					if (cells.length === 0) return;
			
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					cells.forEach(el => {
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							el.style.backgroundColor = colorMap[value];
							el.classList.add("invert_in_dark_mode");
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			}
			
			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);
				}
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			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);
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			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;
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					plotlyElements.forEach(function(element, index) {
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							height: newHeight,
							plot_bgcolor: 'rgba(0, 0, 0, 0)',
							paper_bgcolor: 'rgba(0, 0, 0, 0)',
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						Plotly.relayout(element, layout)
					});
				}
			
				make_text_in_parallel_plot_nicer();
				apply_theme_based_on_system_preferences();
			}
			
			window.addEventListener('load', updatePreWidths);
			window.addEventListener('resize', updatePreWidths);
			
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				colorize_table_entries();
			
				add_up_down_arrows_for_scrolling();
			
				add_colorize_to_gridjs_table();
			});
			
			window.addEventListener('resize', function() {
				resizePlotlyCharts();
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			$(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=1&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><br><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>301</td>
			<td>49</td>
			<td>350</td>
			</tr>
			</tbody>
			</table>
			<h2>Result names and types:</h2>
			<br><table>
			<tr><th>name</th><th>min/max</th></tr>
			<tr>
			<td>RESULT</td>
			<td>min</td>
			</tr>
			</table><br>
			<h2>Last progressbar status:</h2>
			<tt>2025-05-07 00:09:50: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 49/1 = &sum;50/50, new result: 0.35789473684210527</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>
			<button onclick='download_as_file("tab_results_csv_table_pre", "results.csv")'> Download &raquo;results.csv&laquo; as file</button>
<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,0.215789473684210530990412735264,182,0.004086844545602799118333425810,5,15,85
1,1_0,COMPLETED,Sobol,SOBOL,0.357894736842105265495206367632,93,0.005281418676208705746677463111,20,87,29
2,2_0,COMPLETED,Sobol,SOBOL,0.373684210526315840894540087902,47,0.001921856395900249647734625569,16,50,53
3,3_0,COMPLETED,Sobol,SOBOL,0.278947368421052610543142691313,149,0.008066364510636777132579489091,31,76,64
4,4_0,COMPLETED,Sobol,SOBOL,0.436842105263157920447270043951,114,0.000270663183648139264812076954,22,65,74
5,5_0,COMPLETED,Sobol,SOBOL,0.289473684210526327476031838160,13,0.009015402867831289954181350765,7,39,40
6,6_0,COMPLETED,Sobol,SOBOL,0.342105263157894690095872647362,76,0.003055609608162194578556691837,25,98,18
7,7_0,COMPLETED,Sobol,SOBOL,0.221052631578947389456857308687,166,0.006850415381975472409181726618,11,27,99
8,8_0,COMPLETED,Sobol,SOBOL,0.305263157894736791853063095914,155,0.002123264156468212659339966919,28,33,22
9,9_0,COMPLETED,Sobol,SOBOL,0.278947368421052610543142691313,65,0.008402737917471677156489029414,14,59,78
10,10_0,COMPLETED,Sobol,SOBOL,0.478947368421052677156524168822,27,0.004908276228047908293361523135,25,22,60
11,11_0,COMPLETED,Sobol,SOBOL,0.278947368421052610543142691313,129,0.006237683899421245757588305736,10,93,49
12,12_0,COMPLETED,Sobol,SOBOL,0.352631578947368407028761794209,136,0.003469326064269989944727212716,16,81,33
13,13_0,COMPLETED,Sobol,SOBOL,0.389473684210526305271571345656,34,0.007129166191816331196728917519,30,10,68
14,14_0,COMPLETED,Sobol,SOBOL,0.342105263157894690095872647362,103,0.001304272636305541009996145085,5,70,95
15,15_0,COMPLETED,Sobol,SOBOL,0.300000000000000044408920985006,192,0.009914178853482008210717957297,19,44,14
16,16_0,COMPLETED,Sobol,SOBOL,0.336842105263157942651730536454,199,0.000824830826744437370715012925,13,97,63
17,17_0,COMPLETED,Sobol,SOBOL,0.257894736842105287699666860135,97,0.009395421993639321150970644680,28,32,51
18,18_0,COMPLETED,Sobol,SOBOL,0.300000000000000044408920985006,40,0.003608634402230382134946218287,10,63,30
19,19_0,COMPLETED,Sobol,SOBOL,0.310526315789473650319507669337,129,0.007229159479495138665439135650,24,43,88
20,20_0,COMPLETED,Sobol,SOBOL,0.352631578947368407028761794209,122,0.004501324065867812196373165534,30,54,97
21,21_0,COMPLETED,Sobol,SOBOL,0.310526315789473650319507669337,32,0.005791419010423124943964801048,15,74,18
22,22_0,COMPLETED,Sobol,SOBOL,0.363157894736842123961650941055,60,0.002335062141809612391851747049,19,20,42
23,23_0,COMPLETED,Sobol,SOBOL,0.231578947368421106389746455534,161,0.008575223175995051738684793463,4,86,75
24,24_0,COMPLETED,Sobol,SOBOL,0.326315789473684225718841389607,171,0.002651093154959380596147333620,21,68,44
25,25_0,COMPLETED,Sobol,SOBOL,0.268421052631578893610253544466,70,0.006406586238835007898750895095,7,48,56
26,26_0,COMPLETED,Sobol,SOBOL,0.342105263157894690095872647362,19,0.000484896582923829554557376698,32,80,83
27,27_0,COMPLETED,Sobol,SOBOL,0.273684210526315752076698117889,109,0.009190323577169329932745611700,18,15,25
28,28_0,COMPLETED,Sobol,SOBOL,0.284210526315789469009587264736,144,0.001435144597943872326814562790,8,26,10
29,29_0,COMPLETED,Sobol,SOBOL,0.357894736842105265495206367632,54,0.007540337625518441985739137579,23,92,89
30,30_0,COMPLETED,Sobol,SOBOL,0.294736842105263185942476411583,86,0.004218882526364178126021542425,12,37,71
31,31_0,COMPLETED,Sobol,SOBOL,0.294736842105263185942476411583,187,0.005374141643568874221470466068,26,57,37
32,32_0,COMPLETED,Sobol,SOBOL,0.384210526315789446805126772233,184,0.001757793323975056533348126919,25,85,99
33,33_0,COMPLETED,Sobol,SOBOL,0.205263157894736814057523588417,83,0.007843690539896489011262303848,10,19,20
34,34_0,COMPLETED,Sobol,SOBOL,0.352631578947368407028761794209,57,0.003922780809830874945709489054,28,72,39
35,35_0,COMPLETED,Sobol,SOBOL,0.284210526315789469009587264736,147,0.005058744115382433209626711346,14,52,72
36,36_0,COMPLETED,Sobol,SOBOL,0.289473684210526327476031838160,106,0.002949573803134262692249301097,5,41,66
37,37_0,COMPLETED,Sobol,SOBOL,0.363157894736842123961650941055,17,0.006724438229668886456147358643,19,61,54
38,38_0,COMPLETED,Sobol,SOBOL,0.473684210526315818690079595399,73,0.000164627968706190601615863001,16,31,27
39,39_0,COMPLETED,Sobol,SOBOL,0.315789473684210508785952242761,174,0.008889426305610686682157073335,30,96,84
40,40_0,COMPLETED,Sobol,SOBOL,0.321052631578947367252396816184,164,0.004802222148794681524930361149,17,55,14
41,41_0,COMPLETED,Sobol,SOBOL,0.394736842105263163738015919080,63,0.006111688436008990733816492735,31,36,93
42,42_0,COMPLETED,Sobol,SOBOL,0.378947368421052588338682198810,29,0.002017209487129002776217845394,6,90,68
43,43_0,COMPLETED,Sobol,SOBOL,0.326315789473684225718841389607,119,0.008276741863973438584345387881,21,25,35
44,44_0,COMPLETED,Sobol,SOBOL,0.300000000000000044408920985006,133,0.001140227838605642344052548687,26,13,47
45,45_0,COMPLETED,Sobol,SOBOL,0.226315789473684247923301882111,42,0.009691523193847388292776479091,12,79,59
46,46_0,COMPLETED,Sobol,SOBOL,0.336842105263157942651730536454,94,0.003305281856656074827155444851,22,47,80
47,47_0,COMPLETED,Sobol,SOBOL,0.247368421052631570766777713288,195,0.006906511122267693959797529857,8,67,23
48,48_0,COMPLETED,Sobol,SOBOL,0.331578947368421084185285963031,189,0.003792012777086347513622044403,32,28,78
49,49_0,COMPLETED,Sobol,SOBOL,0.300000000000000044408920985006,99,0.007432481561973691870648384139,18,99,43
50,50_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,133,0.008577504456510273711522529538,9,21,14
51,51_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.284210526315789469009587264736,121,0.009818272291073204885436531697,10,86,12
52,52_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.263157894736842146166111433558,142,0.007137340016123906727418813034,7,10,42
53,53_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.210526315789473672523968161840,125,0.009744594475476721015527736824,9,32,18
54,54_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,166,0.006950327656025007821982697465,4,14,84
55,55_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.226315789473684247923301882111,139,0.008798112083856104645440687761,7,11,69
56,56_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.342105263157894690095872647362,120,0.010000000000000000208166817117,10,100,83
57,57_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,48,0.010000000000000000208166817117,12,75,12
58,58_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,79,0.009258267750248419525327392421,9,91,22
59,59_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.226315789473684247923301882111,196,0.005556302825780697236812688544,9,12,88
60,60_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.231578947368421106389746455534,103,0.010000000000000000208166817117,10,10,40
61,61_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.284210526315789469009587264736,160,0.008001981087390761318567378169,6,13,35
62,62_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,125,0.008515341535115643692432918499,8,56,12
63,63_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.252631578947368429233222286712,116,0.009648653744496277218090085626,9,65,29
64,64_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.252631578947368429233222286712,116,0.010000000000000000208166817117,10,50,56
65,65_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.284210526315789469009587264736,114,0.009279508125766304169057541174,9,97,36
66,66_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.221052631578947389456857308687,187,0.005193540037535490302977869703,6,15,12
67,67_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.231578947368421106389746455534,116,0.008813640999560575992055611039,9,50,15
68,68_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.300000000000000044408920985006,68,0.010000000000000000208166817117,12,32,20
69,69_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.221052631578947389456857308687,112,0.009008066003247780853535608969,10,10,12
70,70_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,99,0.010000000000000000208166817117,8,95,34
71,71_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,175,0.008982729676910994331962001525,6,37,13
72,72_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,96,0.010000000000000000208166817117,10,63,12
73,73_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.315789473684210508785952242761,26,0.010000000000000000208166817117,15,90,20
74,74_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.315789473684210508785952242761,138,0.009313386529547548059460027048,8,54,49
75,75_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.194736842105263208146936904086,166,0.009214396673853866501224807450,9,12,12
76,76_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.221052631578947389456857308687,163,0.009546552301604260479250818605,9,76,94
77,77_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.368421052631578982428095514479,147,0.006954417456552954360238238962,4,14,21
78,78_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.215789473684210530990412735264,74,0.009640987831256973145110933388,10,25,47
79,79_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.226315789473684247923301882111,126,0.009737317249339197400281875616,9,59,35
80,80_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.278947368421052610543142691313,134,0.010000000000000000208166817117,11,77,22
81,81_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,136,0.009714152980487143068666355816,7,94,38
82,82_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.252631578947368429233222286712,130,0.005989085553031035791260450196,7,17,10
83,83_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,93,0.008907503300410438487610953473,10,95,11
84,84_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,155,0.009489672677845194248558158279,8,90,68
85,85_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,133,0.007919025068734422342919820892,5,31,10
86,86_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.263157894736842146166111433558,170,0.007093616379362981637368701371,9,11,11
87,87_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.357894736842105265495206367632,145,0.010000000000000000208166817117,8,13,26
88,88_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,198,0.008744131195503632852927822228,6,11,96
89,89_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,158,0.010000000000000000208166817117,9,54,16
90,90_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,165,0.009780347900098872171437136558,10,31,94
91,91_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.199999999999999955591079014994,165,0.010000000000000000208166817117,10,21,61
92,92_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,125,0.008824063502547264264963544633,5,34,14
93,93_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.415789473684210486581491750258,17,0.010000000000000000208166817117,14,27,23
94,94_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.357894736842105265495206367632,76,0.010000000000000000208166817117,6,90,84
95,95_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.199999999999999955591079014994,180,0.001943773273209835165953318636,4,15,80
96,96_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,90,0.010000000000000000208166817117,11,43,37
97,97_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.236842105263157853833888566442,136,0.009872329444681192042732043035,9,35,80
98,98_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.347368421052631548562317220785,100,0.010000000000000000208166817117,9,63,82
99,99_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.352631578947368407028761794209,147,0.008498460640559984610731270038,4,10,55
100,100_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.357894736842105265495206367632,128,0.007328165143666878940387210406,11,10,48
101,101_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.305263157894736791853063095914,199,0.003580058943620138735969282706,7,34,66
102,102_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.289473684210526327476031838160,173,0.007354887547036352904439304723,12,13,42
103,103_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.289473684210526327476031838160,196,0.000680550022858143798323848905,5,10,63
104,104_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.263157894736842146166111433558,190,0.005528909705012396806622643197,9,70,71
105,105_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.305263157894736791853063095914,189,0.003570749819384346195744184271,9,13,52
106,106_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.231578947368421106389746455534,196,0.003750095933055425188179521356,5,82,77
107,107_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.221052631578947389456857308687,141,0.008569652555526699813648328075,13,14,54
108,108_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.236842105263157853833888566442,198,0.003852011714893742531234943627,9,10,44
109,109_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.321052631578947367252396816184,65,0.007063617445149230310297294722,10,13,69
110,110_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.300000000000000044408920985006,200,0.005628487729766808340958750279,7,95,95
111,111_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.336842105263157942651730536454,200,0.001300815900408056578763105193,4,42,35
112,112_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,186,0.006164225392213050838674526233,6,85,95
113,113_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.305263157894736791853063095914,198,0.006288258460588526214951610172,9,92,71
114,114_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.373684210526315840894540087902,199,0.000905037362874354183416014674,5,43,68
115,115_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.278947368421052610543142691313,165,0.008388896327259951629651268945,13,39,60
116,116_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.294736842105263185942476411583,167,0.010000000000000000208166817117,30,14,29
117,117_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.352631578947368407028761794209,138,0.003544362072843388992982038843,9,10,92
118,118_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.273684210526315752076698117889,191,0.007007867855856318196894338968,13,19,64
119,119_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,138,0.010000000000000000208166817117,27,78,18
120,120_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.336842105263157942651730536454,121,0.005714763782904381389515791057,10,10,68
121,121_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,144,0.006895473797321891723521858353,12,11,33
122,122_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.294736842105263185942476411583,164,0.010000000000000000208166817117,27,43,24
123,123_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.310526315789473650319507669337,194,0.003040045886165567909364959576,6,64,37
124,124_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.231578947368421106389746455534,195,0.010000000000000000208166817117,27,76,34
125,125_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.310526315789473650319507669337,190,0.002120316804501299907254052712,9,12,96
126,126_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.326315789473684225718841389607,191,0.000100000000000000004792173602,5,14,77
127,127_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.273684210526315752076698117889,180,0.005267571433207468567516684743,9,40,53
128,128_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.315789473684210508785952242761,115,0.007758164796308052169049318536,12,10,46
129,129_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.342105263157894690095872647362,170,0.003762872988497674344582355488,9,27,77
130,130_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.236842105263157853833888566442,190,0.007947880364360022237280034574,12,36,44
131,131_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.321052631578947367252396816184,192,0.004951282663584587878657927718,9,42,65
132,132_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.226315789473684247923301882111,198,0.003896030035410551640301379805,6,36,65
133,133_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.231578947368421106389746455534,149,0.007881764468139451987327426252,13,55,36
134,134_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.326315789473684225718841389607,168,0.009222464332006793247265008517,28,25,75
135,135_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.257894736842105287699666860135,196,0.003806215445926703928175571789,6,89,50
136,136_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,191,0.007021442597610894065240927375,9,58,71
137,137_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,191,0.007128999541857151608925668995,12,18,24
138,138_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.305263157894736791853063095914,182,0.008026985369642108958387893836,12,46,33
139,139_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.257894736842105287699666860135,194,0.003306135577411622398363855169,6,78,59
140,140_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.273684210526315752076698117889,182,0.004323422961681195123007093173,6,85,70
141,141_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.273684210526315752076698117889,141,0.007719074453487567190335116862,13,19,62
142,142_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,144,0.010000000000000000208166817117,31,72,15
143,143_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.342105263157894690095872647362,193,0.000857345903600753383132226926,9,20,82
144,144_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.300000000000000044408920985006,188,0.001281827816867635522549151439,9,27,85
145,145_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.289473684210526327476031838160,178,0.005897926953008805067701914027,11,57,57
146,146_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.252631578947368429233222286712,158,0.005338181538748697566032497264,10,10,64
147,147_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.278947368421052610543142691313,197,0.003731141318260021520064606548,8,29,95
148,148_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.273684210526315752076698117889,106,0.010000000000000000208166817117,30,17,21
149,149_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,136,0.009874131838474345043699109681,26,69,39
150,150_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.194736842105263208146936904086,200,0.010000000000000000208166817117,15,10,100
151,151_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.210526315789473672523968161840,200,0.010000000000000000208166817117,15,13,34
152,152_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.305263157894736791853063095914,138,0.010000000000000000208166817117,15,12,95
153,153_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.231578947368421106389746455534,192,0.010000000000000000208166817117,16,100,100
154,154_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.300000000000000044408920985006,196,0.007730263524140227986147788641,13,96,25
155,155_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.463157894736842101757190448552,200,0.000100000000000000004792173602,32,10,10
156,156_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.378947368421052588338682198810,200,0.000100000000000000004792173602,32,100,10
157,157_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.315789473684210508785952242761,177,0.001313545503326270583177581841,32,52,23
158,158_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,198,0.008014373080690435219297640401,12,20,93
159,159_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.305263157894736791853063095914,191,0.001608538467685494350103980743,31,96,68
160,160_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.310526315789473650319507669337,199,0.010000000000000000208166817117,20,20,78
161,161_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.278947368421052610543142691313,171,0.010000000000000000208166817117,13,16,100
162,162_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.389473684210526305271571345656,42,0.000100000000000000004792173602,32,59,46
163,163_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.310526315789473650319507669337,198,0.004294366743974310958453788345,30,90,20
164,164_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.357894736842105265495206367632,159,0.006007570117257618816375419613,28,31,81
165,165_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,193,0.010000000000000000208166817117,32,10,97
166,166_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.326315789473684225718841389607,180,0.001543628383647337870554494543,31,48,12
167,167_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.405263157894736880670905065926,112,0.000100000000000000004792173602,32,77,26
168,168_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.284210526315789469009587264736,199,0.008903408070860379872057954742,16,53,70
169,169_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,98,0.000100000000000000004792173602,32,88,10
170,170_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.394736842105263163738015919080,61,0.002675672718157655338711009563,32,91,11
171,171_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.205263157894736814057523588417,194,0.009483950817449808903814023608,14,49,85
172,172_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.478947368421052677156524168822,194,0.003112244397367996701780912261,31,48,62
173,173_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.326315789473684225718841389607,144,0.002241743597017828437678588216,31,25,25
174,174_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.352631578947368407028761794209,192,0.008198805150044939996090143097,18,14,13
175,175_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.331578947368421084185285963031,122,0.002513119276252127800436175775,28,23,35
176,176_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.294736842105263185942476411583,132,0.000629139444783942771745322009,30,33,20
177,177_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.294736842105263185942476411583,195,0.010000000000000000208166817117,13,87,80
178,178_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.357894736842105265495206367632,192,0.008371381953704055620124613313,15,11,25
179,179_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.357894736842105265495206367632,184,0.002241882606741776775421959300,30,56,34
180,180_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.278947368421052610543142691313,136,0.002320195776518194519938420584,27,13,26
181,181_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,172,0.001147543717954733642414022476,31,74,14
182,182_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.389473684210526305271571345656,180,0.005813898878096229044798448626,28,14,92
183,183_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.205263157894736814057523588417,95,0.005906303250325943034193532100,7,13,99
184,184_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.215789473684210530990412735264,199,0.008103652102722510436327851835,12,14,24
185,185_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.252631578947368429233222286712,195,0.007648087627267045190970762292,14,92,92
186,186_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.273684210526315752076698117889,173,0.005238454956395250348977210564,29,14,70
187,187_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.268421052631578893610253544466,159,0.001032169478795734061590816388,32,25,14
188,188_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.342105263157894690095872647362,172,0.002377266684934614508761807627,30,55,16
189,189_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.305263157894736791853063095914,191,0.007451484272620452660451650928,32,60,24
190,190_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.368421052631578982428095514479,120,0.000815032302419993167144629531,32,42,25
191,191_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.215789473684210530990412735264,200,0.007960593673277541540422852506,28,20,74
192,192_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.315789473684210508785952242761,182,0.006262168295360940814542338728,31,51,58
193,193_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.347368421052631548562317220785,185,0.001676929286724987032061728875,30,27,12
194,194_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.315789473684210508785952242761,200,0.004849079563059101143085438679,10,48,11
195,195_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,149,0.005553668164979486988885870602,25,39,81
196,196_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.352631578947368407028761794209,158,0.000699616396771418147873533577,25,96,79
197,197_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.231578947368421106389746455534,198,0.007649381166543604664009858851,19,28,79
198,198_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.300000000000000044408920985006,196,0.001348557631808395542924450261,30,59,13
199,199_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.347368421052631548562317220785,186,0.007058599013385699269540474177,30,81,90
200,200_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.368421052631578982428095514479,78,0.010000000000000000208166817117,4,10,100
201,201_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.300000000000000044408920985006,92,0.010000000000000000208166817117,13,10,100
202,202_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.252631578947368429233222286712,196,0.010000000000000000208166817117,4,100,100
203,203_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,74,0.010000000000000000208166817117,4,12,42
204,204_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,67,0.007996080402047250554331547789,4,10,81
205,205_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.189473684210526349680492330663,169,0.006708814873979875893772462092,4,100,100
206,206_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.305263157894736791853063095914,164,0.002169413565395823719622603321,4,100,100
207,207_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.257894736842105287699666860135,200,0.010000000000000000208166817117,11,50,100
208,208_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,90,0.010000000000000000208166817117,4,10,70
209,209_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,79,0.010000000000000000208166817117,4,10,10
210,210_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,200,0.009749012337050041998587346370,4,59,22
211,211_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.357894736842105265495206367632,82,0.010000000000000000208166817117,13,10,59
212,212_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,83,0.010000000000000000208166817117,8,10,25
213,213_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,200,0.010000000000000000208166817117,4,55,95
214,214_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.336842105263157942651730536454,72,0.009472401634708067438839229624,5,16,81
215,215_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.357894736842105265495206367632,78,0.007481519651620194277796827009,4,11,12
216,216_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.226315789473684247923301882111,93,0.010000000000000000208166817117,15,14,57
217,217_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,64,0.010000000000000000208166817117,4,11,51
218,218_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,96,0.009694800616111378874228954317,16,19,87
219,219_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.336842105263157942651730536454,10,0.010000000000000000208166817117,4,100,69
220,220_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,54,0.010000000000000000208166817117,4,14,100
221,221_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.236842105263157853833888566442,46,0.009440972924177703715087339731,4,24,80
222,222_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.321052631578947367252396816184,175,0.010000000000000000208166817117,15,95,95
223,223_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.331578947368421084185285963031,17,0.010000000000000000208166817117,6,95,54
224,224_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.347368421052631548562317220785,94,0.009343742192117206191159795026,10,19,95
225,225_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.347368421052631548562317220785,70,0.008955403214434798711551799499,18,14,64
226,226_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.278947368421052610543142691313,164,0.007264409825752541315091459495,13,94,98
227,227_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.357894736842105265495206367632,28,0.010000000000000000208166817117,24,98,27
228,228_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.231578947368421106389746455534,178,0.010000000000000000208166817117,7,98,57
229,229_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.226315789473684247923301882111,69,0.010000000000000000208166817117,17,15,79
230,230_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.263157894736842146166111433558,140,0.005010466861507650686291537312,6,92,87
231,231_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,41,0.010000000000000000208166817117,4,41,32
232,232_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.342105263157894690095872647362,17,0.007055760108174730788066497666,4,95,62
233,233_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.284210526315789469009587264736,99,0.009194321504287672475186354859,12,20,83
234,234_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.284210526315789469009587264736,67,0.003364656865678123959934042730,6,93,79
235,235_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,52,0.005685192655278845444422053390,5,98,85
236,236_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.221052631578947389456857308687,200,0.010000000000000000208166817117,11,100,64
237,237_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.305263157894736791853063095914,12,0.010000000000000000208166817117,4,49,73
238,238_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,121,0.010000000000000000208166817117,14,16,100
239,239_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.305263157894736791853063095914,100,0.010000000000000000208166817117,23,26,83
240,240_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.215789473684210530990412735264,198,0.007731675252046769225566791306,6,45,94
241,241_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.305263157894736791853063095914,86,0.010000000000000000208166817117,22,19,91
242,242_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.336842105263157942651730536454,51,0.010000000000000000208166817117,5,20,64
243,243_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.242105263157894712300333139865,200,0.010000000000000000208166817117,9,34,32
244,244_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.331578947368421084185285963031,71,0.009280344521994299614164880552,10,14,89
245,245_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,27,0.010000000000000000208166817117,4,51,90
246,246_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.231578947368421106389746455534,87,0.006955764471627999372127515443,5,25,35
247,247_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.357894736842105265495206367632,79,0.009402314477485483601437721290,20,13,84
248,248_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.236842105263157853833888566442,19,0.008174287507179699846515674722,9,96,94
249,249_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.199999999999999955591079014994,87,0.008685049338473319058273602877,12,16,100
250,250_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.199999999999999955591079014994,200,0.007291676439191521232052739521,9,10,100
251,251_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.268421052631578893610253544466,200,0.007929985518306420858025695964,10,59,95
252,252_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.284210526315789469009587264736,199,0.008195248509410299128652432898,10,76,100
253,253_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,193,0.007931655319971116571697855591,11,90,74
254,254_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.263157894736842146166111433558,193,0.009594192945999061722384126938,11,22,96
255,255_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.205263157894736814057523588417,200,0.007055811264348119289657734754,9,77,100
256,256_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.357894736842105265495206367632,200,0.010000000000000000208166817117,12,10,72
257,257_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.263157894736842146166111433558,200,0.010000000000000000208166817117,12,93,100
258,258_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.336842105263157942651730536454,200,0.005425183743495280187796314664,4,100,100
259,259_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.221052631578947389456857308687,200,0.008440358256238074396993198434,10,17,89
260,260_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,168,0.006826646227095431451736828876,7,85,100
261,261_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.257894736842105287699666860135,200,0.008151733417899107228543620352,12,85,97
262,262_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.410526315789473739137349639350,55,0.000100000000000000004792173602,4,76,12
263,263_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.263157894736842146166111433558,200,0.010000000000000000208166817117,22,20,95
264,264_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.184210526315789491214047757239,189,0.006015229369388397882845165299,7,14,66
265,265_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.226315789473684247923301882111,195,0.003128322759995349425926614018,4,90,28
266,266_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.347368421052631548562317220785,200,0.010000000000000000208166817117,11,10,100
267,267_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.294736842105263185942476411583,196,0.010000000000000000208166817117,15,58,32
268,268_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.205263157894736814057523588417,199,0.007625260542159143992146930202,22,12,17
269,269_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.257894736842105287699666860135,195,0.010000000000000000208166817117,25,47,98
270,270_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,198,0.006201190276445331557575446624,6,31,93
271,271_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,195,0.008296187054131350449570625472,24,100,17
272,272_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.226315789473684247923301882111,200,0.006883295264170376757950631230,10,77,99
273,273_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.231578947368421106389746455534,192,0.007434520055481418088216827300,7,77,99
274,274_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.194736842105263208146936904086,197,0.008846428018668237025501355220,17,31,56
275,275_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.284210526315789469009587264736,199,0.010000000000000000208166817117,21,47,98
276,276_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.252631578947368429233222286712,198,0.008938719527158999964000507532,21,94,92
277,277_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,197,0.010000000000000000208166817117,16,85,22
278,278_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.305263157894736791853063095914,200,0.007962235188536335647735420196,9,96,100
279,279_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.305263157894736791853063095914,194,0.008734301063598860423442538092,25,16,18
280,280_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.221052631578947389456857308687,175,0.008487945627539824136609247773,27,77,31
281,281_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.284210526315789469009587264736,200,0.009537737592372700495824133782,19,78,83
282,282_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.326315789473684225718841389607,117,0.002561336279059253564355236321,4,18,100
283,283_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.252631578947368429233222286712,199,0.010000000000000000208166817117,23,79,28
284,284_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.284210526315789469009587264736,179,0.003390113275396877332013012563,4,59,18
285,285_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.205263157894736814057523588417,198,0.010000000000000000208166817117,27,11,11
286,286_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.305263157894736791853063095914,175,0.009349272459615030547719349840,26,97,49
287,287_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.347368421052631548562317220785,36,0.005056488906256526895399705523,9,12,12
288,288_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.252631578947368429233222286712,191,0.009836560025212250091275478781,27,21,57
289,289_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,187,0.008391866727533774106273511961,10,12,90
290,290_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.215789473684210530990412735264,199,0.008772779087706203057783760357,13,16,76
291,291_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.210526315789473672523968161840,199,0.010000000000000000208166817117,25,20,49
292,292_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.321052631578947367252396816184,170,0.007863181618209195977708958480,27,98,32
293,293_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.257894736842105287699666860135,187,0.007664264830929409973159227576,25,63,37
294,294_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.247368421052631570766777713288,188,0.008505773835092489409959171098,23,28,22
295,295_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.289473684210526327476031838160,199,0.008127769768451859402902393015,15,11,69
296,296_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.289473684210526327476031838160,136,0.008573263979629782913227664665,26,93,26
297,297_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.357894736842105265495206367632,184,0.008766550644958560206676523308,12,18,68
298,298_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.263157894736842146166111433558,198,0.006391300842046437717669515877,4,37,95
299,299_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.363157894736842123961650941055,193,0.008208469928146253785650188206,27,47,11
300,300_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.357894736842105265495206367632,200,0.010000000000000000208166817117,23,10,41
301,301_0,RUNNING,BoTorch,BOTORCH_MODULAR,,191,0.008690228343366133631486825095,16,13,99
302,302_0,RUNNING,BoTorch,BOTORCH_MODULAR,,151,0.008214996255335754726800701064,11,88,99
303,303_0,RUNNING,BoTorch,BOTORCH_MODULAR,,200,0.007200959901677950018850093983,13,47,100
304,304_0,RUNNING,BoTorch,BOTORCH_MODULAR,,200,0.005081474352885096898435612900,6,94,11
305,305_0,RUNNING,BoTorch,BOTORCH_MODULAR,,200,0.004392889949584495752621382536,4,82,27
306,306_0,RUNNING,BoTorch,BOTORCH_MODULAR,,200,0.004433710192649271963905022176,4,15,72
307,307_0,RUNNING,BoTorch,BOTORCH_MODULAR,,193,0.006026825322515550267810091611,10,96,90
308,308_0,RUNNING,BoTorch,BOTORCH_MODULAR,,200,0.010000000000000000208166817117,23,10,10
309,309_0,RUNNING,BoTorch,BOTORCH_MODULAR,,197,0.005826684793629684049054429096,8,59,60
310,310_0,RUNNING,BoTorch,BOTORCH_MODULAR,,137,0.006825591395611478248706127658,10,94,99
311,311_0,RUNNING,BoTorch,BOTORCH_MODULAR,,199,0.005738844622553738485104535272,8,14,21
312,312_0,RUNNING,BoTorch,BOTORCH_MODULAR,,26,0.006196918380796844622038221928,9,24,90
313,313_0,RUNNING,BoTorch,BOTORCH_MODULAR,,170,0.006861978646614732592345919926,9,86,100
314,314_0,RUNNING,BoTorch,BOTORCH_MODULAR,,197,0.010000000000000000208166817117,32,10,44
315,315_0,RUNNING,BoTorch,BOTORCH_MODULAR,,91,0.010000000000000000208166817117,15,74,100
316,316_0,RUNNING,BoTorch,BOTORCH_MODULAR,,200,0.006487832008299583910759800176,8,94,100
317,317_0,RUNNING,BoTorch,BOTORCH_MODULAR,,189,0.006594452433289561994744776285,18,31,28
318,318_0,RUNNING,BoTorch,BOTORCH_MODULAR,,184,0.008788193223409001067492063441,28,11,17
319,319_0,RUNNING,BoTorch,BOTORCH_MODULAR,,185,0.009706456536513294319767908291,19,12,100
320,320_0,RUNNING,BoTorch,BOTORCH_MODULAR,,179,0.010000000000000000208166817117,32,95,10
321,321_0,RUNNING,BoTorch,BOTORCH_MODULAR,,124,0.007660351672229673974934271996,10,19,88
322,322_0,RUNNING,BoTorch,BOTORCH_MODULAR,,199,0.007697847625975125750164007599,19,33,97
323,323_0,RUNNING,BoTorch,BOTORCH_MODULAR,,189,0.007080508871516897825837411062,11,17,98
324,324_0,RUNNING,BoTorch,BOTORCH_MODULAR,,195,0.006347464730234357935256817029,11,98,91
325,325_0,RUNNING,BoTorch,BOTORCH_MODULAR,,152,0.007053687018213984465109245292,9,40,98
326,326_0,RUNNING,BoTorch,BOTORCH_MODULAR,,196,0.006733822685616534450825376723,8,12,36
327,327_0,RUNNING,BoTorch,BOTORCH_MODULAR,,200,0.005330177068560809118535903650,4,11,92
328,328_0,RUNNING,BoTorch,BOTORCH_MODULAR,,167,0.007082479005346094258488420792,10,96,90
329,329_0,RUNNING,BoTorch,BOTORCH_MODULAR,,192,0.008223181018541025899537544319,22,10,75
330,330_0,RUNNING,BoTorch,BOTORCH_MODULAR,,181,0.007530052111167856790374663944,13,10,100
331,331_0,RUNNING,BoTorch,BOTORCH_MODULAR,,197,0.005755042939312985175726034015,23,11,18
332,332_0,RUNNING,BoTorch,BOTORCH_MODULAR,,198,0.008448069330515475122700408406,22,16,88
333,333_0,RUNNING,BoTorch,BOTORCH_MODULAR,,192,0.006854246695185100927971699747,11,95,24
334,334_0,RUNNING,BoTorch,BOTORCH_MODULAR,,198,0.006760587303112118931491814067,9,99,68
335,335_0,RUNNING,BoTorch,BOTORCH_MODULAR,,191,0.009999002156982919609085058710,31,37,44
336,336_0,RUNNING,BoTorch,BOTORCH_MODULAR,,191,0.006767322079922043903676964760,11,10,67
337,337_0,RUNNING,BoTorch,BOTORCH_MODULAR,,200,0.009130179879195661138413520064,24,100,19
338,338_0,RUNNING,BoTorch,BOTORCH_MODULAR,,198,0.010000000000000000208166817117,19,19,20
339,339_0,RUNNING,BoTorch,BOTORCH_MODULAR,,199,0.006120715678959642511158811828,9,36,94
340,340_0,RUNNING,BoTorch,BOTORCH_MODULAR,,166,0.006052328243896887977060217167,9,51,100
341,341_0,RUNNING,BoTorch,BOTORCH_MODULAR,,199,0.007480037307678853025771914531,19,10,63
342,342_0,RUNNING,BoTorch,BOTORCH_MODULAR,,134,0.006649065335040425968327060247,13,94,98
343,343_0,RUNNING,BoTorch,BOTORCH_MODULAR,,171,0.006060800778925073614700202995,6,88,41
344,344_0,RUNNING,BoTorch,BOTORCH_MODULAR,,199,0.007390091014643066814893135330,10,13,78
345,345_0,RUNNING,BoTorch,BOTORCH_MODULAR,,172,0.005118832947024146845516057169,5,16,95
346,346_0,RUNNING,BoTorch,BOTORCH_MODULAR,,196,0.006318060363255504144341934136,14,10,77
347,347_0,RUNNING,BoTorch,BOTORCH_MODULAR,,200,0.003110382722629966793098654776,4,88,76
348,348_0,RUNNING,BoTorch,BOTORCH_MODULAR,,160,0.007329839398934116095896129650,16,15,33
349,349_0,RUNNING,BoTorch,BOTORCH_MODULAR,,152,0.007336594368444059217904129611,9,97,87
</pre>
			<button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("tab_results_csv_table_pre")'> Copy raw data to clipboard</button>
			<button onclick='download_as_file("tab_results_csv_table_pre", "results.csv")'> Download &raquo;results.csv&laquo; as file</button>
			<script>
				createTable(tab_results_csv_json, tab_results_headers_json, 'tab_results_csv_table');</script>
			
			<h1>&nbsp;Progressbar log</h1>
			<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>
<pre id='simple_pre_tab_tab_progressbar_log'>2025-05-06 14:11:09: SOBOL, Started OmniOpt2 run...
2025-05-06 14:11:17: SOBOL, getting new HP set #1/50
2025-05-06 14:11:20: Sobol, getting new HP set #2/50 | ETA: 13s
2025-05-06 14:11:23: Sobol, getting new HP set #3/50 | ETA: 11s
2025-05-06 14:11:26: Sobol, getting new HP set #4/50 | ETA: 9s 
2025-05-06 14:11:31: Sobol, getting new HP set #5/50 | ETA: 9s 
2025-05-06 14:11:37: Sobol, getting new HP set #6/50 | ETA: 8s 
2025-05-06 14:11:41: Sobol, getting new HP set #7/50 | ETA: 7s 
2025-05-06 14:11:45: Sobol, getting new HP set #8/50 | ETA: 7s 
2025-05-06 14:11:49: Sobol, getting new HP set #9/50 | ETA: 7s 
2025-05-06 14:11:52: Sobol, getting new HP set #10/50 | ETA: 7s
2025-05-06 14:11:55: Sobol, getting new HP set #11/50 | ETA: 6s
2025-05-06 14:11:59: Sobol, getting new HP set #12/50 | ETA: 6s
2025-05-06 14:12:02: Sobol, getting new HP set #13/50 | ETA: 6s
2025-05-06 14:12:06: Sobol, getting new HP set #14/50 | ETA: 6s
2025-05-06 14:12:09: Sobol, getting new HP set #15/50 | ETA: 5s
2025-05-06 14:12:12: Sobol, getting new HP set #16/50 | ETA: 5s
2025-05-06 14:12:15: Sobol, getting new HP set #17/50 | ETA: 5s
2025-05-06 14:12:19: Sobol, getting new HP set #18/50 | ETA: 5s
2025-05-06 14:12:22: Sobol, getting new HP set #19/50 | ETA: 5s
2025-05-06 14:12:26: Sobol, getting new HP set #20/50 | ETA: 5s
2025-05-06 14:12:30: Sobol, getting new HP set #21/50 | ETA: 4s
2025-05-06 14:12:35: Sobol, getting new HP set #22/50 | ETA: 4s
2025-05-06 14:12:41: Sobol, getting new HP set #23/50 | ETA: 4s
2025-05-06 14:12:44: Sobol, getting new HP set #24/50 | ETA: 4s
2025-05-06 14:12:47: Sobol, getting new HP set #25/50 | ETA: 4s
2025-05-06 14:12:51: Sobol, getting new HP set #26/50 | ETA: 4s
2025-05-06 14:12:54: Sobol, getting new HP set #27/50 | ETA: 3s
2025-05-06 14:12:58: Sobol, getting new HP set #28/50 | ETA: 3s
2025-05-06 14:13:03: Sobol, getting new HP set #29/50 | ETA: 3s
2025-05-06 14:13:06: Sobol, getting new HP set #30/50 | ETA: 3s
2025-05-06 14:13:09: Sobol, getting new HP set #31/50 | ETA: 3s
2025-05-06 14:13:14: Sobol, getting new HP set #32/50 | ETA: 3s
2025-05-06 14:13:18: Sobol, getting new HP set #33/50 | ETA: 3s
2025-05-06 14:13:21: Sobol, getting new HP set #34/50 | ETA: 2s
2025-05-06 14:13:23: Sobol, getting new HP set #35/50 | ETA: 2s
2025-05-06 14:13:26: Sobol, getting new HP set #36/50 | ETA: 2s
2025-05-06 14:13:29: Sobol, getting new HP set #37/50 | ETA: 2s
2025-05-06 14:13:35: Sobol, getting new HP set #38/50 | ETA: 2s
2025-05-06 14:13:41: Sobol, getting new HP set #39/50 | ETA: 2s
2025-05-06 14:13:44: Sobol, getting new HP set #40/50 | ETA: 1s
2025-05-06 14:13:47: Sobol, getting new HP set #41/50 | ETA: 1s
2025-05-06 14:13:51: Sobol, getting new HP set #42/50 | ETA: 1s
2025-05-06 14:13:53: Sobol, getting new HP set #43/50 | ETA: 1s
2025-05-06 14:13:56: Sobol, getting new HP set #44/50 | ETA: 1s
2025-05-06 14:13:59: Sobol, getting new HP set #45/50 | ETA: 1s
2025-05-06 14:14:01: Sobol, getting new HP set #46/50 | ETA: 0s
2025-05-06 14:14:04: Sobol, getting new HP set #47/50 | ETA: 0s
2025-05-06 14:14:07: Sobol, getting new HP set #48/50 | ETA: 0s
2025-05-06 14:14:10: Sobol, getting new HP set #49/50 | ETA: 0s
2025-05-06 14:14:13: Sobol, getting new HP set #50/50 | ETA: 0s
2025-05-06 14:14:17: Sobol, eval start                         
2025-05-06 14:14:22: Sobol, starting new job                   
2025-05-06 14:14:28: Sobol, unknown 1 = &sum;1/50, started new job 
2025-05-06 14:14:31: Sobol, pending 1 = &sum;1/50, eval start      
2025-05-06 14:14:37: Sobol, pending 1 = &sum;1/50, starting new job
2025-05-06 14:14:44: Sobol, running/unknown 1/1 = &sum;2/50, started new job
2025-05-06 14:14:50: Sobol, running/pending 1/1 = &sum;2/50, eval start     
2025-05-06 14:14:56: Sobol, running/pending 1/1 = &sum;2/50, starting new job
2025-05-06 14:15:03: Sobol, running/pending/unknown 1/1/1 = &sum;3/50, started new job
2025-05-06 14:15:08: Sobol, running/pending 1/2 = &sum;3/50, eval start               
2025-05-06 14:15:16: Sobol, running 3 = &sum;3/50, starting new job                   
2025-05-06 14:15:25: Sobol, running/unknown 3/1 = &sum;4/50, started new job          
2025-05-06 14:15:31: Sobol, running/pending 3/1 = &sum;4/50, eval start               
2025-05-06 14:15:37: Sobol, running/pending 3/1 = &sum;4/50, starting new job         
2025-05-06 14:15:48: Sobol, running/unknown 4/1 = &sum;5/50, started new job          
2025-05-06 14:15:55: Sobol, running/pending 4/1 = &sum;5/50, eval start               
2025-05-06 14:16:00: Sobol, running/pending 4/1 = &sum;5/50, starting new job         
2025-05-06 14:16:07: Sobol, running/pending/unknown 4/1/1 = &sum;6/50, started new job
2025-05-06 14:16:13: Sobol, running 6 = &sum;6/50, eval start                         
2025-05-06 14:16:19: Sobol, running 6 = &sum;6/50, starting new job                   
2025-05-06 14:16:26: Sobol, running/unknown 6/1 = &sum;7/50, started new job          
2025-05-06 14:16:31: Sobol, running/pending 6/1 = &sum;7/50, eval start               
2025-05-06 14:16:37: Sobol, running/pending 6/1 = &sum;7/50, starting new job         
2025-05-06 14:16:46: Sobol, running/unknown 7/1 = &sum;8/50, started new job          
2025-05-06 14:16:52: Sobol, running/pending 7/1 = &sum;8/50, eval start               
2025-05-06 14:16:57: Sobol, running/pending 7/1 = &sum;8/50, starting new job         
2025-05-06 14:17:03: Sobol, running/completed/pending/unknown 2/5/1/1 = &sum;9/50, started new job
2025-05-06 14:17:07: Sobol, completed/running/pending 6/1/2 = &sum;9/50, eval start               
2025-05-06 14:17:12: Sobol, completed/running/pending 6/1/2 = &sum;9/50, starting new job         
2025-05-06 14:17:18: Sobol, completed/running/unknown 7/2/1 = &sum;10/50, started new job         
2025-05-06 14:17:24: Sobol, completed/running/pending 7/2/1 = &sum;10/50, eval start              
2025-05-06 14:17:29: Sobol, completed/running/pending 7/2/1 = &sum;10/50, starting new job        
2025-05-06 14:17:35: Sobol, completed/running/pending/unknown 7/2/1/1 = &sum;11/50, started new job
2025-05-06 14:17:39: Sobol, completed/running/pending 7/2/2 = &sum;11/50, eval start               
2025-05-06 14:17:48: Sobol, completed/running 8/3 = &sum;11/50, starting new job                   
2025-05-06 14:17:55: Sobol, completed/running/unknown 9/2/1 = &sum;12/50, started new job          
2025-05-06 14:17:59: Sobol, completed/running/pending 9/2/1 = &sum;12/50, eval start               
2025-05-06 14:18:05: Sobol, completed/running/pending 9/2/1 = &sum;12/50, starting new job         
2025-05-06 14:18:10: Sobol, completed/running/pending/unknown 9/2/1/1 = &sum;13/50, started new job
2025-05-06 14:18:19: Sobol, completed/running 11/2 = &sum;13/50, eval start                        
2025-05-06 14:18:25: Sobol, completed/running 11/2 = &sum;13/50, starting new job                  
2025-05-06 14:18:31: Sobol, completed/running/unknown 11/2/1 = &sum;14/50, started new job         
2025-05-06 14:18:37: Sobol, completed/running/pending 11/2/1 = &sum;14/50, eval start              
2025-05-06 14:18:43: Sobol, completed/running/pending 11/2/1 = &sum;14/50, starting new job        
2025-05-06 14:18:51: Sobol, completed/running/unknown 12/2/1 = &sum;15/50, started new job         
2025-05-06 14:18:57: Sobol, completed/running/pending 13/1/1 = &sum;15/50, eval start              
2025-05-06 14:19:03: Sobol, completed/running/pending 13/1/1 = &sum;15/50, starting new job        
2025-05-06 14:19:10: Sobol, completed/running/pending/unknown 13/1/1/1 = &sum;16/50, started new job
2025-05-06 14:19:17: Sobol, completed/running 13/3 = &sum;16/50, eval start                         
2025-05-06 14:19:26: Sobol, completed/running 13/3 = &sum;16/50, starting new job                   
2025-05-06 14:19:35: Sobol, completed/running/unknown 13/3/1 = &sum;17/50, started new job          
2025-05-06 14:19:43: Sobol, completed/running 13/4 = &sum;17/50, eval start                         
2025-05-06 14:19:52: Sobol, completed/running 13/4 = &sum;17/50, starting new job                   
2025-05-06 14:19:59: Sobol, completed/running/unknown 13/4/1 = &sum;18/50, started new job          
2025-05-06 14:20:04: Sobol, completed/running/pending 15/2/1 = &sum;18/50, eval start               
2025-05-06 14:20:09: Sobol, completed/running/pending 15/2/1 = &sum;18/50, starting new job         
2025-05-06 14:20:15: Sobol, completed/running/unknown 16/2/1 = &sum;19/50, started new job          
2025-05-06 14:20:19: Sobol, completed/running/unknown 17/1/1 = &sum;19/50, eval start               
2025-05-06 14:20:24: Sobol, completed/running/unknown 17/1/1 = &sum;19/50, starting new job         
2025-05-06 14:20:30: Sobol, completed/running/pending/unknown 17/1/1/1 = &sum;20/50, started new job
2025-05-06 14:20:35: Sobol, completed/running/pending 17/1/2 = &sum;20/50, eval start               
2025-05-06 14:20:41: Sobol, completed/running/pending 17/1/2 = &sum;20/50, starting new job         
2025-05-06 14:20:51: Sobol, completed/running/unknown 17/3/1 = &sum;21/50, started new job          
2025-05-06 14:20:58: Sobol, completed/running/pending 17/3/1 = &sum;21/50, eval start               
2025-05-06 14:21:06: Sobol, completed/running/pending 17/3/1 = &sum;21/50, starting new job         
2025-05-06 14:21:13: Sobol, completed/running/pending/unknown 17/3/1/1 = &sum;22/50, started new job
2025-05-06 14:21:22: Sobol, completed/running 18/4 = &sum;22/50, eval start                         
2025-05-06 14:21:29: Sobol, completed/running 18/4 = &sum;22/50, starting new job                   
2025-05-06 14:21:36: Sobol, completed/running/unknown 19/3/1 = &sum;23/50, started new job          
2025-05-06 14:21:40: Sobol, completed/running/pending 19/3/1 = &sum;23/50, eval start               
2025-05-06 14:21:47: Sobol, completed/running 20/3 = &sum;23/50, starting new job                   
2025-05-06 14:21:54: Sobol, completed/running/unknown 22/1/1 = &sum;24/50, started new job          
2025-05-06 14:21:58: Sobol, completed/running/pending 22/1/1 = &sum;24/50, eval start               
2025-05-06 14:22:01: Sobol, completed/running/pending 22/1/1 = &sum;24/50, starting new job         
2025-05-06 14:22:07: Sobol, completed/running/pending/unknown 22/1/1/1 = &sum;25/50, started new job
2025-05-06 14:22:10: Sobol, completed/running/pending 22/1/2 = &sum;25/50, eval start               
2025-05-06 14:22:14: Sobol, completed/running/pending 22/1/2 = &sum;25/50, starting new job         
2025-05-06 14:22:20: Sobol, completed/running/unknown 22/3/1 = &sum;26/50, started new job          
2025-05-06 14:22:25: Sobol, completed/running/pending 23/2/1 = &sum;26/50, eval start               
2025-05-06 14:22:31: Sobol, completed/running/pending 23/2/1 = &sum;26/50, starting new job         
2025-05-06 14:22:38: Sobol, completed/running/pending/unknown 23/2/1/1 = &sum;27/50, started new job
2025-05-06 14:22:43: Sobol, completed/running/pending 23/2/2 = &sum;27/50, eval start               
2025-05-06 14:22:51: Sobol, completed/running 24/3 = &sum;27/50, starting new job                   
2025-05-06 14:22:57: Sobol, completed/running/unknown 24/3/1 = &sum;28/50, started new job          
2025-05-06 14:23:02: Sobol, completed/running/pending 25/2/1 = &sum;28/50, eval start               
2025-05-06 14:23:06: Sobol, completed/running/pending 25/2/1 = &sum;28/50, starting new job         
2025-05-06 14:23:13: Sobol, completed/running/pending/unknown 26/1/1/1 = &sum;29/50, started new job
2025-05-06 14:23:19: Sobol, completed/running 27/2 = &sum;29/50, eval start                         
2025-05-06 14:23:25: Sobol, completed/running 27/2 = &sum;29/50, starting new job                   
2025-05-06 14:23:32: Sobol, completed/running/unknown 27/2/1 = &sum;30/50, started new job          
2025-05-06 14:23:37: Sobol, completed/running/pending 27/2/1 = &sum;30/50, eval start               
2025-05-06 14:23:43: Sobol, completed/running/pending 27/2/1 = &sum;30/50, starting new job         
2025-05-06 14:23:51: Sobol, completed/running/unknown 28/2/1 = &sum;31/50, started new job          
2025-05-06 14:23:56: Sobol, completed/running/unknown 29/1/1 = &sum;31/50, eval start               
2025-05-06 14:24:00: Sobol, completed/running/unknown 29/1/1 = &sum;31/50, starting new job         
2025-05-06 14:24:06: Sobol, completed/running/pending/unknown 29/1/1/1 = &sum;32/50, started new job
2025-05-06 14:24:10: Sobol, completed/pending 30/2 = &sum;32/50, eval start                         
2025-05-06 14:24:14: Sobol, completed/pending 30/2 = &sum;32/50, starting new job                   
2025-05-06 14:24:20: Sobol, completed/running/unknown 30/2/1 = &sum;33/50, started new job          
2025-05-06 14:24:25: Sobol, completed/running/pending 30/2/1 = &sum;33/50, eval start               
2025-05-06 14:24:31: Sobol, completed/running/pending 30/2/1 = &sum;33/50, starting new job         
2025-05-06 14:24:39: Sobol, completed/running/pending/unknown 30/2/1/1 = &sum;34/50, started new job
2025-05-06 14:24:46: Sobol, completed/running 30/4 = &sum;34/50, eval start                         
2025-05-06 14:24:52: Sobol, completed/running 30/4 = &sum;34/50, starting new job                   
2025-05-06 14:24:59: Sobol, completed/running/unknown 32/2/1 = &sum;35/50, started new job          
2025-05-06 14:25:04: Sobol, completed/running/pending 32/2/1 = &sum;35/50, eval start               
2025-05-06 14:25:10: Sobol, completed/running/pending 32/2/1 = &sum;35/50, starting new job         
2025-05-06 14:25:15: Sobol, completed/running/pending/unknown 33/1/1/1 = &sum;36/50, started new job
2025-05-06 14:25:20: Sobol, completed/running 34/2 = &sum;36/50, eval start                         
2025-05-06 14:25:25: Sobol, completed/running 34/2 = &sum;36/50, starting new job                   
2025-05-06 14:25:32: Sobol, completed/running/unknown 34/2/1 = &sum;37/50, started new job          
2025-05-06 14:25:37: Sobol, completed/running/pending 34/2/1 = &sum;37/50, eval start               
2025-05-06 14:25:44: Sobol, completed/running/pending 34/2/1 = &sum;37/50, starting new job         
2025-05-06 14:25:51: Sobol, completed/running/unknown 36/1/1 = &sum;38/50, started new job          
2025-05-06 14:25:58: Sobol, completed/running/pending 36/1/1 = &sum;38/50, eval start               
2025-05-06 14:26:03: Sobol, completed/running/pending 36/1/1 = &sum;38/50, starting new job         
2025-05-06 14:26:09: Sobol, completed/running/pending/unknown 36/1/1/1 = &sum;39/50, started new job
2025-05-06 14:26:13: Sobol, completed/running/pending 36/1/2 = &sum;39/50, eval start               
2025-05-06 14:26:19: Sobol, completed/running 37/2 = &sum;39/50, starting new job                   
2025-05-06 14:26:26: Sobol, completed/running/unknown 37/2/1 = &sum;40/50, started new job          
2025-05-06 14:26:32: Sobol, completed/running/pending 37/2/1 = &sum;40/50, eval start               
2025-05-06 14:26:37: Sobol, completed/running/pending 37/2/1 = &sum;40/50, starting new job         
2025-05-06 14:26:44: Sobol, completed/running/pending/unknown 38/1/1/1 = &sum;41/50, started new job
2025-05-06 14:26:49: Sobol, completed/running 39/2 = &sum;41/50, eval start                         
2025-05-06 14:26:54: Sobol, completed/running 39/2 = &sum;41/50, starting new job                   
2025-05-06 14:27:02: Sobol, completed/running/unknown 39/2/1 = &sum;42/50, started new job          
2025-05-06 14:27:07: Sobol, completed/running/pending 39/2/1 = &sum;42/50, eval start               
2025-05-06 14:27:12: Sobol, completed/running/pending 39/2/1 = &sum;42/50, starting new job         
2025-05-06 14:27:17: Sobol, completed/pending/unknown 41/1/1 = &sum;43/50, started new job          
2025-05-06 14:27:23: Sobol, completed/running 41/2 = &sum;43/50, eval start                         
2025-05-06 14:27:28: Sobol, completed/running 41/2 = &sum;43/50, starting new job                   
2025-05-06 14:27:34: Sobol, completed/running/unknown 41/2/1 = &sum;44/50, started new job          
2025-05-06 14:27:40: Sobol, completed/running/pending 41/2/1 = &sum;44/50, eval start               
2025-05-06 14:27:45: Sobol, completed/running/pending 41/2/1 = &sum;44/50, starting new job         
2025-05-06 14:27:52: Sobol, completed/running/unknown 43/1/1 = &sum;45/50, started new job          
2025-05-06 14:27:57: Sobol, completed/running/pending 43/1/1 = &sum;45/50, eval start               
2025-05-06 14:28:03: Sobol, completed/running/pending 43/1/1 = &sum;45/50, starting new job         
2025-05-06 14:28:09: Sobol, completed/running/pending/unknown 43/1/1/1 = &sum;46/50, started new job
2025-05-06 14:28:14: Sobol, completed/running/pending 43/1/2 = &sum;46/50, eval start               
2025-05-06 14:28:18: Sobol, completed/running/pending 43/1/2 = &sum;46/50, starting new job         
2025-05-06 14:28:25: Sobol, completed/running/unknown 44/2/1 = &sum;47/50, started new job          
2025-05-06 14:28:30: Sobol, completed/running/pending 44/2/1 = &sum;47/50, eval start               
2025-05-06 14:28:38: Sobol, completed/running/pending 44/2/1 = &sum;47/50, starting new job         
2025-05-06 14:28:44: Sobol, completed/pending/unknown 46/1/1 = &sum;48/50, started new job          
2025-05-06 14:28:48: Sobol, completed/pending 46/2 = &sum;48/50, eval start                         
2025-05-06 14:28:53: Sobol, completed/pending 46/2 = &sum;48/50, starting new job                   
2025-05-06 14:29:01: Sobol, completed/running/pending 46/2/1 = &sum;49/50, started new job          
2025-05-06 14:29:07: Sobol, completed/running/pending 46/2/1 = &sum;49/50, eval start               
2025-05-06 14:29:12: Sobol, completed/running/pending 46/2/1 = &sum;49/50, starting new job         
2025-05-06 14:29:18: Sobol, completed/running/pending/unknown 47/1/1/1 = &sum;50/50, started new job
2025-05-06 14:29:23: Sobol, completed/running 47/3 = &sum;50/50, new result: 0.21578947368421053    
2025-05-06 14:29:41: Sobol, best RESULT: 0.21578947368421053, completed/running 47/2 = &sum;49/50, new result: 0.35789473684210527
2025-05-06 14:29:53: Sobol, best RESULT: 0.21578947368421053, completed 48 = &sum;48/50, new result: 0.37368421052631584          
2025-05-06 14:30:03: Sobol, best RESULT: 0.21578947368421053, completed 47 = &sum;47/50, new result: 0.2789473684210526           
2025-05-06 14:30:12: Sobol, best RESULT: 0.21578947368421053, completed 46 = &sum;46/50, new result: 0.4368421052631579           
2025-05-06 14:30:23: Sobol, best RESULT: 0.21578947368421053, completed 45 = &sum;45/50, new result: 0.2894736842105263           
2025-05-06 14:30:35: Sobol, best RESULT: 0.21578947368421053, completed 44 = &sum;44/50, new result: 0.3421052631578947           
2025-05-06 14:30:47: Sobol, best RESULT: 0.21578947368421053, completed 43 = &sum;43/50, new result: 0.2210526315789474           
2025-05-06 14:30:58: Sobol, best RESULT: 0.21578947368421053, completed 42 = &sum;42/50, new result: 0.3052631578947368           
2025-05-06 14:31:08: Sobol, best RESULT: 0.21578947368421053, completed 41 = &sum;41/50, new result: 0.2789473684210526           
2025-05-06 14:31:17: Sobol, best RESULT: 0.21578947368421053, completed 40 = &sum;40/50, new result: 0.4789473684210527           
2025-05-06 14:31:27: Sobol, best RESULT: 0.21578947368421053, completed 39 = &sum;39/50, new result: 0.2789473684210526           
2025-05-06 14:31:42: Sobol, best RESULT: 0.21578947368421053, completed 38 = &sum;38/50, new result: 0.3526315789473684           
2025-05-06 14:31:58: Sobol, best RESULT: 0.21578947368421053, completed 37 = &sum;37/50, new result: 0.3894736842105263           
2025-05-06 14:32:08: Sobol, best RESULT: 0.21578947368421053, completed 36 = &sum;36/50, new result: 0.3421052631578947           
2025-05-06 14:32:19: Sobol, best RESULT: 0.21578947368421053, completed 35 = &sum;35/50, new result: 0.30000000000000004          
2025-05-06 14:32:33: Sobol, best RESULT: 0.21578947368421053, completed 34 = &sum;34/50, new result: 0.33684210526315794          
2025-05-06 14:32:44: Sobol, best RESULT: 0.21578947368421053, completed 33 = &sum;33/50, new result: 0.2578947368421053           
2025-05-06 14:32:55: Sobol, best RESULT: 0.21578947368421053, completed 32 = &sum;32/50, new result: 0.30000000000000004          
2025-05-06 14:33:08: Sobol, best RESULT: 0.21578947368421053, completed 31 = &sum;31/50, new result: 0.31052631578947365          
2025-05-06 14:33:23: Sobol, best RESULT: 0.21578947368421053, completed 30 = &sum;30/50, new result: 0.3526315789473684           
2025-05-06 14:33:45: Sobol, best RESULT: 0.21578947368421053, completed 29 = &sum;29/50, new result: 0.31052631578947365          
2025-05-06 14:34:01: Sobol, best RESULT: 0.21578947368421053, completed 28 = &sum;28/50, new result: 0.3631578947368421           
2025-05-06 14:34:16: Sobol, best RESULT: 0.21578947368421053, completed 27 = &sum;27/50, new result: 0.2315789473684211           
2025-05-06 14:34:29: Sobol, best RESULT: 0.21578947368421053, completed 26 = &sum;26/50, new result: 0.3263157894736842           
2025-05-06 14:34:40: Sobol, best RESULT: 0.21578947368421053, completed 25 = &sum;25/50, new result: 0.2684210526315789           
2025-05-06 14:34:51: Sobol, best RESULT: 0.21578947368421053, completed 24 = &sum;24/50, new result: 0.3421052631578947           
2025-05-06 14:35:02: Sobol, best RESULT: 0.21578947368421053, completed 23 = &sum;23/50, new result: 0.27368421052631575          
2025-05-06 14:35:13: Sobol, best RESULT: 0.21578947368421053, completed 22 = &sum;22/50, new result: 0.28421052631578947          
2025-05-06 14:35:27: Sobol, best RESULT: 0.21578947368421053, completed 21 = &sum;21/50, new result: 0.35789473684210527          
2025-05-06 14:35:45: Sobol, best RESULT: 0.21578947368421053, completed 20 = &sum;20/50, new result: 0.2947368421052632           
2025-05-06 14:35:56: Sobol, best RESULT: 0.21578947368421053, completed 19 = &sum;19/50, new result: 0.2947368421052632           
2025-05-06 14:36:08: Sobol, best RESULT: 0.21578947368421053, completed 18 = &sum;18/50, new result: 0.38421052631578945          
2025-05-06 14:36:20: Sobol, best RESULT: 0.21578947368421053, completed 17 = &sum;17/50, new result: 0.20526315789473681          
2025-05-06 14:36:35: Sobol, best RESULT: 0.20526315789473681, completed 16 = &sum;16/50, new result: 0.3526315789473684           
2025-05-06 14:36:55: Sobol, best RESULT: 0.20526315789473681, completed 15 = &sum;15/50, new result: 0.28421052631578947          
2025-05-06 14:37:13: Sobol, best RESULT: 0.20526315789473681, completed 14 = &sum;14/50, new result: 0.2894736842105263           
2025-05-06 14:37:33: Sobol, best RESULT: 0.20526315789473681, completed 13 = &sum;13/50, new result: 0.3631578947368421           
2025-05-06 14:37:53: Sobol, best RESULT: 0.20526315789473681, completed 12 = &sum;12/50, new result: 0.4736842105263158           
2025-05-06 14:38:18: Sobol, best RESULT: 0.20526315789473681, completed 11 = &sum;11/50, new result: 0.3157894736842105           
2025-05-06 14:38:41: Sobol, best RESULT: 0.20526315789473681, completed 10 = &sum;10/50, new result: 0.32105263157894737          
2025-05-06 14:38:56: Sobol, best RESULT: 0.20526315789473681, completed 9 = &sum;9/50, new result: 0.39473684210526316            
2025-05-06 14:39:07: Sobol, best RESULT: 0.20526315789473681, completed 8 = &sum;8/50, new result: 0.3789473684210526             
2025-05-06 14:39:19: Sobol, best RESULT: 0.20526315789473681, completed 7 = &sum;7/50, new result: 0.3263157894736842             
2025-05-06 14:39:31: Sobol, best RESULT: 0.20526315789473681, completed 6 = &sum;6/50, new result: 0.30000000000000004            
2025-05-06 14:39:48: Sobol, best RESULT: 0.20526315789473681, completed 5 = &sum;5/50, new result: 0.22631578947368425            
2025-05-06 14:40:00: Sobol, best RESULT: 0.20526315789473681, completed 4 = &sum;4/50, new result: 0.33684210526315794            
2025-05-06 14:40:16: Sobol, best RESULT: 0.20526315789473681, completed 3 = &sum;3/50, new result: 0.24736842105263157            
2025-05-06 14:40:44: Sobol, best RESULT: 0.20526315789473681, completed 2 = &sum;2/50, new result: 0.3315789473684211             
2025-05-06 14:40:59: Sobol, best RESULT: 0.20526315789473681, completed 1 = &sum;1/50, new result: 0.30000000000000004            
2025-05-06 14:41:12: Sobol, best RESULT: 0.20526315789473681, finishing jobs, finished 50 jobs                                
2025-05-06 14:41:20: Sobol, best RESULT: 0.20526315789473681, getting new HP set #1/50                                        
2025-05-06 14:41:44: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #2/50 | ETA: 11m 4s                   
2025-05-06 14:41:53: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #3/50 | ETA: 6m 14s                   
2025-05-06 14:42:08: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #4/50 | ETA: 5m 19s                   
2025-05-06 14:42:16: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #5/50 | ETA: 4m 22s                   
2025-05-06 14:42:23: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #6/50 | ETA: 3m 40s                   
2025-05-06 14:42:33: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #7/50 | ETA: 3m 12s                   
2025-05-06 14:42:47: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #8/50 | ETA: 2m 53s                   
2025-05-06 14:42:54: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #9/50 | ETA: 2m 37s                   
2025-05-06 14:43:02: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #10/50 | ETA: 2m 26s                  
2025-05-06 14:43:10: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #11/50 | ETA: 2m 15s                  
2025-05-06 14:43:20: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #12/50 | ETA: 2m 7s                   
2025-05-06 14:43:33: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #13/50 | ETA: 2m 1s                   
2025-05-06 14:43:42: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #14/50 | ETA: 1m 54s                  
2025-05-06 14:43:50: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #15/50 | ETA: 1m 48s                  
2025-05-06 14:43:59: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #16/50 | ETA: 1m 44s                  
2025-05-06 14:44:06: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #17/50 | ETA: 1m 39s                  
2025-05-06 14:44:15: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #18/50 | ETA: 1m 36s                  
2025-05-06 14:44:25: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #19/50 | ETA: 1m 31s                  
2025-05-06 14:44:36: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #20/50 | ETA: 1m 27s                  
2025-05-06 14:44:49: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #21/50 | ETA: 1m 24s                  
2025-05-06 14:44:59: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #22/50 | ETA: 1m 21s                  
2025-05-06 14:45:15: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #23/50 | ETA: 1m 20s                  
2025-05-06 14:45:25: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #24/50 | ETA: 1m 18s                  
2025-05-06 14:45:38: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #25/50 | ETA: 1m 15s                  
2025-05-06 14:45:50: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #26/50 | ETA: 1m 13s                  
2025-05-06 14:46:01: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #27/50 | ETA: 1m 10s                  
2025-05-06 14:46:12: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #28/50 | ETA: 1m 8s                   
2025-05-06 14:46:26: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #29/50 | ETA: 1m 6s                   
2025-05-06 14:46:39: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #30/50 | ETA: 1m 3s                   
2025-05-06 14:46:50: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #31/50 | ETA: 1m 1s                   
2025-05-06 14:47:05: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #32/50 | ETA: 58s                     
2025-05-06 14:47:19: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #33/50 | ETA: 55s                     
2025-05-06 14:47:33: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #34/50 | ETA: 53s                     
2025-05-06 14:47:43: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #35/50 | ETA: 50s                     
2025-05-06 14:47:54: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #36/50 | ETA: 47s                     
2025-05-06 14:48:07: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #37/50 | ETA: 45s                     
2025-05-06 14:48:28: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #38/50 | ETA: 42s                     
2025-05-06 14:48:43: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #39/50 | ETA: 40s                     
2025-05-06 14:48:53: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #40/50 | ETA: 37s                     
2025-05-06 14:49:06: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #41/50 | ETA: 34s                     
2025-05-06 14:49:21: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #42/50 | ETA: 31s                     
2025-05-06 14:49:37: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #43/50 | ETA: 28s                     
2025-05-06 14:49:50: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #44/50 | ETA: 24s                     
2025-05-06 14:50:03: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #45/50 | ETA: 21s                     
2025-05-06 14:50:20: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #46/50 | ETA: 17s                     
2025-05-06 14:50:32: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #47/50 | ETA: 14s                     
2025-05-06 14:50:52: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #48/50 | ETA: 10s                     
2025-05-06 14:51:06: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #49/50 | ETA: 7s                      
2025-05-06 14:51:23: BoTorchModel, best RESULT: 0.20526315789473681, getting new HP set #50/50 | ETA: 3s                      
2025-05-06 14:51:38: BoTorchModel, best RESULT: 0.20526315789473681, eval start                                               
2025-05-06 14:51:48: BoTorchModel, best RESULT: 0.20526315789473681, starting new job                                         
2025-05-06 14:52:00: BoTorchModel, best RESULT: 0.20526315789473681, unknown 1 = &sum;1/50, started new job                       
2025-05-06 14:52:07: BoTorchModel, best RESULT: 0.20526315789473681, pending 1 = &sum;1/50, eval start                            
2025-05-06 14:52:24: BoTorchModel, best RESULT: 0.20526315789473681, running 1 = &sum;1/50, starting new job                      
2025-05-06 14:52:34: BoTorchModel, best RESULT: 0.20526315789473681, running/unknown 1/1 = &sum;2/50, started new job             
2025-05-06 14:52:44: BoTorchModel, best RESULT: 0.20526315789473681, running 2 = &sum;2/50, eval start                            
2025-05-06 14:52:54: BoTorchModel, best RESULT: 0.20526315789473681, running 2 = &sum;2/50, starting new job                      
2025-05-06 14:53:04: BoTorchModel, best RESULT: 0.20526315789473681, running/unknown 2/1 = &sum;3/50, started new job             
2025-05-06 14:53:19: BoTorchModel, best RESULT: 0.20526315789473681, running 3 = &sum;3/50, eval start                            
2025-05-06 14:53:31: BoTorchModel, best RESULT: 0.20526315789473681, running 3 = &sum;3/50, starting new job                      
2025-05-06 14:53:40: BoTorchModel, best RESULT: 0.20526315789473681, running/unknown 3/1 = &sum;4/50, started new job             
2025-05-06 14:53:50: BoTorchModel, best RESULT: 0.20526315789473681, running 4 = &sum;4/50, eval start                            
2025-05-06 14:54:08: BoTorchModel, best RESULT: 0.20526315789473681, running/completed 3/1 = &sum;4/50, starting new job          
2025-05-06 14:54:21: BoTorchModel, best RESULT: 0.20526315789473681, running/completed/unknown 2/2/1 = &sum;5/50, started new job 
2025-05-06 14:54:31: BoTorchModel, best RESULT: 0.20526315789473681, running/completed/pending 2/2/1 = &sum;5/50, eval start      
2025-05-06 14:54:40: BoTorchModel, best RESULT: 0.20526315789473681, running/completed/pending 2/2/1 = &sum;5/50, starting new job
2025-05-06 14:55:01: BoTorchModel, best RESULT: 0.20526315789473681, running/completed/unknown 3/2/1 = &sum;6/50, started new job 
2025-05-06 14:55:29: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 4/2 = &sum;6/50, eval start                
2025-05-06 14:55:43: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 4/2 = &sum;6/50, starting new job          
2025-05-06 14:55:56: BoTorchModel, best RESULT: 0.20526315789473681, completed/unknown 6/1 = &sum;7/50, started new job           
2025-05-06 14:56:15: BoTorchModel, best RESULT: 0.20526315789473681, completed/pending 6/1 = &sum;7/50, eval start                
2025-05-06 14:56:29: BoTorchModel, best RESULT: 0.20526315789473681, completed/pending 6/1 = &sum;7/50, starting new job          
2025-05-06 14:56:44: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 6/1/1 = &sum;8/50, started new job 
2025-05-06 14:56:56: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 7/1 = &sum;8/50, eval start                
2025-05-06 14:57:08: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 7/1 = &sum;8/50, starting new job          
2025-05-06 14:57:17: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 7/1/1 = &sum;9/50, started new job 
2025-05-06 14:57:26: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 8/1 = &sum;9/50, eval start                
2025-05-06 14:57:33: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 8/1 = &sum;9/50, starting new job          
2025-05-06 14:57:43: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 8/1/1 = &sum;10/50, started new job
2025-05-06 14:57:51: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 9/1 = &sum;10/50, eval start               
2025-05-06 14:58:02: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 9/1 = &sum;10/50, starting new job         
2025-05-06 14:58:12: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 9/1/1 = &sum;11/50, started new job
2025-05-06 14:58:19: BoTorchModel, best RESULT: 0.20526315789473681, completed/pending 10/1 = &sum;11/50, eval start              
2025-05-06 14:58:26: BoTorchModel, best RESULT: 0.20526315789473681, completed/pending 10/1 = &sum;11/50, starting new job        
2025-05-06 14:58:34: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 10/1/1 = &sum;12/50, started new job
2025-05-06 14:58:41: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 10/1/1 = &sum;12/50, eval start     
2025-05-06 14:58:48: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 10/1/1 = &sum;12/50, starting new job
2025-05-06 14:59:00: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 11/1/1 = &sum;13/50, started new job 
2025-05-06 14:59:09: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 11/1/1 = &sum;13/50, eval start      
2025-05-06 14:59:16: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 11/1/1 = &sum;13/50, starting new job
2025-05-06 14:59:25: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 12/1/1 = &sum;14/50, started new job 
2025-05-06 14:59:32: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 12/1/1 = &sum;14/50, eval start      
2025-05-06 14:59:40: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 12/1/1 = &sum;14/50, starting new job
2025-05-06 14:59:48: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending/unknown 12/1/1/1 = &sum;15/50, started new job
2025-05-06 14:59:58: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 13/2 = &sum;15/50, eval start                         
2025-05-06 15:00:08: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 13/2 = &sum;15/50, starting new job                   
2025-05-06 15:00:16: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 13/2/1 = &sum;16/50, started new job          
2025-05-06 15:00:24: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 15/1 = &sum;16/50, eval start                         
2025-05-06 15:00:36: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 15/1 = &sum;16/50, starting new job                   
2025-05-06 15:00:44: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 15/1/1 = &sum;17/50, started new job          
2025-05-06 15:00:53: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 16/1 = &sum;17/50, eval start                         
2025-05-06 15:01:12: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 16/1 = &sum;17/50, starting new job                   
2025-05-06 15:01:22: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 16/1/1 = &sum;18/50, started new job          
2025-05-06 15:01:31: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 17/1 = &sum;18/50, eval start                         
2025-05-06 15:01:38: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 17/1 = &sum;18/50, starting new job                   
2025-05-06 15:01:47: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 17/1/1 = &sum;19/50, started new job          
2025-05-06 15:01:56: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 18/1 = &sum;19/50, eval start                         
2025-05-06 15:02:03: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 18/1 = &sum;19/50, starting new job                   
2025-05-06 15:02:12: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 18/1/1 = &sum;20/50, started new job          
2025-05-06 15:02:20: BoTorchModel, best RESULT: 0.20526315789473681, completed/pending 19/1 = &sum;20/50, eval start                         
2025-05-06 15:02:26: BoTorchModel, best RESULT: 0.20526315789473681, completed/pending 19/1 = &sum;20/50, starting new job                   
2025-05-06 15:02:34: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 19/1/1 = &sum;21/50, started new job          
2025-05-06 15:02:40: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 19/1/1 = &sum;21/50, eval start               
2025-05-06 15:02:45: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 19/1/1 = &sum;21/50, starting new job         
2025-05-06 15:02:55: BoTorchModel, best RESULT: 0.20526315789473681, completed/pending/unknown 20/1/1 = &sum;22/50, started new job          
2025-05-06 15:03:03: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 20/1/1 = &sum;22/50, eval start               
2025-05-06 15:03:10: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 20/1/1 = &sum;22/50, starting new job         
2025-05-06 15:03:19: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending/unknown 20/1/1/1 = &sum;23/50, started new job
2025-05-06 15:03:25: BoTorchModel, best RESULT: 0.20526315789473681, completed/pending 21/2 = &sum;23/50, eval start                         
2025-05-06 15:03:35: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 21/2 = &sum;23/50, starting new job                   
2025-05-06 15:03:45: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 21/2/1 = &sum;24/50, started new job          
2025-05-06 15:03:54: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 21/2/1 = &sum;24/50, eval start               
2025-05-06 15:04:03: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 21/2/1 = &sum;24/50, starting new job         
2025-05-06 15:04:17: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 22/2/1 = &sum;25/50, started new job          
2025-05-06 15:04:25: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 22/2/1 = &sum;25/50, eval start               
2025-05-06 15:04:32: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 22/2/1 = &sum;25/50, starting new job         
2025-05-06 15:04:42: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 22/3/1 = &sum;26/50, started new job          
2025-05-06 15:04:53: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 23/2/1 = &sum;26/50, eval start               
2025-05-06 15:05:03: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 23/2/1 = &sum;26/50, starting new job         
2025-05-06 15:05:14: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 24/2/1 = &sum;27/50, started new job          
2025-05-06 15:05:20: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 24/2/1 = &sum;27/50, eval start               
2025-05-06 15:05:28: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 24/2/1 = &sum;27/50, starting new job         
2025-05-06 15:05:42: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 25/2/1 = &sum;28/50, started new job          
2025-05-06 15:05:51: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 26/1/1 = &sum;28/50, eval start               
2025-05-06 15:06:00: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 26/1/1 = &sum;28/50, starting new job         
2025-05-06 15:06:10: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 27/1/1 = &sum;29/50, started new job          
2025-05-06 15:06:17: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 27/1/1 = &sum;29/50, eval start               
2025-05-06 15:06:25: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 27/1/1 = &sum;29/50, starting new job         
2025-05-06 15:06:34: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 27/2/1 = &sum;30/50, started new job          
2025-05-06 15:06:42: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 27/2/1 = &sum;30/50, eval start               
2025-05-06 15:06:50: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 27/2/1 = &sum;30/50, starting new job         
2025-05-06 15:06:59: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending/unknown 28/1/1/1 = &sum;31/50, started new job
2025-05-06 15:07:09: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 28/3 = &sum;31/50, eval start                         
2025-05-06 15:07:19: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 28/3 = &sum;31/50, starting new job                   
2025-05-06 15:07:28: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 30/1/1 = &sum;32/50, started new job          
2025-05-06 15:07:39: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 30/2 = &sum;32/50, eval start                         
2025-05-06 15:07:50: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 30/2 = &sum;32/50, starting new job                   
2025-05-06 15:08:00: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 31/1/1 = &sum;33/50, started new job          
2025-05-06 15:08:09: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 32/1 = &sum;33/50, eval start                         
2025-05-06 15:08:17: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 32/1 = &sum;33/50, starting new job                   
2025-05-06 15:08:27: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 32/1/1 = &sum;34/50, started new job          
2025-05-06 15:08:36: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 32/2 = &sum;34/50, eval start                         
2025-05-06 15:08:49: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 32/2 = &sum;34/50, starting new job                   
2025-05-06 15:08:59: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 33/1/1 = &sum;35/50, started new job          
2025-05-06 15:09:09: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 33/2 = &sum;35/50, eval start                         
2025-05-06 15:09:18: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 33/2 = &sum;35/50, starting new job                   
2025-05-06 15:09:29: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 34/1/1 = &sum;36/50, started new job          
2025-05-06 15:09:39: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 35/1 = &sum;36/50, eval start                         
2025-05-06 15:09:50: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 35/1 = &sum;36/50, starting new job                   
2025-05-06 15:10:00: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 35/1/1 = &sum;37/50, started new job          
2025-05-06 15:10:10: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 36/1 = &sum;37/50, eval start                         
2025-05-06 15:10:18: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 36/1 = &sum;37/50, starting new job                   
2025-05-06 15:10:29: BoTorchModel, best RESULT: 0.20526315789473681, completed/unknown 37/1 = &sum;38/50, started new job                    
2025-05-06 15:10:40: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 37/1 = &sum;38/50, eval start                         
2025-05-06 15:10:52: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 37/1 = &sum;38/50, starting new job                   
2025-05-06 15:11:06: BoTorchModel, best RESULT: 0.20526315789473681, completed/unknown 38/1 = &sum;39/50, started new job                    
2025-05-06 15:11:27: BoTorchModel, best RESULT: 0.20526315789473681, completed/pending 38/1 = &sum;39/50, eval start                         
2025-05-06 15:11:43: BoTorchModel, best RESULT: 0.20526315789473681, completed/pending 38/1 = &sum;39/50, starting new job                   
2025-05-06 15:12:04: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 38/1/1 = &sum;40/50, started new job          
2025-05-06 15:12:21: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 38/2 = &sum;40/50, eval start                         
2025-05-06 15:12:30: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 38/2 = &sum;40/50, starting new job                   
2025-05-06 15:12:41: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 39/1/1 = &sum;41/50, started new job          
2025-05-06 15:12:50: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 39/1/1 = &sum;41/50, eval start               
2025-05-06 15:12:59: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 39/1/1 = &sum;41/50, starting new job         
2025-05-06 15:13:09: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 39/2/1 = &sum;42/50, started new job          
2025-05-06 15:13:19: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 39/2/1 = &sum;42/50, eval start               
2025-05-06 15:13:29: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 39/2/1 = &sum;42/50, starting new job         
2025-05-06 15:13:42: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 39/3/1 = &sum;43/50, started new job          
2025-05-06 15:13:52: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 39/3/1 = &sum;43/50, eval start               
2025-05-06 15:14:02: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 39/3/1 = &sum;43/50, starting new job         
2025-05-06 15:14:14: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 40/3/1 = &sum;44/50, started new job          
2025-05-06 15:14:24: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 40/3/1 = &sum;44/50, eval start               
2025-05-06 15:14:34: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 40/3/1 = &sum;44/50, starting new job         
2025-05-06 15:14:45: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 41/3/1 = &sum;45/50, started new job          
2025-05-06 15:14:55: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 42/2/1 = &sum;45/50, eval start               
2025-05-06 15:15:02: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 42/2/1 = &sum;45/50, starting new job         
2025-05-06 15:15:11: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending/unknown 43/1/1/1 = &sum;46/50, started new job
2025-05-06 15:15:21: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 43/2/1 = &sum;46/50, eval start               
2025-05-06 15:15:30: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 43/2/1 = &sum;46/50, starting new job         
2025-05-06 15:15:42: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 44/2/1 = &sum;47/50, started new job          
2025-05-06 15:15:52: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 44/2/1 = &sum;47/50, eval start               
2025-05-06 15:16:01: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 44/2/1 = &sum;47/50, starting new job         
2025-05-06 15:16:10: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending/unknown 44/2/1/1 = &sum;48/50, started new job
2025-05-06 15:16:18: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 44/4 = &sum;48/50, eval start                         
2025-05-06 15:16:28: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 44/4 = &sum;48/50, starting new job                   
2025-05-06 15:16:42: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 47/1/1 = &sum;49/50, started new job          
2025-05-06 15:16:57: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 47/2 = &sum;49/50, eval start                         
2025-05-06 15:17:05: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 47/2 = &sum;49/50, starting new job                   
2025-05-06 15:17:16: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/unknown 48/1/1 = &sum;50/50, started new job          
2025-05-06 15:17:33: BoTorchModel, best RESULT: 0.20526315789473681, completed/running/pending 48/1/1 = &sum;50/50, new result: 0.3631578947368421
2025-05-06 15:18:00: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 47/2 = &sum;49/50, new result: 0.28421052631578947         
2025-05-06 15:18:23: BoTorchModel, best RESULT: 0.20526315789473681, completed/running 46/2 = &sum;48/50, new result: 0.26315789473684215         
2025-05-06 15:18:46: BoTorchModel, best RESULT: 0.20526315789473681, completed 47 = &sum;47/50, new result: 0.21052631578947367                   
2025-05-06 15:19:08: BoTorchModel, best RESULT: 0.20526315789473681, completed 46 = &sum;46/50, new result: 0.3631578947368421                    
2025-05-06 15:19:26: BoTorchModel, best RESULT: 0.20526315789473681, completed 45 = &sum;45/50, new result: 0.22631578947368425                   
2025-05-06 15:19:53: BoTorchModel, best RESULT: 0.20526315789473681, completed 44 = &sum;44/50, new result: 0.3421052631578947                    
2025-05-06 15:20:10: BoTorchModel, best RESULT: 0.20526315789473681, completed 43 = &sum;43/50, new result: 0.3631578947368421                    
2025-05-06 15:20:28: BoTorchModel, best RESULT: 0.20526315789473681, completed 42 = &sum;42/50, new result: 0.3631578947368421                    
2025-05-06 15:20:48: BoTorchModel, best RESULT: 0.20526315789473681, completed 41 = &sum;41/50, new result: 0.22631578947368425                   
2025-05-06 15:21:10: BoTorchModel, best RESULT: 0.20526315789473681, completed 40 = &sum;40/50, new result: 0.2315789473684211                    
2025-05-06 15:21:27: BoTorchModel, best RESULT: 0.20526315789473681, completed 39 = &sum;39/50, new result: 0.28421052631578947                   
2025-05-06 15:21:47: BoTorchModel, best RESULT: 0.20526315789473681, completed 38 = &sum;38/50, new result: 0.3631578947368421                    
2025-05-06 15:22:04: BoTorchModel, best RESULT: 0.20526315789473681, completed 37 = &sum;37/50, new result: 0.25263157894736843                   
2025-05-06 15:22:20: BoTorchModel, best RESULT: 0.20526315789473681, completed 36 = &sum;36/50, new result: 0.25263157894736843                   
2025-05-06 15:22:38: BoTorchModel, best RESULT: 0.20526315789473681, completed 35 = &sum;35/50, new result: 0.28421052631578947                   
2025-05-06 15:22:53: BoTorchModel, best RESULT: 0.20526315789473681, completed 34 = &sum;34/50, new result: 0.2210526315789474                    
2025-05-06 15:23:10: BoTorchModel, best RESULT: 0.20526315789473681, completed 33 = &sum;33/50, new result: 0.2315789473684211                    
2025-05-06 15:23:29: BoTorchModel, best RESULT: 0.20526315789473681, completed 32 = &sum;32/50, new result: 0.30000000000000004                   
2025-05-06 15:23:46: BoTorchModel, best RESULT: 0.20526315789473681, completed 31 = &sum;31/50, new result: 0.2210526315789474                    
2025-05-06 15:24:04: BoTorchModel, best RESULT: 0.20526315789473681, completed 30 = &sum;30/50, new result: 0.3631578947368421                    
2025-05-06 15:24:23: BoTorchModel, best RESULT: 0.20526315789473681, completed 29 = &sum;29/50, new result: 0.3631578947368421                    
2025-05-06 15:24:43: BoTorchModel, best RESULT: 0.20526315789473681, completed 28 = &sum;28/50, new result: 0.3631578947368421                    
2025-05-06 15:24:59: BoTorchModel, best RESULT: 0.20526315789473681, completed 27 = &sum;27/50, new result: 0.3157894736842105                    
2025-05-06 15:25:19: BoTorchModel, best RESULT: 0.20526315789473681, completed 26 = &sum;26/50, new result: 0.3157894736842105                    
2025-05-06 15:25:40: BoTorchModel, best RESULT: 0.20526315789473681, completed 25 = &sum;25/50, new result: 0.1947368421052632                    
2025-05-06 15:26:03: BoTorchModel, best RESULT: 0.1947368421052632, completed 24 = &sum;24/50, new result: 0.2210526315789474                     
2025-05-06 15:26:28: BoTorchModel, best RESULT: 0.1947368421052632, completed 23 = &sum;23/50, new result: 0.368421052631579                      
2025-05-06 15:26:46: BoTorchModel, best RESULT: 0.1947368421052632, completed 22 = &sum;22/50, new result: 0.21578947368421053                    
2025-05-06 15:27:05: BoTorchModel, best RESULT: 0.1947368421052632, completed 21 = &sum;21/50, new result: 0.22631578947368425                    
2025-05-06 15:27:28: BoTorchModel, best RESULT: 0.1947368421052632, completed 20 = &sum;20/50, new result: 0.2789473684210526                     
2025-05-06 15:27:52: BoTorchModel, best RESULT: 0.1947368421052632, completed 19 = &sum;19/50, new result: 0.3631578947368421                     
2025-05-06 15:28:13: BoTorchModel, best RESULT: 0.1947368421052632, completed 18 = &sum;18/50, new result: 0.25263157894736843                    
2025-05-06 15:28:40: BoTorchModel, best RESULT: 0.1947368421052632, completed 17 = &sum;17/50, new result: 0.3631578947368421                     
2025-05-06 15:28:56: BoTorchModel, best RESULT: 0.1947368421052632, completed 16 = &sum;16/50, new result: 0.2421052631578947                     
2025-05-06 15:29:11: BoTorchModel, best RESULT: 0.1947368421052632, completed 15 = &sum;15/50, new result: 0.3631578947368421                     
2025-05-06 15:29:28: BoTorchModel, best RESULT: 0.1947368421052632, completed 14 = &sum;14/50, new result: 0.26315789473684215                    
2025-05-06 15:29:45: BoTorchModel, best RESULT: 0.1947368421052632, completed 13 = &sum;13/50, new result: 0.35789473684210527                    
2025-05-06 15:30:01: BoTorchModel, best RESULT: 0.1947368421052632, completed 12 = &sum;12/50, new result: 0.3631578947368421                     
2025-05-06 15:30:24: BoTorchModel, best RESULT: 0.1947368421052632, completed 11 = &sum;11/50, new result: 0.3631578947368421                     
2025-05-06 15:30:40: BoTorchModel, best RESULT: 0.1947368421052632, completed 10 = &sum;10/50, new result: 0.3631578947368421                     
2025-05-06 15:30:57: BoTorchModel, best RESULT: 0.1947368421052632, completed 9 = &sum;9/50, new result: 0.19999999999999996                      
2025-05-06 15:31:21: BoTorchModel, best RESULT: 0.1947368421052632, completed 8 = &sum;8/50, new result: 0.3631578947368421                       
2025-05-06 15:31:38: BoTorchModel, best RESULT: 0.1947368421052632, completed 7 = &sum;7/50, new result: 0.4157894736842105                       
2025-05-06 15:31:58: BoTorchModel, best RESULT: 0.1947368421052632, completed 6 = &sum;6/50, new result: 0.35789473684210527                      
2025-05-06 15:32:22: BoTorchModel, best RESULT: 0.1947368421052632, completed 5 = &sum;5/50, new result: 0.19999999999999996                      
2025-05-06 15:32:41: BoTorchModel, best RESULT: 0.1947368421052632, completed 4 = &sum;4/50, new result: 0.2421052631578947                       
2025-05-06 15:33:04: BoTorchModel, best RESULT: 0.1947368421052632, completed 3 = &sum;3/50, new result: 0.23684210526315785                      
2025-05-06 15:33:24: BoTorchModel, best RESULT: 0.1947368421052632, completed 2 = &sum;2/50, new result: 0.34736842105263155                      
2025-05-06 15:33:40: BoTorchModel, best RESULT: 0.1947368421052632, completed 1 = &sum;1/50, new result: 0.3526315789473684                       
2025-05-06 15:33:55: BoTorchModel, best RESULT: 0.1947368421052632, finishing jobs, finished 50 jobs                                          
2025-05-06 15:34:04: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #1/50                                                  
2025-05-06 15:34:34: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #2/50 | ETA: 17m 48s                                   
2025-05-06 15:34:44: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #3/50 | ETA: 10m 12s                                   
2025-05-06 15:34:55: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #4/50 | ETA: 7m 45s                                    
2025-05-06 15:35:05: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #5/50 | ETA: 6m 18s                                    
2025-05-06 15:35:16: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #6/50 | ETA: 5m 17s                                    
2025-05-06 15:35:27: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #7/50 | ETA: 4m 40s                                    
2025-05-06 15:35:38: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #8/50 | ETA: 4m 17s                                    
2025-05-06 15:35:50: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #9/50 | ETA: 4m 0s                                     
2025-05-06 15:36:00: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #10/50 | ETA: 3m 41s                                   
2025-05-06 15:36:11: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #11/50 | ETA: 3m 26s                                   
2025-05-06 15:36:23: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #12/50 | ETA: 3m 16s                                   
2025-05-06 15:36:33: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #13/50 | ETA: 3m 7s                                    
2025-05-06 15:36:45: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #14/50 | ETA: 2m 58s                                   
2025-05-06 15:37:00: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #15/50 | ETA: 2m 53s                                   
2025-05-06 15:37:13: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #16/50 | ETA: 2m 47s                                   
2025-05-06 15:37:24: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #17/50 | ETA: 2m 38s                                   
2025-05-06 15:37:36: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #18/50 | ETA: 2m 32s                                   
2025-05-06 15:37:49: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #19/50 | ETA: 2m 27s                                   
2025-05-06 15:38:01: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #20/50 | ETA: 2m 21s                                   
2025-05-06 15:38:14: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #21/50 | ETA: 2m 14s                                   
2025-05-06 15:38:26: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #22/50 | ETA: 2m 10s                                   
2025-05-06 15:38:37: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #23/50 | ETA: 2m 4s                                    
2025-05-06 15:38:50: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #24/50 | ETA: 1m 59s                                   
2025-05-06 15:39:02: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #25/50 | ETA: 1m 54s                                   
2025-05-06 15:39:18: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #26/50 | ETA: 1m 50s                                   
2025-05-06 15:39:30: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #27/50 | ETA: 1m 45s                                   
2025-05-06 15:39:44: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #28/50 | ETA: 1m 41s                                   
2025-05-06 15:39:58: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #29/50 | ETA: 1m 36s                                   
2025-05-06 15:40:13: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #30/50 | ETA: 1m 32s                                   
2025-05-06 15:40:25: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #31/50 | ETA: 1m 27s                                   
2025-05-06 15:40:40: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #32/50 | ETA: 1m 23s                                   
2025-05-06 15:40:54: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #33/50 | ETA: 1m 19s                                   
2025-05-06 15:41:14: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #34/50 | ETA: 1m 14s                                   
2025-05-06 15:41:28: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #35/50 | ETA: 1m 11s                                   
2025-05-06 15:41:41: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #36/50 | ETA: 1m 6s                                    
2025-05-06 15:41:55: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #37/50 | ETA: 1m 2s                                    
2025-05-06 15:42:11: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #38/50 | ETA: 58s                                      
2025-05-06 15:42:24: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #39/50 | ETA: 54s                                      
2025-05-06 15:42:42: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #40/50 | ETA: 50s                                      
2025-05-06 15:42:57: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #41/50 | ETA: 45s                                      
2025-05-06 15:43:13: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #42/50 | ETA: 41s                                      
2025-05-06 15:43:36: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #43/50 | ETA: 37s                                      
2025-05-06 15:43:51: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #44/50 | ETA: 32s                                      
2025-05-06 15:44:08: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #45/50 | ETA: 28s                                      
2025-05-06 15:44:29: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #46/50 | ETA: 23s                                      
2025-05-06 15:44:46: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #47/50 | ETA: 19s                                      
2025-05-06 15:45:08: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #48/50 | ETA: 14s                                      
2025-05-06 15:45:32: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #49/50 | ETA: 9s                                       
2025-05-06 15:45:46: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #50/50 | ETA: 4s                                       
2025-05-06 15:46:01: BoTorchModel, best RESULT: 0.1947368421052632, eval start                                                                
2025-05-06 15:46:10: BoTorchModel, best RESULT: 0.1947368421052632, starting new job                                                          
2025-05-06 15:46:22: BoTorchModel, best RESULT: 0.1947368421052632, unknown 1 = &sum;1/50, started new job                                        
2025-05-06 15:46:35: BoTorchModel, best RESULT: 0.1947368421052632, pending 1 = &sum;1/50, eval start                                             
2025-05-06 15:46:47: BoTorchModel, best RESULT: 0.1947368421052632, pending 1 = &sum;1/50, starting new job                                       
2025-05-06 15:47:00: BoTorchModel, best RESULT: 0.1947368421052632, running/unknown 1/1 = &sum;2/50, started new job                              
2025-05-06 15:47:13: BoTorchModel, best RESULT: 0.1947368421052632, running/pending 1/1 = &sum;2/50, eval start                                   
2025-05-06 15:47:25: BoTorchModel, best RESULT: 0.1947368421052632, running/pending 1/1 = &sum;2/50, starting new job                             
2025-05-06 15:47:39: BoTorchModel, best RESULT: 0.1947368421052632, running/unknown 2/1 = &sum;3/50, started new job                              
2025-05-06 15:47:48: BoTorchModel, best RESULT: 0.1947368421052632, running/pending 2/1 = &sum;3/50, eval start                                   
2025-05-06 15:47:57: BoTorchModel, best RESULT: 0.1947368421052632, running/pending 2/1 = &sum;3/50, starting new job                             
2025-05-06 15:48:16: BoTorchModel, best RESULT: 0.1947368421052632, running/unknown 3/1 = &sum;4/50, started new job                              
2025-05-06 15:48:34: BoTorchModel, best RESULT: 0.1947368421052632, running 4 = &sum;4/50, eval start                                             
2025-05-06 15:48:49: BoTorchModel, best RESULT: 0.1947368421052632, running 4 = &sum;4/50, starting new job                                       
2025-05-06 15:49:08: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 1/3/1 = &sum;5/50, started new job                  
2025-05-06 15:49:20: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 3/1/1 = &sum;5/50, eval start                       
2025-05-06 15:49:35: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 4/1 = &sum;5/50, starting new job                           
2025-05-06 15:49:52: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 4/1/1 = &sum;6/50, started new job                  
2025-05-06 15:50:02: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 4/2 = &sum;6/50, eval start                                 
2025-05-06 15:50:19: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 4/2 = &sum;6/50, starting new job                           
2025-05-06 15:50:37: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 4/2/1 = &sum;7/50, started new job                  
2025-05-06 15:50:53: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 5/1/1 = &sum;7/50, eval start                       
2025-05-06 15:51:09: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 5/1/1 = &sum;7/50, starting new job                 
2025-05-06 15:51:23: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 5/2/1 = &sum;8/50, started new job                  
2025-05-06 15:51:36: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 5/3 = &sum;8/50, eval start                                 
2025-05-06 15:51:51: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 5/3 = &sum;8/50, starting new job                           
2025-05-06 15:52:06: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 5/3/1 = &sum;9/50, started new job                  
2025-05-06 15:52:23: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 7/1/1 = &sum;9/50, eval start                       
2025-05-06 15:52:46: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 7/2 = &sum;9/50, starting new job                           
2025-05-06 15:53:03: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 7/2/1 = &sum;10/50, started new job                 
2025-05-06 15:53:20: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 7/2/1 = &sum;10/50, eval start                      
2025-05-06 15:53:36: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 7/2/1 = &sum;10/50, starting new job                
2025-05-06 15:53:54: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 7/3/1 = &sum;11/50, started new job                 
2025-05-06 15:54:11: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 8/3 = &sum;11/50, eval start                                
2025-05-06 15:54:27: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 8/3 = &sum;11/50, starting new job                          
2025-05-06 15:54:50: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 10/1/1 = &sum;12/50, started new job                
2025-05-06 15:55:10: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 10/2 = &sum;12/50, eval start                               
2025-05-06 15:55:31: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 10/2 = &sum;12/50, starting new job                         
2025-05-06 15:55:50: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 10/2/1 = &sum;13/50, started new job                
2025-05-06 15:56:07: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 10/3 = &sum;13/50, eval start                               
2025-05-06 15:56:29: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 10/3 = &sum;13/50, starting new job                         
2025-05-06 15:56:55: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 11/2/1 = &sum;14/50, started new job                
2025-05-06 15:57:11: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 11/3 = &sum;14/50, eval start                               
2025-05-06 15:57:24: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 11/3 = &sum;14/50, starting new job                         
2025-05-06 15:57:44: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 13/1/1 = &sum;15/50, started new job                
2025-05-06 15:58:07: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 13/2 = &sum;15/50, eval start                               
2025-05-06 15:58:21: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 13/2 = &sum;15/50, starting new job                         
2025-05-06 15:58:34: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 14/1/1 = &sum;16/50, started new job                
2025-05-06 15:58:50: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 14/1/1 = &sum;16/50, eval start                     
2025-05-06 15:59:10: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 15/1 = &sum;16/50, starting new job                         
2025-05-06 15:59:30: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 15/1/1 = &sum;17/50, started new job                
2025-05-06 15:59:48: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 15/1/1 = &sum;17/50, eval start                     
2025-05-06 16:00:06: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 15/1/1 = &sum;17/50, starting new job               
2025-05-06 16:00:23: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 15/2/1 = &sum;18/50, started new job                
2025-05-06 16:00:39: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 16/2 = &sum;18/50, eval start                               
2025-05-06 16:01:02: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 16/2 = &sum;18/50, starting new job                         
2025-05-06 16:01:18: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 17/1/1 = &sum;19/50, started new job                
2025-05-06 16:01:34: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 18/1 = &sum;19/50, eval start                               
2025-05-06 16:01:50: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 18/1 = &sum;19/50, starting new job                         
2025-05-06 16:02:13: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 18/1/1 = &sum;20/50, started new job                
2025-05-06 16:02:27: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 18/1/1 = &sum;20/50, eval start                     
2025-05-06 16:02:40: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 18/1/1 = &sum;20/50, starting new job               
2025-05-06 16:02:57: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 18/2/1 = &sum;21/50, started new job                
2025-05-06 16:03:19: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 18/3 = &sum;21/50, eval start                               
2025-05-06 16:03:37: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 18/3 = &sum;21/50, starting new job                         
2025-05-06 16:03:57: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 20/1/1 = &sum;22/50, started new job                
2025-05-06 16:04:24: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 21/1 = &sum;22/50, eval start                               
2025-05-06 16:04:43: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 21/1 = &sum;22/50, starting new job                         
2025-05-06 16:05:06: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 21/1/1 = &sum;23/50, started new job                
2025-05-06 16:05:31: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 21/2 = &sum;23/50, eval start                               
2025-05-06 16:05:54: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 21/2 = &sum;23/50, starting new job                         
2025-05-06 16:06:16: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 22/1/1 = &sum;24/50, started new job                
2025-05-06 16:06:37: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 22/1/1 = &sum;24/50, eval start                     
2025-05-06 16:06:54: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 22/1/1 = &sum;24/50, starting new job               
2025-05-06 16:07:17: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 23/1/1 = &sum;25/50, started new job                
2025-05-06 16:07:37: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 23/1/1 = &sum;25/50, eval start                     
2025-05-06 16:08:05: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 23/2 = &sum;25/50, starting new job                         
2025-05-06 16:08:40: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 24/1/1 = &sum;26/50, started new job                
2025-05-06 16:09:09: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 25/1 = &sum;26/50, eval start                               
2025-05-06 16:09:45: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 25/1 = &sum;26/50, starting new job                         
2025-05-06 16:10:13: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 25/1/1 = &sum;27/50, started new job                
2025-05-06 16:10:43: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 25/1/1 = &sum;27/50, eval start                     
2025-05-06 16:11:25: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 25/2 = &sum;27/50, starting new job                         
2025-05-06 16:11:56: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 25/2/1 = &sum;28/50, started new job                
2025-05-06 16:12:27: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 25/3 = &sum;28/50, eval start                               
2025-05-06 16:12:52: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 25/3 = &sum;28/50, starting new job                         
2025-05-06 16:13:23: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 25/3/1 = &sum;29/50, started new job                
2025-05-06 16:13:49: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 25/4 = &sum;29/50, eval start                               
2025-05-06 16:14:25: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 26/3 = &sum;29/50, starting new job                         
2025-05-06 16:14:59: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 26/3/1 = &sum;30/50, started new job                
2025-05-06 16:15:28: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 27/3 = &sum;30/50, eval start                               
2025-05-06 16:15:48: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 27/3 = &sum;30/50, starting new job                         
2025-05-06 16:16:09: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 27/3/1 = &sum;31/50, started new job                
2025-05-06 16:16:52: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 27/4 = &sum;31/50, eval start                               
2025-05-06 16:17:18: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 27/4 = &sum;31/50, starting new job                         
2025-05-06 16:17:46: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 27/4/1 = &sum;32/50, started new job                
2025-05-06 16:18:15: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 28/4 = &sum;32/50, eval start                               
2025-05-06 16:18:38: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 28/4 = &sum;32/50, starting new job                         
2025-05-06 16:19:08: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 29/3/1 = &sum;33/50, started new job                
2025-05-06 16:19:37: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 30/3 = &sum;33/50, eval start                               
2025-05-06 16:20:14: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 30/3 = &sum;33/50, starting new job                         
2025-05-06 16:20:44: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 31/2/1 = &sum;34/50, started new job                
2025-05-06 16:21:25: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 31/3 = &sum;34/50, eval start                               
2025-05-06 16:22:00: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 31/3 = &sum;34/50, starting new job                         
2025-05-06 16:22:42: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 31/3/1 = &sum;35/50, started new job                
2025-05-06 16:23:27: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 31/4 = &sum;35/50, eval start                               
2025-05-06 16:24:02: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 31/4 = &sum;35/50, starting new job                         
2025-05-06 16:25:01: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 32/3/1 = &sum;36/50, started new job                
2025-05-06 16:25:52: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 32/4 = &sum;36/50, eval start                               
2025-05-06 16:26:28: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 32/4 = &sum;36/50, starting new job                         
2025-05-06 16:27:15: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 34/2/1 = &sum;37/50, started new job                
2025-05-06 16:27:56: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 34/3 = &sum;37/50, eval start                               
2025-05-06 16:28:34: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 34/3 = &sum;37/50, starting new job                         
2025-05-06 16:29:06: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 34/3/1 = &sum;38/50, started new job                
2025-05-06 16:29:38: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 34/4 = &sum;38/50, eval start                               
2025-05-06 16:30:37: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 34/4 = &sum;38/50, starting new job                         
2025-05-06 16:32:02: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 34/4/1 = &sum;39/50, started new job                
2025-05-06 16:32:37: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 34/5 = &sum;39/50, eval start                               
2025-05-06 16:33:12: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 34/5 = &sum;39/50, starting new job                         
2025-05-06 16:33:48: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 34/5/1 = &sum;40/50, started new job                
2025-05-06 16:34:14: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 34/6 = &sum;40/50, eval start                               
2025-05-06 16:34:53: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 34/6 = &sum;40/50, starting new job                         
2025-05-06 16:35:26: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 34/6/1 = &sum;41/50, started new job                
2025-05-06 16:35:52: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 34/7 = &sum;41/50, eval start                               
2025-05-06 16:36:10: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 34/7 = &sum;41/50, starting new job                         
2025-05-06 16:36:36: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 34/7/1 = &sum;42/50, started new job                
2025-05-06 16:37:08: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 34/8 = &sum;42/50, eval start                               
2025-05-06 16:37:36: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 34/8 = &sum;42/50, starting new job                         
2025-05-06 16:38:02: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 35/7/1 = &sum;43/50, started new job                
2025-05-06 16:38:24: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 35/8 = &sum;43/50, eval start                               
2025-05-06 16:38:49: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 35/8 = &sum;43/50, starting new job                         
2025-05-06 16:39:15: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 35/8/1 = &sum;44/50, started new job                
2025-05-06 16:39:41: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 35/9 = &sum;44/50, eval start                               
2025-05-06 16:40:07: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 35/9 = &sum;44/50, starting new job                         
2025-05-06 16:40:35: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 36/8/1 = &sum;45/50, started new job                
2025-05-06 16:40:56: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 36/9 = &sum;45/50, eval start                               
2025-05-06 16:41:28: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 36/9 = &sum;45/50, starting new job                         
2025-05-06 16:41:48: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 36/9/1 = &sum;46/50, started new job                
2025-05-06 16:42:22: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 41/5 = &sum;46/50, eval start                               
2025-05-06 16:43:03: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 41/5 = &sum;46/50, starting new job                         
2025-05-06 16:43:37: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 43/3/1 = &sum;47/50, started new job                
2025-05-06 16:44:05: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 44/3 = &sum;47/50, eval start                               
2025-05-06 16:44:29: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 44/3 = &sum;47/50, starting new job                         
2025-05-06 16:45:09: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 44/3/1 = &sum;48/50, started new job                
2025-05-06 16:45:52: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 44/4 = &sum;48/50, eval start                               
2025-05-06 16:46:29: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 44/4 = &sum;48/50, starting new job                         
2025-05-06 16:47:05: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 44/4/1 = &sum;49/50, started new job                
2025-05-06 16:47:35: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 45/4 = &sum;49/50, eval start                               
2025-05-06 16:48:10: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 45/4 = &sum;49/50, starting new job                         
2025-05-06 16:48:41: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 45/4/1 = &sum;50/50, started new job                
2025-05-06 16:49:20: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 45/5 = &sum;50/50, new result: 0.35789473684210527          
2025-05-06 16:50:56: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 44/5 = &sum;49/50, new result: 0.3052631578947368           
2025-05-06 16:52:55: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 45/3 = &sum;48/50, new result: 0.2894736842105263           
2025-05-06 16:54:16: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 44/3 = &sum;47/50, new result: 0.2894736842105263           
2025-05-06 16:55:38: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 45/1 = &sum;46/50, new result: 0.26315789473684215          
2025-05-06 16:57:20: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 44/1 = &sum;45/50, new result: 0.3052631578947368           
2025-05-06 16:58:54: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 43/1 = &sum;44/50, new result: 0.2315789473684211           
2025-05-06 17:00:32: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 42/1 = &sum;43/50, new result: 0.2210526315789474           
2025-05-06 17:02:17: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 41/1 = &sum;42/50, new result: 0.23684210526315785          
2025-05-06 17:04:10: BoTorchModel, best RESULT: 0.1947368421052632, completed 41 = &sum;41/50, new result: 0.32105263157894737                    
2025-05-06 17:06:00: BoTorchModel, best RESULT: 0.1947368421052632, completed 40 = &sum;40/50, new result: 0.30000000000000004                    
2025-05-06 17:07:06: BoTorchModel, best RESULT: 0.1947368421052632, completed 39 = &sum;39/50, new result: 0.33684210526315794                    
2025-05-06 17:08:07: BoTorchModel, best RESULT: 0.1947368421052632, completed 38 = &sum;38/50, new result: 0.2421052631578947                     
2025-05-06 17:09:07: BoTorchModel, best RESULT: 0.1947368421052632, completed 37 = &sum;37/50, new result: 0.3052631578947368                     
2025-05-06 17:09:57: BoTorchModel, best RESULT: 0.1947368421052632, completed 36 = &sum;36/50, new result: 0.37368421052631584                    
2025-05-06 17:10:44: BoTorchModel, best RESULT: 0.1947368421052632, completed 35 = &sum;35/50, new result: 0.2789473684210526                     
2025-05-06 17:11:39: BoTorchModel, best RESULT: 0.1947368421052632, completed 34 = &sum;34/50, new result: 0.2947368421052632                     
2025-05-06 17:12:39: BoTorchModel, best RESULT: 0.1947368421052632, completed 33 = &sum;33/50, new result: 0.3526315789473684                     
2025-05-06 17:13:38: BoTorchModel, best RESULT: 0.1947368421052632, completed 32 = &sum;32/50, new result: 0.27368421052631575                    
2025-05-06 17:14:31: BoTorchModel, best RESULT: 0.1947368421052632, completed 31 = &sum;31/50, new result: 0.3631578947368421                     
2025-05-06 17:15:20: BoTorchModel, best RESULT: 0.1947368421052632, completed 30 = &sum;30/50, new result: 0.33684210526315794                    
2025-05-06 17:16:26: BoTorchModel, best RESULT: 0.1947368421052632, completed 29 = &sum;29/50, new result: 0.24736842105263157                    
2025-05-06 17:17:18: BoTorchModel, best RESULT: 0.1947368421052632, completed 28 = &sum;28/50, new result: 0.2947368421052632                     
2025-05-06 17:18:08: BoTorchModel, best RESULT: 0.1947368421052632, completed 27 = &sum;27/50, new result: 0.31052631578947365                    
2025-05-06 17:18:48: BoTorchModel, best RESULT: 0.1947368421052632, completed 26 = &sum;26/50, new result: 0.2315789473684211                     
2025-05-06 17:19:32: BoTorchModel, best RESULT: 0.1947368421052632, completed 25 = &sum;25/50, new result: 0.31052631578947365                    
2025-05-06 17:20:24: BoTorchModel, best RESULT: 0.1947368421052632, completed 24 = &sum;24/50, new result: 0.3263157894736842                     
2025-05-06 17:21:34: BoTorchModel, best RESULT: 0.1947368421052632, completed 23 = &sum;23/50, new result: 0.27368421052631575                    
2025-05-06 17:22:37: BoTorchModel, best RESULT: 0.1947368421052632, completed 22 = &sum;22/50, new result: 0.3157894736842105                     
2025-05-06 17:23:25: BoTorchModel, best RESULT: 0.1947368421052632, completed 21 = &sum;21/50, new result: 0.3421052631578947                     
2025-05-06 17:24:10: BoTorchModel, best RESULT: 0.1947368421052632, completed 20 = &sum;20/50, new result: 0.23684210526315785                    
2025-05-06 17:24:56: BoTorchModel, best RESULT: 0.1947368421052632, completed 19 = &sum;19/50, new result: 0.32105263157894737                    
2025-05-06 17:25:33: BoTorchModel, best RESULT: 0.1947368421052632, completed 18 = &sum;18/50, new result: 0.22631578947368425                    
2025-05-06 17:26:17: BoTorchModel, best RESULT: 0.1947368421052632, completed 17 = &sum;17/50, new result: 0.2315789473684211                     
2025-05-06 17:27:11: BoTorchModel, best RESULT: 0.1947368421052632, completed 16 = &sum;16/50, new result: 0.3263157894736842                     
2025-05-06 17:28:04: BoTorchModel, best RESULT: 0.1947368421052632, completed 15 = &sum;15/50, new result: 0.2578947368421053                     
2025-05-06 17:29:05: BoTorchModel, best RESULT: 0.1947368421052632, completed 14 = &sum;14/50, new result: 0.2421052631578947                     
2025-05-06 17:30:14: BoTorchModel, best RESULT: 0.1947368421052632, completed 13 = &sum;13/50, new result: 0.2421052631578947                     
2025-05-06 17:31:07: BoTorchModel, best RESULT: 0.1947368421052632, completed 12 = &sum;12/50, new result: 0.3052631578947368                     
2025-05-06 17:32:08: BoTorchModel, best RESULT: 0.1947368421052632, completed 11 = &sum;11/50, new result: 0.2578947368421053                     
2025-05-06 17:32:59: BoTorchModel, best RESULT: 0.1947368421052632, completed 10 = &sum;10/50, new result: 0.27368421052631575                    
2025-05-06 17:33:43: BoTorchModel, best RESULT: 0.1947368421052632, completed 9 = &sum;9/50, new result: 0.27368421052631575                      
2025-05-06 17:34:25: BoTorchModel, best RESULT: 0.1947368421052632, completed 8 = &sum;8/50, new result: 0.3631578947368421                       
2025-05-06 17:35:06: BoTorchModel, best RESULT: 0.1947368421052632, completed 7 = &sum;7/50, new result: 0.3421052631578947                       
2025-05-06 17:35:45: BoTorchModel, best RESULT: 0.1947368421052632, completed 6 = &sum;6/50, new result: 0.30000000000000004                      
2025-05-06 17:36:22: BoTorchModel, best RESULT: 0.1947368421052632, completed 5 = &sum;5/50, new result: 0.2894736842105263                       
2025-05-06 17:36:59: BoTorchModel, best RESULT: 0.1947368421052632, completed 4 = &sum;4/50, new result: 0.25263157894736843                      
2025-05-06 17:37:39: BoTorchModel, best RESULT: 0.1947368421052632, completed 3 = &sum;3/50, new result: 0.2789473684210526                       
2025-05-06 17:38:09: BoTorchModel, best RESULT: 0.1947368421052632, completed 2 = &sum;2/50, new result: 0.27368421052631575                      
2025-05-06 17:38:44: BoTorchModel, best RESULT: 0.1947368421052632, completed 1 = &sum;1/50, new result: 0.3631578947368421                       
2025-05-06 17:39:20: BoTorchModel, best RESULT: 0.1947368421052632, finishing jobs, finished 50 jobs                                          
2025-05-06 17:39:38: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #1/50                                                  
2025-05-06 17:40:08: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #2/50 | ETA: 9m 37s                                    
2025-05-06 17:40:31: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #3/50 | ETA: 6m 36s                                    
2025-05-06 17:40:52: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #4/50 | ETA: 5m 27s                                    
2025-05-06 17:41:16: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #5/50 | ETA: 4m 57s                                    
2025-05-06 17:41:37: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #6/50 | ETA: 4m 30s                                    
2025-05-06 17:42:04: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #7/50 | ETA: 4m 24s                                    
2025-05-06 17:42:25: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #8/50 | ETA: 4m 13s                                    
2025-05-06 17:42:53: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #9/50 | ETA: 4m 2s                                     
2025-05-06 17:43:17: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #10/50 | ETA: 3m 52s                                   
2025-05-06 17:43:39: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #11/50 | ETA: 3m 45s                                   
2025-05-06 17:44:02: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #12/50 | ETA: 3m 35s                                   
2025-05-06 17:44:23: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #13/50 | ETA: 3m 24s                                   
2025-05-06 17:44:53: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #14/50 | ETA: 3m 17s                                   
2025-05-06 17:45:17: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #15/50 | ETA: 3m 10s                                   
2025-05-06 17:45:42: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #16/50 | ETA: 3m 2s                                    
2025-05-06 17:46:10: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #17/50 | ETA: 2m 55s                                   
2025-05-06 17:46:42: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #18/50 | ETA: 2m 51s                                   
2025-05-06 17:47:05: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #19/50 | ETA: 2m 45s                                   
2025-05-06 17:47:25: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #20/50 | ETA: 2m 38s                                   
2025-05-06 17:47:47: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #21/50 | ETA: 2m 35s                                   
2025-05-06 17:48:06: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #22/50 | ETA: 2m 30s                                   
2025-05-06 17:48:23: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #23/50 | ETA: 2m 24s                                   
2025-05-06 17:48:42: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #24/50 | ETA: 2m 18s                                   
2025-05-06 17:49:03: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #25/50 | ETA: 2m 14s                                   
2025-05-06 17:49:28: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #26/50 | ETA: 2m 8s                                    
2025-05-06 17:49:50: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #27/50 | ETA: 2m 3s                                    
2025-05-06 17:50:07: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #28/50 | ETA: 1m 58s                                   
2025-05-06 17:50:24: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #29/50 | ETA: 1m 52s                                   
2025-05-06 17:50:43: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #30/50 | ETA: 1m 47s                                   
2025-05-06 17:51:01: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #31/50 | ETA: 1m 42s                                   
2025-05-06 17:51:20: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #32/50 | ETA: 1m 37s                                   
2025-05-06 17:51:49: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #33/50 | ETA: 1m 32s                                   
2025-05-06 17:52:05: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #34/50 | ETA: 1m 27s                                   
2025-05-06 17:52:26: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #35/50 | ETA: 1m 22s                                   
2025-05-06 17:52:44: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #36/50 | ETA: 1m 17s                                   
2025-05-06 17:53:03: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #37/50 | ETA: 1m 12s                                   
2025-05-06 17:53:29: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #38/50 | ETA: 1m 8s                                    
2025-05-06 17:53:47: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #39/50 | ETA: 1m 3s                                    
2025-05-06 17:54:07: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #40/50 | ETA: 58s                                      
2025-05-06 17:54:31: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #41/50 | ETA: 53s                                      
2025-05-06 17:54:54: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #42/50 | ETA: 47s                                      
2025-05-06 17:55:16: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #43/50 | ETA: 42s                                      
2025-05-06 17:55:46: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #44/50 | ETA: 37s                                      
2025-05-06 17:56:12: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #45/50 | ETA: 32s                                      
2025-05-06 17:56:36: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #46/50 | ETA: 27s                                      
2025-05-06 17:56:55: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #47/50 | ETA: 21s                                      
2025-05-06 17:57:15: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #48/50 | ETA: 16s                                      
2025-05-06 17:57:37: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #49/50 | ETA: 11s                                      
2025-05-06 17:58:01: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #50/50 | ETA: 5s                                       
2025-05-06 17:58:23: BoTorchModel, best RESULT: 0.1947368421052632, eval start                                                                
2025-05-06 17:58:40: BoTorchModel, best RESULT: 0.1947368421052632, starting new job                                                          
2025-05-06 17:59:00: BoTorchModel, best RESULT: 0.1947368421052632, unknown 1 = &sum;1/50, started new job                                        
2025-05-06 17:59:23: BoTorchModel, best RESULT: 0.1947368421052632, running 1 = &sum;1/50, eval start                                             
2025-05-06 17:59:42: BoTorchModel, best RESULT: 0.1947368421052632, running 1 = &sum;1/50, starting new job                                       
2025-05-06 18:00:01: BoTorchModel, best RESULT: 0.1947368421052632, running/unknown 1/1 = &sum;2/50, started new job                              
2025-05-06 18:00:21: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 1/1 = &sum;2/50, eval start                                 
2025-05-06 18:00:37: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 1/1 = &sum;2/50, starting new job                           
2025-05-06 18:00:52: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 1/1/1 = &sum;3/50, started new job                  
2025-05-06 18:01:16: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 1/2 = &sum;3/50, eval start                                 
2025-05-06 18:01:31: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 1/2 = &sum;3/50, starting new job                           
2025-05-06 18:01:49: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 3/1 = &sum;4/50, started new job                            
2025-05-06 18:02:09: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 3/1 = &sum;4/50, eval start                                 
2025-05-06 18:02:27: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 3/1 = &sum;4/50, starting new job                           
2025-05-06 18:02:52: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 3/1/1 = &sum;5/50, started new job                  
2025-05-06 18:03:16: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 4/1 = &sum;5/50, eval start                                 
2025-05-06 18:03:30: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 4/1 = &sum;5/50, starting new job                           
2025-05-06 18:03:47: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 4/1/1 = &sum;6/50, started new job                  
2025-05-06 18:04:02: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 5/1 = &sum;6/50, eval start                                 
2025-05-06 18:04:16: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 5/1 = &sum;6/50, starting new job                           
2025-05-06 18:04:32: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 5/1/1 = &sum;7/50, started new job                  
2025-05-06 18:04:50: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 5/2 = &sum;7/50, eval start                                 
2025-05-06 18:05:09: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 6/1 = &sum;7/50, starting new job                           
2025-05-06 18:05:27: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 7/1 = &sum;8/50, started new job                            
2025-05-06 18:05:40: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 7/1 = &sum;8/50, eval start                                 
2025-05-06 18:05:58: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 7/1 = &sum;8/50, starting new job                           
2025-05-06 18:06:13: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 7/1/1 = &sum;9/50, started new job                  
2025-05-06 18:06:24: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 8/1 = &sum;9/50, eval start                                 
2025-05-06 18:06:35: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 8/1 = &sum;9/50, starting new job                           
2025-05-06 18:06:55: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 8/1/1 = &sum;10/50, started new job                 
2025-05-06 18:07:08: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 8/1/1 = &sum;10/50, eval start                      
2025-05-06 18:07:21: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 8/1/1 = &sum;10/50, starting new job                
2025-05-06 18:07:35: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 8/2/1 = &sum;11/50, started new job                 
2025-05-06 18:07:54: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 10/1 = &sum;11/50, eval start                               
2025-05-06 18:08:10: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 10/1 = &sum;11/50, starting new job                         
2025-05-06 18:08:24: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 10/1/1 = &sum;12/50, started new job                
2025-05-06 18:08:35: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 11/1 = &sum;12/50, eval start                               
2025-05-06 18:08:55: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 11/1 = &sum;12/50, starting new job                         
2025-05-06 18:09:12: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 11/1/1 = &sum;13/50, started new job                
2025-05-06 18:09:26: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 11/2 = &sum;13/50, eval start                               
2025-05-06 18:09:44: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 11/2 = &sum;13/50, starting new job                         
2025-05-06 18:10:06: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 12/1/1 = &sum;14/50, started new job                
2025-05-06 18:10:27: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 13/1 = &sum;14/50, eval start                               
2025-05-06 18:10:49: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 13/1 = &sum;14/50, starting new job                         
2025-05-06 18:11:13: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 13/1/1 = &sum;15/50, started new job                
2025-05-06 18:11:36: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 13/2 = &sum;15/50, eval start                               
2025-05-06 18:12:03: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 14/1 = &sum;15/50, starting new job                         
2025-05-06 18:12:29: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 14/1/1 = &sum;16/50, started new job                
2025-05-06 18:12:55: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 15/1 = &sum;16/50, eval start                               
2025-05-06 18:13:18: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 15/1 = &sum;16/50, starting new job                         
2025-05-06 18:13:45: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 15/1/1 = &sum;17/50, started new job                
2025-05-06 18:14:13: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 16/1 = &sum;17/50, eval start                               
2025-05-06 18:14:44: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 16/1 = &sum;17/50, starting new job                         
2025-05-06 18:15:14: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 16/1/1 = &sum;18/50, started new job                
2025-05-06 18:15:44: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 17/1 = &sum;18/50, eval start                               
2025-05-06 18:16:07: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 17/1 = &sum;18/50, starting new job                         
2025-05-06 18:16:38: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 17/1/1 = &sum;19/50, started new job                
2025-05-06 18:17:08: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 18/1 = &sum;19/50, eval start                               
2025-05-06 18:17:36: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 18/1 = &sum;19/50, starting new job                         
2025-05-06 18:18:06: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 19/1 = &sum;20/50, started new job                          
2025-05-06 18:18:34: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 19/1 = &sum;20/50, eval start                               
2025-05-06 18:19:04: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 19/1 = &sum;20/50, starting new job                         
2025-05-06 18:19:41: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 20/1 = &sum;21/50, started new job                          
2025-05-06 18:20:13: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 20/1 = &sum;21/50, eval start                               
2025-05-06 18:20:35: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 20/1 = &sum;21/50, starting new job                         
2025-05-06 18:21:02: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 21/1 = &sum;22/50, started new job                          
2025-05-06 18:21:25: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 21/1 = &sum;22/50, eval start                               
2025-05-06 18:21:54: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 21/1 = &sum;22/50, starting new job                         
2025-05-06 18:22:41: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 21/1/1 = &sum;23/50, started new job                
2025-05-06 18:23:19: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 21/2 = &sum;23/50, eval start                               
2025-05-06 18:24:06: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 21/2 = &sum;23/50, starting new job                         
2025-05-06 18:24:50: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 21/2/1 = &sum;24/50, started new job                
2025-05-06 18:25:25: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 21/3 = &sum;24/50, eval start                               
2025-05-06 18:26:07: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 21/3 = &sum;24/50, starting new job                         
2025-05-06 18:26:41: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 21/3/1 = &sum;25/50, started new job                
2025-05-06 18:27:19: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 21/4 = &sum;25/50, eval start                               
2025-05-06 18:28:05: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 22/3 = &sum;25/50, starting new job                         
2025-05-06 18:28:54: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 22/3/1 = &sum;26/50, started new job                
2025-05-06 18:29:37: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 22/4 = &sum;26/50, eval start                               
2025-05-06 18:30:14: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 22/4 = &sum;26/50, starting new job                         
2025-05-06 18:30:58: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 22/4/1 = &sum;27/50, started new job                
2025-05-06 18:31:42: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 22/5 = &sum;27/50, eval start                               
2025-05-06 18:32:26: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 22/5 = &sum;27/50, starting new job                         
2025-05-06 18:33:20: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 22/5/1 = &sum;28/50, started new job                
2025-05-06 18:34:25: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 22/6 = &sum;28/50, eval start                               
2025-05-06 18:35:11: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 22/6 = &sum;28/50, starting new job                         
2025-05-06 18:35:52: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 22/6/1 = &sum;29/50, started new job                
2025-05-06 18:36:44: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 22/7 = &sum;29/50, eval start                               
2025-05-06 18:37:38: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 22/7 = &sum;29/50, starting new job                         
2025-05-06 18:38:24: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 22/7/1 = &sum;30/50, started new job                
2025-05-06 18:38:53: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 22/7/1 = &sum;30/50, eval start                     
2025-05-06 18:39:21: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 22/7/1 = &sum;30/50, starting new job               
2025-05-06 18:39:52: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 22/8/1 = &sum;31/50, started new job                
2025-05-06 18:40:13: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 23/7/1 = &sum;31/50, eval start                     
2025-05-06 18:40:50: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 23/8 = &sum;31/50, starting new job                         
2025-05-06 18:41:27: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 23/8/1 = &sum;32/50, started new job                
2025-05-06 18:41:52: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 23/9 = &sum;32/50, eval start                               
2025-05-06 18:42:25: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 23/9 = &sum;32/50, starting new job                         
2025-05-06 18:43:46: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 23/9/1 = &sum;33/50, started new job                
2025-05-06 18:44:14: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 24/9 = &sum;33/50, eval start                               
2025-05-06 18:44:46: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 24/9 = &sum;33/50, starting new job                         
2025-05-06 18:45:08: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 24/9/1 = &sum;34/50, started new job                
2025-05-06 18:45:39: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 24/10 = &sum;34/50, eval start                              
2025-05-06 18:46:12: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 25/9 = &sum;34/50, starting new job                         
2025-05-06 18:47:02: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 25/9/1 = &sum;35/50, started new job                
2025-05-06 18:47:29: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 25/10 = &sum;35/50, eval start                              
2025-05-06 18:47:53: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 25/10 = &sum;35/50, starting new job                        
2025-05-06 18:48:22: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 32/3/1 = &sum;36/50, started new job                
2025-05-06 18:48:46: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 34/2 = &sum;36/50, eval start                               
2025-05-06 18:49:12: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 34/2 = &sum;36/50, starting new job                         
2025-05-06 18:49:35: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 34/2/1 = &sum;37/50, started new job                
2025-05-06 18:50:00: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 35/2 = &sum;37/50, eval start                               
2025-05-06 18:50:26: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 35/2 = &sum;37/50, starting new job                         
2025-05-06 18:50:55: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 35/2/1 = &sum;38/50, started new job                
2025-05-06 18:51:28: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 36/2 = &sum;38/50, eval start                               
2025-05-06 18:51:52: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 36/2 = &sum;38/50, starting new job                         
2025-05-06 18:52:17: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 37/1/1 = &sum;39/50, started new job                
2025-05-06 18:52:42: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 38/1 = &sum;39/50, eval start                               
2025-05-06 18:53:11: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 38/1 = &sum;39/50, starting new job                         
2025-05-06 18:53:44: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 39/1 = &sum;40/50, started new job                          
2025-05-06 18:54:16: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 39/1 = &sum;40/50, eval start                               
2025-05-06 18:54:37: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 39/1 = &sum;40/50, starting new job                         
2025-05-06 18:55:01: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 39/1/1 = &sum;41/50, started new job                
2025-05-06 18:55:28: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 40/1 = &sum;41/50, eval start                               
2025-05-06 18:55:52: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 40/1 = &sum;41/50, starting new job                         
2025-05-06 18:56:17: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 40/1/1 = &sum;42/50, started new job                
2025-05-06 18:56:39: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 41/1 = &sum;42/50, eval start                               
2025-05-06 18:57:01: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 41/1 = &sum;42/50, starting new job                         
2025-05-06 18:57:31: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 42/1 = &sum;43/50, started new job                          
2025-05-06 18:57:57: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 42/1 = &sum;43/50, eval start                               
2025-05-06 18:58:25: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 42/1 = &sum;43/50, starting new job                         
2025-05-06 18:58:49: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 42/1/1 = &sum;44/50, started new job                
2025-05-06 18:59:20: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 43/1 = &sum;44/50, eval start                               
2025-05-06 18:59:53: BoTorchModel, best RESULT: 0.1947368421052632, completed 44 = &sum;44/50, starting new job                                   
2025-05-06 19:00:26: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 44/1 = &sum;45/50, started new job                          
2025-05-06 19:00:47: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 44/1 = &sum;45/50, eval start                               
2025-05-06 19:01:08: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 44/1 = &sum;45/50, starting new job                         
2025-05-06 19:01:43: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 45/1 = &sum;46/50, started new job                          
2025-05-06 19:02:12: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 45/1 = &sum;46/50, eval start                               
2025-05-06 19:02:40: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 45/1 = &sum;46/50, starting new job                         
2025-05-06 19:02:59: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 45/1/1 = &sum;47/50, started new job                
2025-05-06 19:03:20: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 46/1 = &sum;47/50, eval start                               
2025-05-06 19:03:45: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 46/1 = &sum;47/50, starting new job                         
2025-05-06 19:04:06: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 47/1 = &sum;48/50, started new job                          
2025-05-06 19:04:25: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 47/1 = &sum;48/50, eval start                               
2025-05-06 19:04:53: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 47/1 = &sum;48/50, starting new job                         
2025-05-06 19:05:09: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 48/1 = &sum;49/50, started new job                          
2025-05-06 19:05:29: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 48/1 = &sum;49/50, eval start                               
2025-05-06 19:05:56: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 48/1 = &sum;49/50, starting new job                         
2025-05-06 19:06:15: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 49/1 = &sum;50/50, started new job                          
2025-05-06 19:06:50: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 49/1 = &sum;50/50, new result: 0.1947368421052632           
2025-05-06 19:07:42: BoTorchModel, best RESULT: 0.1947368421052632, completed 49 = &sum;49/50, new result: 0.21052631578947367                    
2025-05-06 19:08:22: BoTorchModel, best RESULT: 0.1947368421052632, completed 48 = &sum;48/50, new result: 0.3052631578947368                     
2025-05-06 19:09:05: BoTorchModel, best RESULT: 0.1947368421052632, completed 47 = &sum;47/50, new result: 0.2315789473684211                     
2025-05-06 19:09:49: BoTorchModel, best RESULT: 0.1947368421052632, completed 46 = &sum;46/50, new result: 0.30000000000000004                    
2025-05-06 19:10:31: BoTorchModel, best RESULT: 0.1947368421052632, completed 45 = &sum;45/50, new result: 0.4631578947368421                     
2025-05-06 19:11:21: BoTorchModel, best RESULT: 0.1947368421052632, completed 44 = &sum;44/50, new result: 0.3789473684210526                     
2025-05-06 19:12:12: BoTorchModel, best RESULT: 0.1947368421052632, completed 43 = &sum;43/50, new result: 0.3157894736842105                     
2025-05-06 19:12:58: BoTorchModel, best RESULT: 0.1947368421052632, completed 42 = &sum;42/50, new result: 0.2421052631578947                     
2025-05-06 19:13:58: BoTorchModel, best RESULT: 0.1947368421052632, completed 41 = &sum;41/50, new result: 0.3052631578947368                     
2025-05-06 19:14:38: BoTorchModel, best RESULT: 0.1947368421052632, completed 40 = &sum;40/50, new result: 0.31052631578947365                    
2025-05-06 19:15:15: BoTorchModel, best RESULT: 0.1947368421052632, completed 39 = &sum;39/50, new result: 0.2789473684210526                     
2025-05-06 19:15:55: BoTorchModel, best RESULT: 0.1947368421052632, completed 38 = &sum;38/50, new result: 0.3894736842105263                     
2025-05-06 19:16:28: BoTorchModel, best RESULT: 0.1947368421052632, completed 37 = &sum;37/50, new result: 0.31052631578947365                    
2025-05-06 19:17:02: BoTorchModel, best RESULT: 0.1947368421052632, completed 36 = &sum;36/50, new result: 0.35789473684210527                    
2025-05-06 19:17:31: BoTorchModel, best RESULT: 0.1947368421052632, completed 35 = &sum;35/50, new result: 0.3631578947368421                     
2025-05-06 19:18:07: BoTorchModel, best RESULT: 0.1947368421052632, completed 34 = &sum;34/50, new result: 0.3263157894736842                     
2025-05-06 19:18:50: BoTorchModel, best RESULT: 0.1947368421052632, completed 33 = &sum;33/50, new result: 0.4052631578947369                     
2025-05-06 19:19:21: BoTorchModel, best RESULT: 0.1947368421052632, completed 32 = &sum;32/50, new result: 0.28421052631578947                    
2025-05-06 19:20:00: BoTorchModel, best RESULT: 0.1947368421052632, completed 31 = &sum;31/50, new result: 0.3631578947368421                     
2025-05-06 19:20:38: BoTorchModel, best RESULT: 0.1947368421052632, completed 30 = &sum;30/50, new result: 0.39473684210526316                    
2025-05-06 19:21:19: BoTorchModel, best RESULT: 0.1947368421052632, completed 29 = &sum;29/50, new result: 0.20526315789473681                    
2025-05-06 19:22:02: BoTorchModel, best RESULT: 0.1947368421052632, completed 28 = &sum;28/50, new result: 0.4789473684210527                     
2025-05-06 19:22:48: BoTorchModel, best RESULT: 0.1947368421052632, completed 27 = &sum;27/50, new result: 0.3263157894736842                     
2025-05-06 19:23:29: BoTorchModel, best RESULT: 0.1947368421052632, completed 26 = &sum;26/50, new result: 0.3526315789473684                     
2025-05-06 19:24:15: BoTorchModel, best RESULT: 0.1947368421052632, completed 25 = &sum;25/50, new result: 0.3315789473684211                     
2025-05-06 19:24:49: BoTorchModel, best RESULT: 0.1947368421052632, completed 24 = &sum;24/50, new result: 0.2947368421052632                     
2025-05-06 19:25:23: BoTorchModel, best RESULT: 0.1947368421052632, completed 23 = &sum;23/50, new result: 0.2947368421052632                     
2025-05-06 19:25:59: BoTorchModel, best RESULT: 0.1947368421052632, completed 22 = &sum;22/50, new result: 0.35789473684210527                    
2025-05-06 19:26:37: BoTorchModel, best RESULT: 0.1947368421052632, completed 21 = &sum;21/50, new result: 0.35789473684210527                    
2025-05-06 19:27:10: BoTorchModel, best RESULT: 0.1947368421052632, completed 20 = &sum;20/50, new result: 0.2789473684210526                     
2025-05-06 19:27:53: BoTorchModel, best RESULT: 0.1947368421052632, completed 19 = &sum;19/50, new result: 0.3631578947368421                     
2025-05-06 19:28:39: BoTorchModel, best RESULT: 0.1947368421052632, completed 18 = &sum;18/50, new result: 0.3894736842105263                     
2025-05-06 19:29:21: BoTorchModel, best RESULT: 0.1947368421052632, completed 17 = &sum;17/50, new result: 0.20526315789473681                    
2025-05-06 19:30:02: BoTorchModel, best RESULT: 0.1947368421052632, completed 16 = &sum;16/50, new result: 0.21578947368421053                    
2025-05-06 19:30:39: BoTorchModel, best RESULT: 0.1947368421052632, completed 15 = &sum;15/50, new result: 0.25263157894736843                    
2025-05-06 19:31:17: BoTorchModel, best RESULT: 0.1947368421052632, completed 14 = &sum;14/50, new result: 0.27368421052631575                    
2025-05-06 19:31:51: BoTorchModel, best RESULT: 0.1947368421052632, completed 13 = &sum;13/50, new result: 0.2684210526315789                     
2025-05-06 19:32:28: BoTorchModel, best RESULT: 0.1947368421052632, completed 12 = &sum;12/50, new result: 0.3421052631578947                     
2025-05-06 19:33:06: BoTorchModel, best RESULT: 0.1947368421052632, completed 11 = &sum;11/50, new result: 0.3052631578947368                     
2025-05-06 19:33:42: BoTorchModel, best RESULT: 0.1947368421052632, completed 10 = &sum;10/50, new result: 0.368421052631579                      
2025-05-06 19:34:15: BoTorchModel, best RESULT: 0.1947368421052632, completed 9 = &sum;9/50, new result: 0.21578947368421053                      
2025-05-06 19:34:50: BoTorchModel, best RESULT: 0.1947368421052632, completed 8 = &sum;8/50, new result: 0.3157894736842105                       
2025-05-06 19:35:28: BoTorchModel, best RESULT: 0.1947368421052632, completed 7 = &sum;7/50, new result: 0.34736842105263155                      
2025-05-06 19:36:01: BoTorchModel, best RESULT: 0.1947368421052632, completed 6 = &sum;6/50, new result: 0.3157894736842105                       
2025-05-06 19:36:32: BoTorchModel, best RESULT: 0.1947368421052632, completed 5 = &sum;5/50, new result: 0.24736842105263157                      
2025-05-06 19:37:05: BoTorchModel, best RESULT: 0.1947368421052632, completed 4 = &sum;4/50, new result: 0.3526315789473684                       
2025-05-06 19:37:32: BoTorchModel, best RESULT: 0.1947368421052632, completed 3 = &sum;3/50, new result: 0.2315789473684211                       
2025-05-06 19:38:03: BoTorchModel, best RESULT: 0.1947368421052632, completed 2 = &sum;2/50, new result: 0.30000000000000004                      
2025-05-06 19:38:31: BoTorchModel, best RESULT: 0.1947368421052632, completed 1 = &sum;1/50, new result: 0.34736842105263155                      
2025-05-06 19:39:01: BoTorchModel, best RESULT: 0.1947368421052632, finishing jobs, finished 50 jobs                                          
2025-05-06 19:39:16: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #1/50                                                  
2025-05-06 19:39:46: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #2/50 | ETA: 11m 42s                                   
2025-05-06 19:40:13: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #3/50 | ETA: 9m 50s                                    
2025-05-06 19:40:39: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #4/50 | ETA: 8m 47s                                    
2025-05-06 19:41:05: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #5/50 | ETA: 7m 47s                                    
2025-05-06 19:41:28: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #6/50 | ETA: 7m 8s                                     
2025-05-06 19:41:52: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #7/50 | ETA: 6m 46s                                    
2025-05-06 19:42:14: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #8/50 | ETA: 6m 20s                                    
2025-05-06 19:42:35: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #9/50 | ETA: 6m 2s                                     
2025-05-06 19:42:54: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #10/50 | ETA: 5m 46s                                   
2025-05-06 19:43:15: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #11/50 | ETA: 5m 34s                                   
2025-05-06 19:43:36: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #12/50 | ETA: 5m 20s                                   
2025-05-06 19:43:57: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #13/50 | ETA: 5m 7s                                    
2025-05-06 19:44:20: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #14/50 | ETA: 4m 54s                                   
2025-05-06 19:44:41: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #15/50 | ETA: 4m 42s                                   
2025-05-06 19:45:06: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #16/50 | ETA: 4m 31s                                   
2025-05-06 19:45:39: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #17/50 | ETA: 4m 27s                                   
2025-05-06 19:46:07: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #18/50 | ETA: 4m 16s                                   
2025-05-06 19:46:33: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #19/50 | ETA: 4m 8s                                    
2025-05-06 19:46:58: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #20/50 | ETA: 3m 59s                                   
2025-05-06 19:47:28: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #21/50 | ETA: 3m 51s                                   
2025-05-06 19:47:51: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #22/50 | ETA: 3m 42s                                   
2025-05-06 19:48:18: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #23/50 | ETA: 3m 34s                                   
2025-05-06 19:48:41: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #24/50 | ETA: 3m 26s                                   
2025-05-06 19:49:07: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #25/50 | ETA: 3m 19s                                   
2025-05-06 19:49:32: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #26/50 | ETA: 3m 11s                                   
2025-05-06 19:49:56: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #27/50 | ETA: 3m 3s                                    
2025-05-06 19:50:20: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #28/50 | ETA: 2m 55s                                   
2025-05-06 19:50:43: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #29/50 | ETA: 2m 47s                                   
2025-05-06 19:51:08: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #30/50 | ETA: 2m 39s                                   
2025-05-06 19:51:33: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #31/50 | ETA: 2m 31s                                   
2025-05-06 19:51:58: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #32/50 | ETA: 2m 24s                                   
2025-05-06 19:52:22: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #33/50 | ETA: 2m 16s                                   
2025-05-06 19:52:53: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #34/50 | ETA: 2m 8s                                    
2025-05-06 19:53:21: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #35/50 | ETA: 2m 1s                                    
2025-05-06 19:53:46: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #36/50 | ETA: 1m 53s                                   
2025-05-06 19:54:13: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #37/50 | ETA: 1m 46s                                   
2025-05-06 19:54:36: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #38/50 | ETA: 1m 38s                                   
2025-05-06 19:55:08: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #39/50 | ETA: 1m 31s                                   
2025-05-06 19:55:31: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #40/50 | ETA: 1m 23s                                   
2025-05-06 19:55:54: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #41/50 | ETA: 1m 16s                                   
2025-05-06 19:56:20: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #42/50 | ETA: 1m 8s                                    
2025-05-06 19:56:47: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #43/50 | ETA: 1m 1s                                    
2025-05-06 19:57:15: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #44/50 | ETA: 53s                                      
2025-05-06 19:57:42: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #45/50 | ETA: 46s                                      
2025-05-06 19:58:12: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #46/50 | ETA: 38s                                      
2025-05-06 19:58:38: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #47/50 | ETA: 31s                                      
2025-05-06 19:59:05: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #48/50 | ETA: 23s                                      
2025-05-06 19:59:29: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #49/50 | ETA: 15s                                      
2025-05-06 19:59:54: BoTorchModel, best RESULT: 0.1947368421052632, getting new HP set #50/50 | ETA: 7s                                       
2025-05-06 20:00:22: BoTorchModel, best RESULT: 0.1947368421052632, eval start                                                                
2025-05-06 20:00:37: BoTorchModel, best RESULT: 0.1947368421052632, starting new job                                                          
2025-05-06 20:01:04: BoTorchModel, best RESULT: 0.1947368421052632, unknown 1 = &sum;1/50, started new job                                        
2025-05-06 20:01:22: BoTorchModel, best RESULT: 0.1947368421052632, running 1 = &sum;1/50, eval start                                             
2025-05-06 20:01:41: BoTorchModel, best RESULT: 0.1947368421052632, running 1 = &sum;1/50, starting new job                                       
2025-05-06 20:01:59: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 1/1 = &sum;2/50, started new job                            
2025-05-06 20:02:14: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 1/1 = &sum;2/50, eval start                                 
2025-05-06 20:02:29: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 1/1 = &sum;2/50, starting new job                           
2025-05-06 20:02:49: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 2/1 = &sum;3/50, started new job                            
2025-05-06 20:03:04: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 2/1 = &sum;3/50, eval start                                 
2025-05-06 20:03:17: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 2/1 = &sum;3/50, starting new job                           
2025-05-06 20:03:31: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 2/1/1 = &sum;4/50, started new job                  
2025-05-06 20:03:43: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 3/1 = &sum;4/50, eval start                                 
2025-05-06 20:03:56: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 3/1 = &sum;4/50, starting new job                           
2025-05-06 20:04:10: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 3/1/1 = &sum;5/50, started new job                  
2025-05-06 20:04:22: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 4/1 = &sum;5/50, eval start                                 
2025-05-06 20:04:35: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 4/1 = &sum;5/50, starting new job                           
2025-05-06 20:04:50: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 5/1 = &sum;6/50, started new job                            
2025-05-06 20:05:03: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 5/1 = &sum;6/50, eval start                                 
2025-05-06 20:05:16: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 5/1 = &sum;6/50, starting new job                           
2025-05-06 20:05:30: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 6/1 = &sum;7/50, started new job                            
2025-05-06 20:05:43: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 6/1 = &sum;7/50, eval start                                 
2025-05-06 20:05:54: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 6/1 = &sum;7/50, starting new job                           
2025-05-06 20:06:08: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 6/1/1 = &sum;8/50, started new job                  
2025-05-06 20:06:21: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 6/1/1 = &sum;8/50, eval start                       
2025-05-06 20:06:34: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 6/1/1 = &sum;8/50, starting new job                 
2025-05-06 20:06:48: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 7/1/1 = &sum;9/50, started new job                  
2025-05-06 20:07:00: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 8/1 = &sum;9/50, eval start                                 
2025-05-06 20:07:13: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 8/1 = &sum;9/50, starting new job                           
2025-05-06 20:07:28: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 9/1 = &sum;10/50, started new job                           
2025-05-06 20:07:40: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 9/1 = &sum;10/50, eval start                                
2025-05-06 20:07:53: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 9/1 = &sum;10/50, starting new job                          
2025-05-06 20:08:06: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 10/1 = &sum;11/50, started new job                          
2025-05-06 20:08:18: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 10/1 = &sum;11/50, eval start                               
2025-05-06 20:08:31: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 10/1 = &sum;11/50, starting new job                         
2025-05-06 20:08:45: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 10/1/1 = &sum;12/50, started new job                
2025-05-06 20:09:00: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 10/1/1 = &sum;12/50, eval start                     
2025-05-06 20:09:13: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 10/1/1 = &sum;12/50, starting new job               
2025-05-06 20:09:27: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 12/1 = &sum;13/50, started new job                          
2025-05-06 20:09:39: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 12/1 = &sum;13/50, eval start                               
2025-05-06 20:09:52: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 12/1 = &sum;13/50, starting new job                         
2025-05-06 20:10:06: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 13/1 = &sum;14/50, started new job                          
2025-05-06 20:10:20: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 13/1 = &sum;14/50, eval start                               
2025-05-06 20:10:33: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 13/1 = &sum;14/50, starting new job                         
2025-05-06 20:10:46: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 14/1 = &sum;15/50, started new job                          
2025-05-06 20:10:59: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 14/1 = &sum;15/50, eval start                               
2025-05-06 20:11:11: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 14/1 = &sum;15/50, starting new job                         
2025-05-06 20:11:25: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 14/1/1 = &sum;16/50, started new job                
2025-05-06 20:11:38: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 15/1 = &sum;16/50, eval start                               
2025-05-06 20:11:50: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 15/1 = &sum;16/50, starting new job                         
2025-05-06 20:12:06: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 15/1/1 = &sum;17/50, started new job                
2025-05-06 20:12:20: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 16/1 = &sum;17/50, eval start                               
2025-05-06 20:12:37: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 16/1 = &sum;17/50, starting new job                         
2025-05-06 20:12:53: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 17/1 = &sum;18/50, started new job                          
2025-05-06 20:13:07: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 17/1 = &sum;18/50, eval start                               
2025-05-06 20:13:22: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 17/1 = &sum;18/50, starting new job                         
2025-05-06 20:13:37: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 17/1/1 = &sum;19/50, started new job                
2025-05-06 20:13:52: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 18/1 = &sum;19/50, eval start                               
2025-05-06 20:14:07: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 18/1 = &sum;19/50, starting new job                         
2025-05-06 20:14:23: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 19/1 = &sum;20/50, started new job                          
2025-05-06 20:14:36: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 19/1 = &sum;20/50, eval start                               
2025-05-06 20:14:52: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 19/1 = &sum;20/50, starting new job                         
2025-05-06 20:15:08: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 19/1/1 = &sum;21/50, started new job                
2025-05-06 20:15:22: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 20/1 = &sum;21/50, eval start                               
2025-05-06 20:15:36: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 20/1 = &sum;21/50, starting new job                         
2025-05-06 20:15:55: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 21/1 = &sum;22/50, started new job                          
2025-05-06 20:16:10: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 21/1 = &sum;22/50, eval start                               
2025-05-06 20:16:25: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 21/1 = &sum;22/50, starting new job                         
2025-05-06 20:16:42: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 21/1/1 = &sum;23/50, started new job                
2025-05-06 20:16:59: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 22/1 = &sum;23/50, eval start                               
2025-05-06 20:17:16: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 22/1 = &sum;23/50, starting new job                         
2025-05-06 20:17:34: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 23/1 = &sum;24/50, started new job                          
2025-05-06 20:17:50: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 23/1 = &sum;24/50, eval start                               
2025-05-06 20:18:04: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 23/1 = &sum;24/50, starting new job                         
2025-05-06 20:18:20: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 24/1 = &sum;25/50, started new job                          
2025-05-06 20:18:33: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 24/1 = &sum;25/50, eval start                               
2025-05-06 20:18:51: BoTorchModel, best RESULT: 0.1947368421052632, completed 25 = &sum;25/50, starting new job                                   
2025-05-06 20:19:05: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 25/1 = &sum;26/50, started new job                          
2025-05-06 20:19:19: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 25/1 = &sum;26/50, eval start                               
2025-05-06 20:19:33: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 25/1 = &sum;26/50, starting new job                         
2025-05-06 20:19:50: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 25/1/1 = &sum;27/50, started new job                
2025-05-06 20:20:08: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 26/1 = &sum;27/50, eval start                               
2025-05-06 20:20:25: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 26/1 = &sum;27/50, starting new job                         
2025-05-06 20:20:42: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 27/1 = &sum;28/50, started new job                          
2025-05-06 20:20:59: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 27/1 = &sum;28/50, eval start                               
2025-05-06 20:21:14: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 27/1 = &sum;28/50, starting new job                         
2025-05-06 20:21:34: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 28/1 = &sum;29/50, started new job                          
2025-05-06 20:21:52: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 28/1 = &sum;29/50, eval start                               
2025-05-06 20:22:07: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 28/1 = &sum;29/50, starting new job                         
2025-05-06 20:22:25: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 29/1 = &sum;30/50, started new job                          
2025-05-06 20:22:51: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 29/1 = &sum;30/50, eval start                               
2025-05-06 20:23:08: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 29/1 = &sum;30/50, starting new job                         
2025-05-06 20:23:24: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 29/1/1 = &sum;31/50, started new job                
2025-05-06 20:23:45: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 29/2 = &sum;31/50, eval start                               
2025-05-06 20:24:01: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 29/2 = &sum;31/50, starting new job                         
2025-05-06 20:24:19: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 30/1/1 = &sum;32/50, started new job                
2025-05-06 20:24:34: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 30/1/1 = &sum;32/50, eval start                     
2025-05-06 20:24:55: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 30/2 = &sum;32/50, starting new job                         
2025-05-06 20:25:12: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 30/2/1 = &sum;33/50, started new job                
2025-05-06 20:25:32: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 30/3 = &sum;33/50, eval start                               
2025-05-06 20:25:51: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 30/3 = &sum;33/50, starting new job                         
2025-05-06 20:26:07: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 31/2/1 = &sum;34/50, started new job                
2025-05-06 20:26:21: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 31/3 = &sum;34/50, eval start                               
2025-05-06 20:26:37: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 31/3 = &sum;34/50, starting new job                         
2025-05-06 20:27:00: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 31/3/1 = &sum;35/50, started new job                
2025-05-06 20:27:16: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 31/3/1 = &sum;35/50, eval start                     
2025-05-06 20:27:33: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 31/3/1 = &sum;35/50, starting new job               
2025-05-06 20:27:54: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 31/4/1 = &sum;36/50, started new job                
2025-05-06 20:28:10: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 31/4/1 = &sum;36/50, eval start                     
2025-05-06 20:28:29: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 31/5 = &sum;36/50, starting new job                         
2025-05-06 20:28:49: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 31/5/1 = &sum;37/50, started new job                
2025-05-06 20:29:05: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 31/6 = &sum;37/50, eval start                               
2025-05-06 20:29:22: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 31/6 = &sum;37/50, starting new job                         
2025-05-06 20:29:44: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 31/6/1 = &sum;38/50, started new job                
2025-05-06 20:30:02: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 33/5 = &sum;38/50, eval start                               
2025-05-06 20:30:19: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 33/5 = &sum;38/50, starting new job                         
2025-05-06 20:30:39: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 33/5/1 = &sum;39/50, started new job                
2025-05-06 20:30:56: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 33/5/1 = &sum;39/50, eval start                     
2025-05-06 20:31:11: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 33/5/1 = &sum;39/50, starting new job               
2025-05-06 20:31:31: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 33/6/1 = &sum;40/50, started new job                
2025-05-06 20:31:46: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 33/7 = &sum;40/50, eval start                               
2025-05-06 20:32:01: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 33/7 = &sum;40/50, starting new job                         
2025-05-06 20:32:20: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 33/7/1 = &sum;41/50, started new job                
2025-05-06 20:32:35: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 33/7/1 = &sum;41/50, eval start                     
2025-05-06 20:32:51: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 33/7/1 = &sum;41/50, starting new job               
2025-05-06 20:33:09: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 33/8/1 = &sum;42/50, started new job                
2025-05-06 20:33:25: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 33/8/1 = &sum;42/50, eval start                     
2025-05-06 20:33:45: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 33/9 = &sum;42/50, starting new job                         
2025-05-06 20:34:04: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 33/9/1 = &sum;43/50, started new job                
2025-05-06 20:34:23: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 33/10 = &sum;43/50, eval start                              
2025-05-06 20:34:39: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 33/10 = &sum;43/50, starting new job                        
2025-05-06 20:34:55: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 33/10/1 = &sum;44/50, started new job               
2025-05-06 20:35:12: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 33/11 = &sum;44/50, eval start                              
2025-05-06 20:35:29: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 33/11 = &sum;44/50, starting new job                        
2025-05-06 20:35:51: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 34/10/1 = &sum;45/50, started new job               
2025-05-06 20:36:11: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 34/10/1 = &sum;45/50, eval start                    
2025-05-06 20:36:28: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/pending 34/10/1 = &sum;45/50, starting new job              
2025-05-06 20:36:46: BoTorchModel, best RESULT: 0.1947368421052632, completed/running/unknown 44/1/1 = &sum;46/50, started new job                
2025-05-06 20:37:07: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 45/1 = &sum;46/50, eval start                               
2025-05-06 20:37:23: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 45/1 = &sum;46/50, starting new job                         
2025-05-06 20:37:42: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 46/1 = &sum;47/50, started new job                          
2025-05-06 20:37:59: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 46/1 = &sum;47/50, eval start                               
2025-05-06 20:38:18: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 46/1 = &sum;47/50, starting new job                         
2025-05-06 20:38:34: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 47/1 = &sum;48/50, started new job                          
2025-05-06 20:38:51: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 47/1 = &sum;48/50, eval start                               
2025-05-06 20:39:11: BoTorchModel, best RESULT: 0.1947368421052632, completed/running 47/1 = &sum;48/50, starting new job                         
2025-05-06 20:39:33: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 48/1 = &sum;49/50, started new job                          
2025-05-06 20:39:53: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 48/1 = &sum;49/50, eval start                               
2025-05-06 20:40:12: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 48/1 = &sum;49/50, starting new job                         
2025-05-06 20:40:31: BoTorchModel, best RESULT: 0.1947368421052632, completed/unknown 49/1 = &sum;50/50, started new job                          
2025-05-06 20:40:52: BoTorchModel, best RESULT: 0.1947368421052632, completed/pending 49/1 = &sum;50/50, new result: 0.368421052631579            
2025-05-06 20:41:32: BoTorchModel, best RESULT: 0.1947368421052632, completed 49 = &sum;49/50, new result: 0.30000000000000004                    
2025-05-06 20:42:09: BoTorchModel, best RESULT: 0.1947368421052632, completed 48 = &sum;48/50, new result: 0.25263157894736843                    
2025-05-06 20:42:42: BoTorchModel, best RESULT: 0.1947368421052632, completed 47 = &sum;47/50, new result: 0.3631578947368421                     
2025-05-06 20:43:16: BoTorchModel, best RESULT: 0.1947368421052632, completed 46 = &sum;46/50, new result: 0.3631578947368421                     
2025-05-06 20:43:51: BoTorchModel, best RESULT: 0.1947368421052632, completed 45 = &sum;45/50, new result: 0.18947368421052635                    
2025-05-06 20:44:25: BoTorchModel, best RESULT: 0.18947368421052635, completed 44 = &sum;44/50, new result: 0.3052631578947368                    
2025-05-06 20:44:58: BoTorchModel, best RESULT: 0.18947368421052635, completed 43 = &sum;43/50, new result: 0.2578947368421053                    
2025-05-06 20:45:29: BoTorchModel, best RESULT: 0.18947368421052635, completed 42 = &sum;42/50, new result: 0.3631578947368421                    
2025-05-06 20:46:00: BoTorchModel, best RESULT: 0.18947368421052635, completed 41 = &sum;41/50, new result: 0.3631578947368421                    
2025-05-06 20:46:30: BoTorchModel, best RESULT: 0.18947368421052635, completed 40 = &sum;40/50, new result: 0.3631578947368421                    
2025-05-06 20:47:03: BoTorchModel, best RESULT: 0.18947368421052635, completed 39 = &sum;39/50, new result: 0.35789473684210527                   
2025-05-06 20:47:38: BoTorchModel, best RESULT: 0.18947368421052635, completed 38 = &sum;38/50, new result: 0.3631578947368421                    
2025-05-06 20:48:09: BoTorchModel, best RESULT: 0.18947368421052635, completed 37 = &sum;37/50, new result: 0.2421052631578947                    
2025-05-06 20:48:41: BoTorchModel, best RESULT: 0.18947368421052635, completed 36 = &sum;36/50, new result: 0.33684210526315794                   
2025-05-06 20:49:14: BoTorchModel, best RESULT: 0.18947368421052635, completed 35 = &sum;35/50, new result: 0.35789473684210527                   
2025-05-06 20:49:52: BoTorchModel, best RESULT: 0.18947368421052635, completed 34 = &sum;34/50, new result: 0.22631578947368425                   
2025-05-06 20:50:25: BoTorchModel, best RESULT: 0.18947368421052635, completed 33 = &sum;33/50, new result: 0.3631578947368421                    
2025-05-06 20:51:04: BoTorchModel, best RESULT: 0.18947368421052635, completed 32 = &sum;32/50, new result: 0.24736842105263157                   
2025-05-06 20:51:37: BoTorchModel, best RESULT: 0.18947368421052635, completed 31 = &sum;31/50, new result: 0.33684210526315794                   
2025-05-06 20:52:16: BoTorchModel, best RESULT: 0.18947368421052635, completed 30 = &sum;30/50, new result: 0.3631578947368421                    
2025-05-06 20:52:55: BoTorchModel, best RESULT: 0.18947368421052635, completed 29 = &sum;29/50, new result: 0.23684210526315785                   
2025-05-06 20:53:30: BoTorchModel, best RESULT: 0.18947368421052635, completed 28 = &sum;28/50, new result: 0.32105263157894737                   
2025-05-06 20:54:10: BoTorchModel, best RESULT: 0.18947368421052635, completed 27 = &sum;27/50, new result: 0.3315789473684211                    
2025-05-06 20:54:44: BoTorchModel, best RESULT: 0.18947368421052635, completed 26 = &sum;26/50, new result: 0.34736842105263155                   
2025-05-06 20:55:36: BoTorchModel, best RESULT: 0.18947368421052635, completed 25 = &sum;25/50, new result: 0.34736842105263155                   
2025-05-06 20:56:19: BoTorchModel, best RESULT: 0.18947368421052635, completed 24 = &sum;24/50, new result: 0.2789473684210526                    
2025-05-06 20:56:59: BoTorchModel, best RESULT: 0.18947368421052635, completed 23 = &sum;23/50, new result: 0.35789473684210527                   
2025-05-06 20:57:54: BoTorchModel, best RESULT: 0.18947368421052635, completed 22 = &sum;22/50, new result: 0.2315789473684211                    
2025-05-06 20:58:43: BoTorchModel, best RESULT: 0.18947368421052635, completed 21 = &sum;21/50, new result: 0.22631578947368425                   
2025-05-06 20:59:36: BoTorchModel, best RESULT: 0.18947368421052635, completed 20 = &sum;20/50, new result: 0.26315789473684215                   
2025-05-06 21:00:31: BoTorchModel, best RESULT: 0.18947368421052635, completed 19 = &sum;19/50, new result: 0.3631578947368421                    
2025-05-06 21:01:30: BoTorchModel, best RESULT: 0.18947368421052635, completed 18 = &sum;18/50, new result: 0.3421052631578947                    
2025-05-06 21:02:29: BoTorchModel, best RESULT: 0.18947368421052635, completed 17 = &sum;17/50, new result: 0.28421052631578947                   
2025-05-06 21:03:18: BoTorchModel, best RESULT: 0.18947368421052635, completed 16 = &sum;16/50, new result: 0.28421052631578947                   
2025-05-06 21:03:58: BoTorchModel, best RESULT: 0.18947368421052635, completed 15 = &sum;15/50, new result: 0.3631578947368421                    
2025-05-06 21:04:35: BoTorchModel, best RESULT: 0.18947368421052635, completed 14 = &sum;14/50, new result: 0.2210526315789474                    
2025-05-06 21:05:12: BoTorchModel, best RESULT: 0.18947368421052635, completed 13 = &sum;13/50, new result: 0.3052631578947368                    
2025-05-06 21:05:46: BoTorchModel, best RESULT: 0.18947368421052635, completed 12 = &sum;12/50, new result: 0.2421052631578947                    
2025-05-06 21:06:25: BoTorchModel, best RESULT: 0.18947368421052635, completed 11 = &sum;11/50, new result: 0.3052631578947368                    
2025-05-06 21:07:03: BoTorchModel, best RESULT: 0.18947368421052635, completed 10 = &sum;10/50, new result: 0.21578947368421053                   
2025-05-06 21:07:36: BoTorchModel, best RESULT: 0.18947368421052635, completed 9 = &sum;9/50, new result: 0.3052631578947368                      
2025-05-06 21:08:11: BoTorchModel, best RESULT: 0.18947368421052635, completed 8 = &sum;8/50, new result: 0.33684210526315794                     
2025-05-06 21:08:46: BoTorchModel, best RESULT: 0.18947368421052635, completed 7 = &sum;7/50, new result: 0.2421052631578947                      
2025-05-06 21:09:23: BoTorchModel, best RESULT: 0.18947368421052635, completed 6 = &sum;6/50, new result: 0.3315789473684211                      
2025-05-06 21:09:58: BoTorchModel, best RESULT: 0.18947368421052635, completed 5 = &sum;5/50, new result: 0.3631578947368421                      
2025-05-06 21:10:34: BoTorchModel, best RESULT: 0.18947368421052635, completed 4 = &sum;4/50, new result: 0.2315789473684211                      
2025-05-06 21:11:15: BoTorchModel, best RESULT: 0.18947368421052635, completed 3 = &sum;3/50, new result: 0.35789473684210527                     
2025-05-06 21:11:57: BoTorchModel, best RESULT: 0.18947368421052635, completed 2 = &sum;2/50, new result: 0.23684210526315785                     
2025-05-06 21:12:38: BoTorchModel, best RESULT: 0.18947368421052635, completed 1 = &sum;1/50, new result: 0.19999999999999996                     
2025-05-06 21:13:14: BoTorchModel, best RESULT: 0.18947368421052635, finishing jobs, finished 50 jobs                                         
2025-05-06 21:13:34: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #1/50                                                 
2025-05-06 21:14:12: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #2/50 | ETA: 14m 1s                                   
2025-05-06 21:14:37: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #3/50 | ETA: 10m 22s                                  
2025-05-06 21:15:03: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #4/50 | ETA: 8m 59s                                   
2025-05-06 21:15:28: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #5/50 | ETA: 8m 8s                                    
2025-05-06 21:16:00: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #6/50 | ETA: 7m 40s                                   
2025-05-06 21:16:28: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #7/50 | ETA: 7m 23s                                   
2025-05-06 21:16:56: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #8/50 | ETA: 7m 5s                                    
2025-05-06 21:17:21: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #9/50 | ETA: 6m 47s                                   
2025-05-06 21:17:54: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #10/50 | ETA: 6m 36s                                  
2025-05-06 21:18:22: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #11/50 | ETA: 6m 22s                                  
2025-05-06 21:18:53: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #12/50 | ETA: 6m 9s                                   
2025-05-06 21:19:20: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #13/50 | ETA: 5m 58s                                  
2025-05-06 21:19:51: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #14/50 | ETA: 5m 46s                                  
2025-05-06 21:20:17: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #15/50 | ETA: 5m 35s                                  
2025-05-06 21:20:52: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #16/50 | ETA: 5m 26s                                  
2025-05-06 21:21:21: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #17/50 | ETA: 5m 17s                                  
2025-05-06 21:21:52: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #18/50 | ETA: 5m 6s                                   
2025-05-06 21:22:20: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #19/50 | ETA: 4m 55s                                  
2025-05-06 21:22:52: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #20/50 | ETA: 4m 47s                                  
2025-05-06 21:23:22: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #21/50 | ETA: 4m 37s                                  
2025-05-06 21:23:51: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #22/50 | ETA: 4m 28s                                  
2025-05-06 21:24:18: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #23/50 | ETA: 4m 19s                                  
2025-05-06 21:24:46: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #24/50 | ETA: 4m 10s                                  
2025-05-06 21:25:10: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #25/50 | ETA: 4m 0s                                   
2025-05-06 21:25:40: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #26/50 | ETA: 3m 50s                                  
2025-05-06 21:26:04: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #27/50 | ETA: 3m 41s                                  
2025-05-06 21:26:30: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #28/50 | ETA: 3m 31s                                  
2025-05-06 21:26:55: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #29/50 | ETA: 3m 22s                                  
2025-05-06 21:27:21: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #30/50 | ETA: 3m 14s                                  
2025-05-06 21:27:50: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #31/50 | ETA: 3m 5s                                   
2025-05-06 21:28:16: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #32/50 | ETA: 2m 55s                                  
2025-05-06 21:28:46: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #33/50 | ETA: 2m 46s                                  
2025-05-06 21:29:11: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #34/50 | ETA: 2m 37s                                  
2025-05-06 21:29:40: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #35/50 | ETA: 2m 28s                                  
2025-05-06 21:30:05: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #36/50 | ETA: 2m 19s                                  
2025-05-06 21:30:33: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #37/50 | ETA: 2m 10s                                  
2025-05-06 21:31:00: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #38/50 | ETA: 2m 1s                                   
2025-05-06 21:31:29: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #39/50 | ETA: 1m 52s                                  
2025-05-06 21:31:55: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #40/50 | ETA: 1m 43s                                  
2025-05-06 21:32:24: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #41/50 | ETA: 1m 34s                                  
2025-05-06 21:32:52: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #42/50 | ETA: 1m 25s                                  
2025-05-06 21:33:23: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #43/50 | ETA: 1m 15s                                  
2025-05-06 21:33:48: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #44/50 | ETA: 1m 6s                                   
2025-05-06 21:34:20: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #45/50 | ETA: 57s                                     
2025-05-06 21:34:45: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #46/50 | ETA: 47s                                     
2025-05-06 21:35:11: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #47/50 | ETA: 38s                                     
2025-05-06 21:35:37: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #48/50 | ETA: 28s                                     
2025-05-06 21:36:05: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #49/50 | ETA: 19s                                     
2025-05-06 21:36:29: BoTorchModel, best RESULT: 0.18947368421052635, getting new HP set #50/50 | ETA: 9s                                      
2025-05-06 21:36:55: BoTorchModel, best RESULT: 0.18947368421052635, eval start                                                               
2025-05-06 21:37:09: BoTorchModel, best RESULT: 0.18947368421052635, starting new job                                                         
2025-05-06 21:37:25: BoTorchModel, best RESULT: 0.18947368421052635, unknown 1 = &sum;1/50, started new job                                       
2025-05-06 21:37:39: BoTorchModel, best RESULT: 0.18947368421052635, pending 1 = &sum;1/50, eval start                                            
2025-05-06 21:37:57: BoTorchModel, best RESULT: 0.18947368421052635, running 1 = &sum;1/50, starting new job                                      
2025-05-06 21:38:14: BoTorchModel, best RESULT: 0.18947368421052635, running/unknown 1/1 = &sum;2/50, started new job                             
2025-05-06 21:38:30: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 1/1 = &sum;2/50, eval start                                
2025-05-06 21:38:47: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 1/1 = &sum;2/50, starting new job                          
2025-05-06 21:39:04: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 1/1/1 = &sum;3/50, started new job                 
2025-05-06 21:39:19: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 2/1 = &sum;3/50, eval start                                
2025-05-06 21:39:36: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 2/1 = &sum;3/50, starting new job                          
2025-05-06 21:39:54: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 3/1 = &sum;4/50, started new job                           
2025-05-06 21:40:09: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 3/1 = &sum;4/50, eval start                                
2025-05-06 21:40:27: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 3/1 = &sum;4/50, starting new job                          
2025-05-06 21:40:49: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 4/1 = &sum;5/50, started new job                           
2025-05-06 21:41:04: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 4/1 = &sum;5/50, eval start                                
2025-05-06 21:41:19: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 4/1 = &sum;5/50, starting new job                          
2025-05-06 21:41:37: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 4/1/1 = &sum;6/50, started new job                 
2025-05-06 21:41:55: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 5/1 = &sum;6/50, eval start                                
2025-05-06 21:42:10: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 5/1 = &sum;6/50, starting new job                          
2025-05-06 21:42:28: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 6/1 = &sum;7/50, started new job                           
2025-05-06 21:42:47: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 6/1 = &sum;7/50, eval start                                
2025-05-06 21:43:04: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 6/1 = &sum;7/50, starting new job                          
2025-05-06 21:43:20: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 6/1/1 = &sum;8/50, started new job                 
2025-05-06 21:43:38: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 7/1 = &sum;8/50, eval start                                
2025-05-06 21:43:54: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 7/1 = &sum;8/50, starting new job                          
2025-05-06 21:44:10: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 7/1/1 = &sum;9/50, started new job                 
2025-05-06 21:44:26: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 8/1 = &sum;9/50, eval start                                
2025-05-06 21:44:43: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 8/1 = &sum;9/50, starting new job                          
2025-05-06 21:45:00: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 8/1/1 = &sum;10/50, started new job                
2025-05-06 21:45:16: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/pending 8/1/1 = &sum;10/50, eval start                     
2025-05-06 21:45:31: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/pending 8/1/1 = &sum;10/50, starting new job               
2025-05-06 21:45:50: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 9/1/1 = &sum;11/50, started new job                
2025-05-06 21:46:04: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 9/2 = &sum;11/50, eval start                               
2025-05-06 21:46:20: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 9/2 = &sum;11/50, starting new job                         
2025-05-06 21:46:38: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 10/1/1 = &sum;12/50, started new job               
2025-05-06 21:46:53: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 11/1 = &sum;12/50, eval start                              
2025-05-06 21:47:08: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 11/1 = &sum;12/50, starting new job                        
2025-05-06 21:47:25: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 11/1/1 = &sum;13/50, started new job               
2025-05-06 21:47:45: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 11/2 = &sum;13/50, eval start                              
2025-05-06 21:48:04: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 11/2 = &sum;13/50, starting new job                        
2025-05-06 21:48:25: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 12/1/1 = &sum;14/50, started new job               
2025-05-06 21:48:46: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 13/1 = &sum;14/50, eval start                              
2025-05-06 21:49:03: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 13/1 = &sum;14/50, starting new job                        
2025-05-06 21:49:21: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 14/1 = &sum;15/50, started new job                         
2025-05-06 21:49:39: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 14/1 = &sum;15/50, eval start                              
2025-05-06 21:49:55: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 14/1 = &sum;15/50, starting new job                        
2025-05-06 21:50:12: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 14/1/1 = &sum;16/50, started new job               
2025-05-06 21:50:28: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 15/1 = &sum;16/50, eval start                              
2025-05-06 21:50:45: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 15/1 = &sum;16/50, starting new job                        
2025-05-06 21:51:03: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 15/1/1 = &sum;17/50, started new job               
2025-05-06 21:51:18: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/pending 15/1/1 = &sum;17/50, eval start                    
2025-05-06 21:51:35: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/pending 15/1/1 = &sum;17/50, starting new job              
2025-05-06 21:51:55: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 16/1/1 = &sum;18/50, started new job               
2025-05-06 21:52:11: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 16/2 = &sum;18/50, eval start                              
2025-05-06 21:52:29: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 17/1 = &sum;18/50, starting new job                        
2025-05-06 21:52:49: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 17/1/1 = &sum;19/50, started new job               
2025-05-06 21:53:08: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 18/1 = &sum;19/50, eval start                              
2025-05-06 21:53:25: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 18/1 = &sum;19/50, starting new job                        
2025-05-06 21:53:42: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 18/1/1 = &sum;20/50, started new job               
2025-05-06 21:53:59: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 19/1 = &sum;20/50, eval start                              
2025-05-06 21:54:16: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 19/1 = &sum;20/50, starting new job                        
2025-05-06 21:54:33: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 19/1/1 = &sum;21/50, started new job               
2025-05-06 21:54:52: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 20/1 = &sum;21/50, eval start                              
2025-05-06 21:55:08: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 20/1 = &sum;21/50, starting new job                        
2025-05-06 21:55:27: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 20/1/1 = &sum;22/50, started new job               
2025-05-06 21:55:42: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 21/1 = &sum;22/50, eval start                              
2025-05-06 21:56:02: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 21/1 = &sum;22/50, starting new job                        
2025-05-06 21:56:19: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 21/1/1 = &sum;23/50, started new job               
2025-05-06 21:56:35: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 22/1 = &sum;23/50, eval start                              
2025-05-06 21:56:55: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 22/1 = &sum;23/50, starting new job                        
2025-05-06 21:57:13: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 22/1/1 = &sum;24/50, started new job               
2025-05-06 21:57:30: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 23/1 = &sum;24/50, eval start                              
2025-05-06 21:57:47: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 23/1 = &sum;24/50, starting new job                        
2025-05-06 21:58:08: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 23/1/1 = &sum;25/50, started new job               
2025-05-06 21:58:25: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 23/2 = &sum;25/50, eval start                              
2025-05-06 21:58:41: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 23/2 = &sum;25/50, starting new job                        
2025-05-06 21:59:02: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 25/1 = &sum;26/50, started new job                         
2025-05-06 21:59:20: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 25/1 = &sum;26/50, eval start                              
2025-05-06 21:59:38: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 25/1 = &sum;26/50, starting new job                        
2025-05-06 21:59:59: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 25/1/1 = &sum;27/50, started new job               
2025-05-06 22:00:15: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 26/1 = &sum;27/50, eval start                              
2025-05-06 22:00:35: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 26/1 = &sum;27/50, starting new job                        
2025-05-06 22:00:55: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 26/1/1 = &sum;28/50, started new job               
2025-05-06 22:01:11: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 27/1 = &sum;28/50, eval start                              
2025-05-06 22:01:28: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 27/1 = &sum;28/50, starting new job                        
2025-05-06 22:01:47: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 27/1/1 = &sum;29/50, started new job               
2025-05-06 22:02:05: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/pending 27/1/1 = &sum;29/50, eval start                    
2025-05-06 22:02:22: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/pending 27/1/1 = &sum;29/50, starting new job              
2025-05-06 22:02:39: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 28/1/1 = &sum;30/50, started new job               
2025-05-06 22:02:57: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 28/2 = &sum;30/50, eval start                              
2025-05-06 22:03:15: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 28/2 = &sum;30/50, starting new job                        
2025-05-06 22:03:33: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 30/1 = &sum;31/50, started new job                         
2025-05-06 22:03:50: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 30/1 = &sum;31/50, eval start                              
2025-05-06 22:04:08: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 30/1 = &sum;31/50, starting new job                        
2025-05-06 22:04:25: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 30/1/1 = &sum;32/50, started new job               
2025-05-06 22:04:43: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 31/1 = &sum;32/50, eval start                              
2025-05-06 22:05:00: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 31/1 = &sum;32/50, starting new job                        
2025-05-06 22:05:18: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 31/1/1 = &sum;33/50, started new job               
2025-05-06 22:05:36: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 31/2 = &sum;33/50, eval start                              
2025-05-06 22:05:53: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 31/2 = &sum;33/50, starting new job                        
2025-05-06 22:06:11: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 33/1 = &sum;34/50, started new job                         
2025-05-06 22:06:27: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 33/1 = &sum;34/50, eval start                              
2025-05-06 22:06:46: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 33/1 = &sum;34/50, starting new job                        
2025-05-06 22:07:05: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 33/1/1 = &sum;35/50, started new job               
2025-05-06 22:07:21: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 34/1 = &sum;35/50, eval start                              
2025-05-06 22:07:44: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 34/1 = &sum;35/50, starting new job                        
2025-05-06 22:08:03: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 34/1/1 = &sum;36/50, started new job               
2025-05-06 22:08:18: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/pending 34/1/1 = &sum;36/50, eval start                    
2025-05-06 22:08:40: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 35/1 = &sum;36/50, starting new job                        
2025-05-06 22:09:00: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 35/1/1 = &sum;37/50, started new job               
2025-05-06 22:09:18: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/pending 35/1/1 = &sum;37/50, eval start                    
2025-05-06 22:09:39: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 36/1 = &sum;37/50, starting new job                        
2025-05-06 22:09:58: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 36/1/1 = &sum;38/50, started new job               
2025-05-06 22:10:16: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 36/2 = &sum;38/50, eval start                              
2025-05-06 22:10:39: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 37/1 = &sum;38/50, starting new job                        
2025-05-06 22:10:59: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 38/1 = &sum;39/50, started new job                         
2025-05-06 22:11:17: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 38/1 = &sum;39/50, eval start                              
2025-05-06 22:11:38: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 38/1 = &sum;39/50, starting new job                        
2025-05-06 22:11:59: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 38/1/1 = &sum;40/50, started new job               
2025-05-06 22:12:19: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 39/1 = &sum;40/50, eval start                              
2025-05-06 22:12:40: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 39/1 = &sum;40/50, starting new job                        
2025-05-06 22:12:59: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 39/1/1 = &sum;41/50, started new job               
2025-05-06 22:13:20: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 40/1 = &sum;41/50, eval start                              
2025-05-06 22:13:43: BoTorchModel, best RESULT: 0.18947368421052635, completed 41 = &sum;41/50, starting new job                                  
2025-05-06 22:14:06: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 41/1 = &sum;42/50, started new job                         
2025-05-06 22:14:27: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 41/1 = &sum;42/50, eval start                              
2025-05-06 22:14:44: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 41/1 = &sum;42/50, starting new job                        
2025-05-06 22:15:05: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 42/1 = &sum;43/50, started new job                         
2025-05-06 22:15:27: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 42/1 = &sum;43/50, eval start                              
2025-05-06 22:15:46: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 42/1 = &sum;43/50, starting new job                        
2025-05-06 22:16:07: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 43/1 = &sum;44/50, started new job                         
2025-05-06 22:16:29: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 43/1 = &sum;44/50, eval start                              
2025-05-06 22:16:49: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 43/1 = &sum;44/50, starting new job                        
2025-05-06 22:17:11: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 44/1 = &sum;45/50, started new job                         
2025-05-06 22:17:36: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 44/1 = &sum;45/50, eval start                              
2025-05-06 22:18:00: BoTorchModel, best RESULT: 0.18947368421052635, completed/pending 44/1 = &sum;45/50, starting new job                        
2025-05-06 22:18:24: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 45/1 = &sum;46/50, started new job                         
2025-05-06 22:18:44: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 45/1 = &sum;46/50, eval start                              
2025-05-06 22:19:05: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 45/1 = &sum;46/50, starting new job                        
2025-05-06 22:19:28: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 46/1 = &sum;47/50, started new job                         
2025-05-06 22:19:47: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 46/1 = &sum;47/50, eval start                              
2025-05-06 22:20:14: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 46/1 = &sum;47/50, starting new job                        
2025-05-06 22:20:37: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 47/1 = &sum;48/50, started new job                         
2025-05-06 22:20:55: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 47/1 = &sum;48/50, eval start                              
2025-05-06 22:21:14: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 47/1 = &sum;48/50, starting new job                        
2025-05-06 22:21:34: BoTorchModel, best RESULT: 0.18947368421052635, completed/unknown 48/1 = &sum;49/50, started new job                         
2025-05-06 22:21:52: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 48/1 = &sum;49/50, eval start                              
2025-05-06 22:22:12: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 48/1 = &sum;49/50, starting new job                        
2025-05-06 22:22:36: BoTorchModel, best RESULT: 0.18947368421052635, completed/running/unknown 48/1/1 = &sum;50/50, started new job               
2025-05-06 22:22:59: BoTorchModel, best RESULT: 0.18947368421052635, completed/running 49/1 = &sum;50/50, new result: 0.19999999999999996         
2025-05-06 22:23:44: BoTorchModel, best RESULT: 0.18947368421052635, completed 49 = &sum;49/50, new result: 0.2684210526315789                    
2025-05-06 22:24:20: BoTorchModel, best RESULT: 0.18947368421052635, completed 48 = &sum;48/50, new result: 0.28421052631578947                   
2025-05-06 22:24:56: BoTorchModel, best RESULT: 0.18947368421052635, completed 47 = &sum;47/50, new result: 0.24736842105263157                   
2025-05-06 22:25:30: BoTorchModel, best RESULT: 0.18947368421052635, completed 46 = &sum;46/50, new result: 0.26315789473684215                   
2025-05-06 22:26:06: BoTorchModel, best RESULT: 0.18947368421052635, completed 45 = &sum;45/50, new result: 0.20526315789473681                   
2025-05-06 22:26:44: BoTorchModel, best RESULT: 0.18947368421052635, completed 44 = &sum;44/50, new result: 0.35789473684210527                   
2025-05-06 22:27:20: BoTorchModel, best RESULT: 0.18947368421052635, completed 43 = &sum;43/50, new result: 0.26315789473684215                   
2025-05-06 22:27:56: BoTorchModel, best RESULT: 0.18947368421052635, completed 42 = &sum;42/50, new result: 0.33684210526315794                   
2025-05-06 22:28:33: BoTorchModel, best RESULT: 0.18947368421052635, completed 41 = &sum;41/50, new result: 0.2210526315789474                    
2025-05-06 22:29:08: BoTorchModel, best RESULT: 0.18947368421052635, completed 40 = &sum;40/50, new result: 0.24736842105263157                   
2025-05-06 22:29:43: BoTorchModel, best RESULT: 0.18947368421052635, completed 39 = &sum;39/50, new result: 0.2578947368421053                    
2025-05-06 22:30:17: BoTorchModel, best RESULT: 0.18947368421052635, completed 38 = &sum;38/50, new result: 0.41052631578947374                   
2025-05-06 22:30:52: BoTorchModel, best RESULT: 0.18947368421052635, completed 37 = &sum;37/50, new result: 0.26315789473684215                   
2025-05-06 22:31:31: BoTorchModel, best RESULT: 0.18947368421052635, completed 36 = &sum;36/50, new result: 0.1842105263157895                    
2025-05-06 22:32:07: BoTorchModel, best RESULT: 0.1842105263157895, completed 35 = &sum;35/50, new result: 0.22631578947368425                    
2025-05-06 22:32:47: BoTorchModel, best RESULT: 0.1842105263157895, completed 34 = &sum;34/50, new result: 0.34736842105263155                    
2025-05-06 22:33:25: BoTorchModel, best RESULT: 0.1842105263157895, completed 33 = &sum;33/50, new result: 0.2947368421052632                     
2025-05-06 22:34:01: BoTorchModel, best RESULT: 0.1842105263157895, completed 32 = &sum;32/50, new result: 0.20526315789473681                    
2025-05-06 22:34:42: BoTorchModel, best RESULT: 0.1842105263157895, completed 31 = &sum;31/50, new result: 0.2578947368421053                     
2025-05-06 22:35:23: BoTorchModel, best RESULT: 0.1842105263157895, completed 30 = &sum;30/50, new result: 0.3631578947368421                     
2025-05-06 22:35:59: BoTorchModel, best RESULT: 0.1842105263157895, completed 29 = &sum;29/50, new result: 0.3631578947368421                     
2025-05-06 22:36:38: BoTorchModel, best RESULT: 0.1842105263157895, completed 28 = &sum;28/50, new result: 0.22631578947368425                    
2025-05-06 22:37:16: BoTorchModel, best RESULT: 0.1842105263157895, completed 27 = &sum;27/50, new result: 0.2315789473684211                     
2025-05-06 22:37:50: BoTorchModel, best RESULT: 0.1842105263157895, completed 26 = &sum;26/50, new result: 0.1947368421052632                     
2025-05-06 22:38:25: BoTorchModel, best RESULT: 0.1842105263157895, completed 25 = &sum;25/50, new result: 0.28421052631578947                    
2025-05-06 22:38:59: BoTorchModel, best RESULT: 0.1842105263157895, completed 24 = &sum;24/50, new result: 0.25263157894736843                    
2025-05-06 22:39:34: BoTorchModel, best RESULT: 0.1842105263157895, completed 23 = &sum;23/50, new result: 0.3631578947368421                     
2025-05-06 22:40:11: BoTorchModel, best RESULT: 0.1842105263157895, completed 22 = &sum;22/50, new result: 0.3052631578947368                     
2025-05-06 22:40:47: BoTorchModel, best RESULT: 0.1842105263157895, completed 21 = &sum;21/50, new result: 0.3052631578947368                     
2025-05-06 22:41:32: BoTorchModel, best RESULT: 0.1842105263157895, completed 20 = &sum;20/50, new result: 0.2210526315789474                     
2025-05-06 22:42:16: BoTorchModel, best RESULT: 0.1842105263157895, completed 19 = &sum;19/50, new result: 0.28421052631578947                    
2025-05-06 22:42:59: BoTorchModel, best RESULT: 0.1842105263157895, completed 18 = &sum;18/50, new result: 0.3263157894736842                     
2025-05-06 22:43:37: BoTorchModel, best RESULT: 0.1842105263157895, completed 17 = &sum;17/50, new result: 0.25263157894736843                    
2025-05-06 22:44:16: BoTorchModel, best RESULT: 0.1842105263157895, completed 16 = &sum;16/50, new result: 0.28421052631578947                    
2025-05-06 22:44:51: BoTorchModel, best RESULT: 0.1842105263157895, completed 15 = &sum;15/50, new result: 0.20526315789473681                    
2025-05-06 22:45:32: BoTorchModel, best RESULT: 0.1842105263157895, completed 14 = &sum;14/50, new result: 0.3052631578947368                     
2025-05-06 22:46:11: BoTorchModel, best RESULT: 0.1842105263157895, completed 13 = &sum;13/50, new result: 0.34736842105263155                    
2025-05-06 22:46:46: BoTorchModel, best RESULT: 0.1842105263157895, completed 12 = &sum;12/50, new result: 0.25263157894736843                    
2025-05-06 22:47:22: BoTorchModel, best RESULT: 0.1842105263157895, completed 11 = &sum;11/50, new result: 0.24736842105263157                    
2025-05-06 22:47:59: BoTorchModel, best RESULT: 0.1842105263157895, completed 10 = &sum;10/50, new result: 0.21578947368421053                    
2025-05-06 22:48:34: BoTorchModel, best RESULT: 0.1842105263157895, completed 9 = &sum;9/50, new result: 0.21052631578947367                      
2025-05-06 22:49:09: BoTorchModel, best RESULT: 0.1842105263157895, completed 8 = &sum;8/50, new result: 0.32105263157894737                      
2025-05-06 22:49:43: BoTorchModel, best RESULT: 0.1842105263157895, completed 7 = &sum;7/50, new result: 0.2578947368421053                       
2025-05-06 22:50:18: BoTorchModel, best RESULT: 0.1842105263157895, completed 6 = &sum;6/50, new result: 0.24736842105263157                      
2025-05-06 22:50:51: BoTorchModel, best RESULT: 0.1842105263157895, completed 5 = &sum;5/50, new result: 0.2894736842105263                       
2025-05-06 22:51:25: BoTorchModel, best RESULT: 0.1842105263157895, completed 4 = &sum;4/50, new result: 0.2894736842105263                       
2025-05-06 22:52:02: BoTorchModel, best RESULT: 0.1842105263157895, completed 3 = &sum;3/50, new result: 0.35789473684210527                      
2025-05-06 22:52:36: BoTorchModel, best RESULT: 0.1842105263157895, completed 2 = &sum;2/50, new result: 0.26315789473684215                      
2025-05-06 22:53:13: BoTorchModel, best RESULT: 0.1842105263157895, completed 1 = &sum;1/50, new result: 0.3631578947368421                       
2025-05-06 22:53:50: BoTorchModel, best RESULT: 0.1842105263157895, finishing jobs, finished 50 jobs                                          
2025-05-06 22:54:12: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #1/50                                                  
2025-05-06 22:54:48: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #2/50 | ETA: 14m 24s                                   
2025-05-06 22:55:21: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #3/50 | ETA: 11m 55s                                   
2025-05-06 22:55:50: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #4/50 | ETA: 11m 19s                                   
2025-05-06 22:56:24: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #5/50 | ETA: 11m 0s                                    
2025-05-06 22:56:54: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #6/50 | ETA: 10m 38s                                   
2025-05-06 22:57:26: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #7/50 | ETA: 10m 21s                                   
2025-05-06 22:58:00: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #8/50 | ETA: 9m 59s                                    
2025-05-06 22:58:30: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #9/50 | ETA: 9m 37s                                    
2025-05-06 22:59:04: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #10/50 | ETA: 9m 22s                                   
2025-05-06 22:59:36: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #11/50 | ETA: 9m 2s                                    
2025-05-06 23:00:09: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #12/50 | ETA: 8m 49s                                   
2025-05-06 23:00:43: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #13/50 | ETA: 8m 33s                                   
2025-05-06 23:01:17: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #14/50 | ETA: 8m 14s                                   
2025-05-06 23:01:50: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #15/50 | ETA: 8m 1s                                    
2025-05-06 23:02:21: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #16/50 | ETA: 7m 49s                                   
2025-05-06 23:02:52: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #17/50 | ETA: 7m 34s                                   
2025-05-06 23:03:25: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #18/50 | ETA: 7m 21s                                   
2025-05-06 23:04:01: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #19/50 | ETA: 7m 8s                                    
2025-05-06 23:04:34: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #20/50 | ETA: 6m 55s                                   
2025-05-06 23:05:03: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #21/50 | ETA: 6m 39s                                   
2025-05-06 23:05:36: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #22/50 | ETA: 6m 26s                                   
2025-05-06 23:06:09: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #23/50 | ETA: 6m 12s                                   
2025-05-06 23:06:41: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #24/50 | ETA: 6m 0s                                    
2025-05-06 23:07:14: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #25/50 | ETA: 5m 46s                                   
2025-05-06 23:07:46: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #26/50 | ETA: 5m 33s                                   
2025-05-06 23:08:16: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #27/50 | ETA: 5m 19s                                   
2025-05-06 23:08:56: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #28/50 | ETA: 5m 6s                                    
2025-05-06 23:09:32: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #29/50 | ETA: 4m 53s                                   
2025-05-06 23:10:05: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #30/50 | ETA: 4m 40s                                   
2025-05-06 23:10:40: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #31/50 | ETA: 4m 28s                                   
2025-05-06 23:11:11: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #32/50 | ETA: 4m 14s                                   
2025-05-06 23:11:47: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #33/50 | ETA: 4m 1s                                    
2025-05-06 23:12:20: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #34/50 | ETA: 3m 47s                                   
2025-05-06 23:12:57: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #35/50 | ETA: 3m 34s                                   
2025-05-06 23:13:28: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #36/50 | ETA: 3m 21s                                   
2025-05-06 23:14:02: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #37/50 | ETA: 3m 7s                                    
2025-05-06 23:14:36: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #38/50 | ETA: 2m 54s                                   
2025-05-06 23:15:09: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #39/50 | ETA: 2m 41s                                   
2025-05-06 23:15:45: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #40/50 | ETA: 2m 28s                                   
2025-05-06 23:16:19: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #41/50 | ETA: 2m 15s                                   
2025-05-06 23:16:52: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #42/50 | ETA: 2m 2s                                    
2025-05-06 23:17:25: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #43/50 | ETA: 1m 48s                                   
2025-05-06 23:17:58: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #44/50 | ETA: 1m 35s                                   
2025-05-06 23:18:38: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #45/50 | ETA: 1m 21s                                   
2025-05-06 23:19:16: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #46/50 | ETA: 1m 8s                                    
2025-05-06 23:19:48: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #47/50 | ETA: 54s                                      
2025-05-06 23:20:25: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #48/50 | ETA: 41s                                      
2025-05-06 23:20:58: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #49/50 | ETA: 27s                                      
2025-05-06 23:21:34: BoTorchModel, best RESULT: 0.1842105263157895, getting new HP set #50/50 | ETA: 13s                                      
2025-05-06 23:22:06: BoTorchModel, best RESULT: 0.1842105263157895, eval start                                                                
2025-05-06 23:22:24: BoTorchModel, best RESULT: 0.1842105263157895, starting new job                                                          
2025-05-06 23:22:42: BoTorchModel, best RESULT: 0.1842105263157895, unknown 1 = &sum;1/50, started new job                                        
2025-05-06 23:23:03: BoTorchModel, best RESULT: 0.1842105263157895, running 1 = &sum;1/50, eval start                                             
2025-05-06 23:23:22: BoTorchModel, best RESULT: 0.1842105263157895, running 1 = &sum;1/50, starting new job                                       
2025-05-06 23:23:42: BoTorchModel, best RESULT: 0.1842105263157895, running/unknown 1/1 = &sum;2/50, started new job                              
2025-05-06 23:24:02: BoTorchModel, best RESULT: 0.1842105263157895, running 2 = &sum;2/50, eval start                                             
2025-05-06 23:24:21: BoTorchModel, best RESULT: 0.1842105263157895, running 2 = &sum;2/50, starting new job                                       
2025-05-06 23:24:40: BoTorchModel, best RESULT: 0.1842105263157895, running/unknown 2/1 = &sum;3/50, started new job                              
2025-05-06 23:24:58: BoTorchModel, best RESULT: 0.1842105263157895, running/completed 2/1 = &sum;3/50, eval start                                 
2025-05-06 23:25:17: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 2/1 = &sum;3/50, starting new job                           
2025-05-06 23:25:37: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/unknown 2/1/1 = &sum;4/50, started new job                  
2025-05-06 23:26:00: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 3/1 = &sum;4/50, eval start                                 
2025-05-06 23:26:23: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 3/1 = &sum;4/50, starting new job                           
2025-05-06 23:26:45: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/unknown 3/1/1 = &sum;5/50, started new job                  
2025-05-06 23:27:04: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 4/1 = &sum;5/50, eval start                                 
2025-05-06 23:27:24: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 4/1 = &sum;5/50, starting new job                           
2025-05-06 23:27:47: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/unknown 4/1/1 = &sum;6/50, started new job                  
2025-05-06 23:28:05: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 5/1 = &sum;6/50, eval start                                 
2025-05-06 23:28:23: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 5/1 = &sum;6/50, starting new job                           
2025-05-06 23:28:45: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 6/1 = &sum;7/50, started new job                            
2025-05-06 23:29:04: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 6/1 = &sum;7/50, eval start                                 
2025-05-06 23:29:23: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 6/1 = &sum;7/50, starting new job                           
2025-05-06 23:29:45: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/unknown 6/1/1 = &sum;8/50, started new job                  
2025-05-06 23:30:04: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 6/2 = &sum;8/50, eval start                                 
2025-05-06 23:30:22: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 6/2 = &sum;8/50, starting new job                           
2025-05-06 23:30:41: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 8/1 = &sum;9/50, started new job                            
2025-05-06 23:30:59: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 8/1 = &sum;9/50, eval start                                 
2025-05-06 23:31:17: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 8/1 = &sum;9/50, starting new job                           
2025-05-06 23:31:41: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/unknown 8/1/1 = &sum;10/50, started new job                 
2025-05-06 23:32:32: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 9/1 = &sum;10/50, eval start                                
2025-05-06 23:32:52: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 9/1 = &sum;10/50, starting new job                          
2025-05-06 23:33:11: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 10/1 = &sum;11/50, started new job                          
2025-05-06 23:33:32: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 10/1 = &sum;11/50, eval start                               
2025-05-06 23:33:49: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 10/1 = &sum;11/50, starting new job                         
2025-05-06 23:34:10: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/unknown 10/1/1 = &sum;12/50, started new job                
2025-05-06 23:34:29: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/pending 10/1/1 = &sum;12/50, eval start                     
2025-05-06 23:34:47: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/pending 10/1/1 = &sum;12/50, starting new job               
2025-05-06 23:35:06: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/unknown 11/1/1 = &sum;13/50, started new job                
2025-05-06 23:35:25: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 12/1 = &sum;13/50, eval start                               
2025-05-06 23:35:42: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 12/1 = &sum;13/50, starting new job                         
2025-05-06 23:36:02: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/unknown 12/1/1 = &sum;14/50, started new job                
2025-05-06 23:36:22: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 12/2 = &sum;14/50, eval start                               
2025-05-06 23:36:40: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 12/2 = &sum;14/50, starting new job                         
2025-05-06 23:37:01: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 14/1 = &sum;15/50, started new job                          
2025-05-06 23:37:20: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 14/1 = &sum;15/50, eval start                               
2025-05-06 23:37:38: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 14/1 = &sum;15/50, starting new job                         
2025-05-06 23:38:00: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/unknown 14/1/1 = &sum;16/50, started new job                
2025-05-06 23:38:20: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 15/1 = &sum;16/50, eval start                               
2025-05-06 23:38:41: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 15/1 = &sum;16/50, starting new job                         
2025-05-06 23:39:01: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/unknown 15/1/1 = &sum;17/50, started new job                
2025-05-06 23:39:20: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 16/1 = &sum;17/50, eval start                               
2025-05-06 23:39:39: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 16/1 = &sum;17/50, starting new job                         
2025-05-06 23:39:56: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/unknown 16/1/1 = &sum;18/50, started new job                
2025-05-06 23:40:13: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 17/1 = &sum;18/50, eval start                               
2025-05-06 23:40:30: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 17/1 = &sum;18/50, starting new job                         
2025-05-06 23:40:48: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 18/1 = &sum;19/50, started new job                          
2025-05-06 23:41:06: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 18/1 = &sum;19/50, eval start                               
2025-05-06 23:41:22: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 18/1 = &sum;19/50, starting new job                         
2025-05-06 23:41:41: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/unknown 18/1/1 = &sum;20/50, started new job                
2025-05-06 23:41:59: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 19/1 = &sum;20/50, eval start                               
2025-05-06 23:42:15: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 19/1 = &sum;20/50, starting new job                         
2025-05-06 23:42:33: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 20/1 = &sum;21/50, started new job                          
2025-05-06 23:42:51: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 20/1 = &sum;21/50, eval start                               
2025-05-06 23:43:09: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 20/1 = &sum;21/50, starting new job                         
2025-05-06 23:43:27: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 21/1 = &sum;22/50, started new job                          
2025-05-06 23:43:43: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 21/1 = &sum;22/50, eval start                               
2025-05-06 23:44:01: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 21/1 = &sum;22/50, starting new job                         
2025-05-06 23:44:20: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 22/1 = &sum;23/50, started new job                          
2025-05-06 23:44:37: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 22/1 = &sum;23/50, eval start                               
2025-05-06 23:44:54: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 22/1 = &sum;23/50, starting new job                         
2025-05-06 23:45:12: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 23/1 = &sum;24/50, started new job                          
2025-05-06 23:45:29: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 23/1 = &sum;24/50, eval start                               
2025-05-06 23:45:45: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 23/1 = &sum;24/50, starting new job                         
2025-05-06 23:46:02: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 24/1 = &sum;25/50, started new job                          
2025-05-06 23:46:19: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 24/1 = &sum;25/50, eval start                               
2025-05-06 23:46:37: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 24/1 = &sum;25/50, starting new job                         
2025-05-06 23:46:54: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 25/1 = &sum;26/50, started new job                          
2025-05-06 23:47:11: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 25/1 = &sum;26/50, eval start                               
2025-05-06 23:47:28: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 25/1 = &sum;26/50, starting new job                         
2025-05-06 23:47:46: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/unknown 25/1/1 = &sum;27/50, started new job                
2025-05-06 23:48:04: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 26/1 = &sum;27/50, eval start                               
2025-05-06 23:48:20: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 26/1 = &sum;27/50, starting new job                         
2025-05-06 23:48:38: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 27/1 = &sum;28/50, started new job                          
2025-05-06 23:48:54: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 27/1 = &sum;28/50, eval start                               
2025-05-06 23:49:11: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 27/1 = &sum;28/50, starting new job                         
2025-05-06 23:49:28: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/unknown 27/1/1 = &sum;29/50, started new job                
2025-05-06 23:49:44: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 28/1 = &sum;29/50, eval start                               
2025-05-06 23:50:01: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 28/1 = &sum;29/50, starting new job                         
2025-05-06 23:50:19: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 29/1 = &sum;30/50, started new job                          
2025-05-06 23:50:36: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 29/1 = &sum;30/50, eval start                               
2025-05-06 23:50:54: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 29/1 = &sum;30/50, starting new job                         
2025-05-06 23:51:12: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 30/1 = &sum;31/50, started new job                          
2025-05-06 23:51:29: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 30/1 = &sum;31/50, eval start                               
2025-05-06 23:51:46: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 30/1 = &sum;31/50, starting new job                         
2025-05-06 23:52:05: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 31/1 = &sum;32/50, started new job                          
2025-05-06 23:52:22: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 31/1 = &sum;32/50, eval start                               
2025-05-06 23:52:39: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 31/1 = &sum;32/50, starting new job                         
2025-05-06 23:52:57: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 32/1 = &sum;33/50, started new job                          
2025-05-06 23:53:15: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 32/1 = &sum;33/50, eval start                               
2025-05-06 23:53:32: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 32/1 = &sum;33/50, starting new job                         
2025-05-06 23:53:50: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 33/1 = &sum;34/50, started new job                          
2025-05-06 23:54:08: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 33/1 = &sum;34/50, eval start                               
2025-05-06 23:54:26: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 33/1 = &sum;34/50, starting new job                         
2025-05-06 23:54:52: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 34/1 = &sum;35/50, started new job                          
2025-05-06 23:55:10: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 34/1 = &sum;35/50, eval start                               
2025-05-06 23:55:28: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 34/1 = &sum;35/50, starting new job                         
2025-05-06 23:55:48: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 35/1 = &sum;36/50, started new job                          
2025-05-06 23:56:06: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 35/1 = &sum;36/50, eval start                               
2025-05-06 23:56:26: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 35/1 = &sum;36/50, starting new job                         
2025-05-06 23:56:46: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 36/1 = &sum;37/50, started new job                          
2025-05-06 23:57:06: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 36/1 = &sum;37/50, eval start                               
2025-05-06 23:57:25: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 36/1 = &sum;37/50, starting new job                         
2025-05-06 23:57:46: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/unknown 36/1/1 = &sum;38/50, started new job                
2025-05-06 23:58:04: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 37/1 = &sum;38/50, eval start                               
2025-05-06 23:58:22: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 37/1 = &sum;38/50, starting new job                         
2025-05-06 23:58:41: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 38/1 = &sum;39/50, started new job                          
2025-05-06 23:59:00: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 38/1 = &sum;39/50, eval start                               
2025-05-06 23:59:18: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 38/1 = &sum;39/50, starting new job                         
2025-05-06 23:59:38: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/unknown 38/1/1 = &sum;40/50, started new job                
2025-05-06 23:59:57: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 39/1 = &sum;40/50, eval start                               
2025-05-07 00:00:16: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 39/1 = &sum;40/50, starting new job                         
2025-05-07 00:00:36: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 40/1 = &sum;41/50, started new job                          
2025-05-07 00:00:55: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 40/1 = &sum;41/50, eval start                               
2025-05-07 00:01:15: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 40/1 = &sum;41/50, starting new job                         
2025-05-07 00:01:35: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/unknown 40/1/1 = &sum;42/50, started new job                
2025-05-07 00:01:55: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 41/1 = &sum;42/50, eval start                               
2025-05-07 00:02:14: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 41/1 = &sum;42/50, starting new job                         
2025-05-07 00:02:34: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 42/1 = &sum;43/50, started new job                          
2025-05-07 00:02:54: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 42/1 = &sum;43/50, eval start                               
2025-05-07 00:03:13: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 42/1 = &sum;43/50, starting new job                         
2025-05-07 00:03:33: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 43/1 = &sum;44/50, started new job                          
2025-05-07 00:03:52: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 43/1 = &sum;44/50, eval start                               
2025-05-07 00:04:12: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 43/1 = &sum;44/50, starting new job                         
2025-05-07 00:04:32: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 44/1 = &sum;45/50, started new job                          
2025-05-07 00:04:51: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 44/1 = &sum;45/50, eval start                               
2025-05-07 00:05:11: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 44/1 = &sum;45/50, starting new job                         
2025-05-07 00:05:32: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/unknown 44/1/1 = &sum;46/50, started new job                
2025-05-07 00:05:51: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 45/1 = &sum;46/50, eval start                               
2025-05-07 00:06:10: BoTorchModel, best RESULT: 0.1842105263157895, completed/running 45/1 = &sum;46/50, starting new job                         
2025-05-07 00:06:31: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/unknown 45/1/1 = &sum;47/50, started new job                
2025-05-07 00:06:50: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 46/1 = &sum;47/50, eval start                               
2025-05-07 00:07:10: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 46/1 = &sum;47/50, starting new job                         
2025-05-07 00:07:31: BoTorchModel, best RESULT: 0.1842105263157895, completed/unknown 47/1 = &sum;48/50, started new job                          
2025-05-07 00:07:51: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 47/1 = &sum;48/50, eval start                               
2025-05-07 00:08:10: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 47/1 = &sum;48/50, starting new job                         
2025-05-07 00:08:30: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/unknown 47/1/1 = &sum;49/50, started new job                
2025-05-07 00:08:50: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 48/1 = &sum;49/50, eval start                               
2025-05-07 00:09:10: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 48/1 = &sum;49/50, starting new job                         
2025-05-07 00:09:31: BoTorchModel, best RESULT: 0.1842105263157895, completed/running/unknown 48/1/1 = &sum;50/50, started new job                
2025-05-07 00:09:50: BoTorchModel, best RESULT: 0.1842105263157895, completed/pending 49/1 = &sum;50/50, new result: 0.35789473684210527          
</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>True                                                                                                                                                     </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>
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</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>
			<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>
<pre id="pre_tab_main_worker_cpu_ram">timestamp,ram_usage_mb,cpu_usage_percent
1746533465,619.28515625,34.3
1746533469,619.54296875,36.5
1746533473,619.54296875,35.2
1746533473,619.54296875,31.8
1746533473,619.54296875,28.0
1746533473,619.54296875,33.6
1746533473,619.54296875,48.4
1746535280,641.20703125,35.4
1746535280,641.20703125,28.0
1746535280,641.20703125,37.0
1746538443,699.9921875,42.6
1746538443,699.9921875,34.0
1746538443,699.9921875,32.6
1746538443,699.9921875,39.4
1746545977,714.21484375,33.6
1746545977,714.21484375,38.6
1746545977,714.21484375,39.1
1746545977,714.21484375,33.3
1746553154,731.48828125,37.6
1746553154,731.48828125,50.0
1746553154,731.48828125,37.5
1746553154,731.48828125,50.0
1746558812,758.86328125,39.7
1746558812,758.86328125,43.6
1746558812,758.86328125,40.3
1746558812,758.86328125,36.4
1746564851,788.62890625,39.4
1746564851,788.62890625,43.3
1746564851,788.62890625,38.3
1746564851,788.62890625,40.9
</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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