Experiment overview
| Setting | Value |
|---|
| Model for non-random steps | BOTORCH_MODULAR |
| Max. nr. evaluations | 1000 |
| Number random steps | 20 |
| Nr. of workers (parameter) | 20 |
| Main process memory (GB) | 20 |
| Worker memory (GB) | 40 |
Job Summary per Generation Node
| Generation Node | Total | ABANDONED | COMPLETED | FAILED |
| SOBOL | 20 | 0 | 20 | 0 |
| BOTORCH_MODULAR | 420 | 18 | 401 | 1 |
Experiment parameters
| Name | Type | Lower bound | Upper bound | Type | Log Scale? |
|---|
| epochs | range | 20 | 500 | int | No |
| lr | range | 0.0001 | 0.001 | float | No |
| batch_size | range | 64 | 1024 | int | No |
| hidden_size | range | 512 | 4096 | int | No |
| dropout | range | 0 | 0.5 | float | No |
| num_dense_layers | range | 1 | 2 | int | No |
| filter | range | 16 | 128 | int | No |
| num_conv_layers | range | 5 | 7 | int | No |
Number of evaluations
| Failed |
Succeeded |
Running |
Total |
| 1 |
421 |
0 |
440 |
Result names and types
Last progressbar status
2025-11-03 16:42:11 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 1 = ∑1/20, new result: VAL_ACC: 71.350000
Git-Version
Commit: c1217b1a9c6e5acc72d24e212b400662a8b501db (8996)
trial_index,submit_time,queue_time,worker_generator_uuid,start_time,end_time,run_time,program_string,exit_code,signal,hostname,OO_Info_SLURM_JOB_ID,arm_name,trial_status,generation_node,VAL_ACC,epochs,lr,batch_size,hidden_size,dropout,num_dense_layers,filter,num_conv_layers
0,1762015304,77,21991ec7-24fc-46c4-9def-2d379a567e83,1762015381,1762017808,2427,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 236 --learning_rate 0.00099073007106781005 --batch_size 437 --hidden_size 1567 --dropout 0.32740387320518493652 --num_dense_layers 2 --filter 30 --num_conv_layers 7,0,,c136,1207684,0_0,COMPLETED,SOBOL,52.799999999999997157829056959599,236,0.000990730071067810053042634877,437,1567,0.3274038732051849365234375,2,30,7
1,1762015303,29,21991ec7-24fc-46c4-9def-2d379a567e83,1762015332,1762019780,4448,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 405 --learning_rate 0.00023129228139296174 --batch_size 573 --hidden_size 2952 --dropout 0.17578541673719882965 --num_dense_layers 1 --filter 120 --num_conv_layers 6,0,,c141,1207672,1_0,COMPLETED,SOBOL,60.939999999999997726263245567679,405,0.000231292281392961741447872326,573,2952,0.17578541673719882965087890625,1,120,6
2,1762015303,39,21991ec7-24fc-46c4-9def-2d379a567e83,1762015342,1762019584,4242,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 353 --learning_rate 0.00073059595599770549 --batch_size 132 --hidden_size 826 --dropout 0.03931474918499588966 --num_dense_layers 1 --filter 53 --num_conv_layers 5,0,,c139,1207676,2_0,COMPLETED,SOBOL,62.229999999999996873611962655559,353,0.000730595955997705485095161659,132,826,0.039314749184995889663696289062,1,53,5
3,1762015304,58,21991ec7-24fc-46c4-9def-2d379a567e83,1762015362,1762015904,542,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 49 --learning_rate 0.00047740840269252653 --batch_size 990 --hidden_size 3919 --dropout 0.45606138324365019798 --num_dense_layers 2 --filter 85 --num_conv_layers 6,0,,c138,1207680,3_0,COMPLETED,SOBOL,57.880000000000002557953848736361,49,0.000477408402692526534754485779,990,3919,0.456061383243650197982788085938,2,85,6
4,1762015303,39,21991ec7-24fc-46c4-9def-2d379a567e83,1762015342,1762016384,1042,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 94 --learning_rate 0.00063738108072429901 --batch_size 769 --hidden_size 3516 --dropout 0.42674326198175549507 --num_dense_layers 2 --filter 72 --num_conv_layers 5,0,,c139,1207675,4_0,COMPLETED,SOBOL,59.479999999999996873611962655559,94,0.000637381080724299005357824655,769,3516,0.426743261981755495071411132812,2,72,5
5,1762015303,13,21991ec7-24fc-46c4-9def-2d379a567e83,1762015316,1762018728,3412,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 308 --learning_rate 0.00032805510396137841 --batch_size 420 --hidden_size 1235 --dropout 0.07788012875244021416 --num_dense_layers 1 --filter 94 --num_conv_layers 7,0,,c143,1207670,5_0,COMPLETED,SOBOL,59,308,0.00032805510396137840811725539,420,1235,0.077880128752440214157104492188,1,94,7
6,1762015303,41,21991ec7-24fc-46c4-9def-2d379a567e83,1762015344,1762019815,4471,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 451 --learning_rate 0.00085531726703047756 --batch_size 824 --hidden_size 2467 --dropout 0.20701970811933279037 --num_dense_layers 1 --filter 22 --num_conv_layers 7,0,,c139,1207677,6_0,COMPLETED,SOBOL,47.78000000000000113686837721616,451,0.000855317267030477560579848628,824,2467,0.207019708119332790374755859375,1,22,7
7,1762015303,59,21991ec7-24fc-46c4-9def-2d379a567e83,1762015362,1762017672,2310,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 191 --learning_rate 0.00015224107904359698 --batch_size 237 --hidden_size 2062 --dropout 0.28979146480560302734 --num_dense_layers 2 --filter 101 --num_conv_layers 5,0,,c138,1207682,7_0,COMPLETED,SOBOL,61.42000000000000170530256582424,191,0.00015224107904359697983343036,237,2062,0.28979146480560302734375,2,101,5
8,1762015303,53,21991ec7-24fc-46c4-9def-2d379a567e83,1762015356,1762016798,1442,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 142 --learning_rate 0.00066451374134048828 --batch_size 901 --hidden_size 985 --dropout 0.14608055306598544121 --num_dense_layers 2 --filter 60 --num_conv_layers 5,0,,c139,1207678,8_0,COMPLETED,SOBOL,59.03000000000000113686837721616,142,0.000664513741340488277124787242,901,985,0.146080553065985441207885742188,2,60,5
9,1762015304,58,21991ec7-24fc-46c4-9def-2d379a567e83,1762015362,1762021043,5681,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 499 --learning_rate 0.00052393756173551079 --batch_size 288 --hidden_size 3270 --dropout 0.35823730425909161568 --num_dense_layers 1 --filter 90 --num_conv_layers 6,0,,c138,1207681,9_0,COMPLETED,SOBOL,64.32999999999999829469743417576,499,0.000523937561735510789855119196,288,3270,0.358237304259091615676879882812,1,90,6
10,1762015303,73,21991ec7-24fc-46c4-9def-2d379a567e83,1762015376,1762018001,2625,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 267 --learning_rate 0.00093870668681338436 --batch_size 718 --hidden_size 2259 --dropout 0.48690398037433624268 --num_dense_layers 1 --filter 26 --num_conv_layers 7,0,,c136,1207683,10_0,COMPLETED,SOBOL,50.520000000000003126388037344441,267,0.000938706686813384357480349873,718,2259,0.48690398037433624267578125,1,26,7
11,1762015303,88,21991ec7-24fc-46c4-9def-2d379a567e83,1762015391,1762016936,1545,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 135 --learning_rate 0.00029188072513788941 --batch_size 344 --hidden_size 2667 --dropout 0.00960189756006002426 --num_dense_layers 2 --filter 112 --num_conv_layers 6,0,,c133,1207686,11_0,COMPLETED,SOBOL,59.28999999999999914734871708788,135,0.000291880725137889408815627945,344,2667,0.009601897560060024261474609375,2,112,6
12,1762015303,13,21991ec7-24fc-46c4-9def-2d379a567e83,1762015316,1762016151,835,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 60 --learning_rate 0.00079286287417635324 --batch_size 92 --hidden_size 3147 --dropout 0.10757819749414920807 --num_dense_layers 2 --filter 42 --num_conv_layers 7,0,,c143,1207671,12_0,COMPLETED,SOBOL,57.14000000000000056843418860808,60,0.000792862874176353238896142184,92,3147,0.10757819749414920806884765625,2,42,7
13,1762015303,28,21991ec7-24fc-46c4-9def-2d379a567e83,1762015331,1762019067,3736,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 342 --learning_rate 0.00020217532925307752 --batch_size 917 --hidden_size 1759 --dropout 0.39591639954596757889 --num_dense_layers 1 --filter 124 --num_conv_layers 6,0,,c140,1207674,13_0,COMPLETED,SOBOL,55.909999999999996589394868351519,342,0.000202175329253077515085507132,917,1759,0.395916399545967578887939453125,1,124,6
14,1762015303,29,21991ec7-24fc-46c4-9def-2d379a567e83,1762015332,1762019784,4452,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 424 --learning_rate 0.00058898596586659557 --batch_size 510 --hidden_size 3665 --dropout 0.25894231116399168968 --num_dense_layers 1 --filter 48 --num_conv_layers 5,0,,c141,1207673,14_0,COMPLETED,SOBOL,60.020000000000003126388037344441,424,0.000588985965866595565475216656,510,3665,0.258942311163991689682006835938,1,48,5
15,1762015303,73,21991ec7-24fc-46c4-9def-2d379a567e83,1762015376,1762017681,2305,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 217 --learning_rate 0.00039204820971935986 --batch_size 612 --hidden_size 568 --dropout 0.23673935467377305031 --num_dense_layers 2 --filter 74 --num_conv_layers 6,0,,c134,1207685,15_0,COMPLETED,SOBOL,55.549999999999997157829056959599,217,0.000392048209719359863709847724,612,568,0.236739354673773050308227539062,2,74,6
16,1762015304,58,21991ec7-24fc-46c4-9def-2d379a567e83,1762015362,1762017832,2470,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 208 --learning_rate 0.00057659111171960828 --batch_size 272 --hidden_size 2310 --dropout 0.44128509657457470894 --num_dense_layers 1 --filter 117 --num_conv_layers 5,0,,c138,1207679,16_0,COMPLETED,SOBOL,66.35999999999999943156581139192,208,0.000576591111719608278261828271,272,2310,0.441285096574574708938598632812,1,117,5
17,1762015308,84,21991ec7-24fc-46c4-9def-2d379a567e83,1762015392,1762019680,4288,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 430 --learning_rate 0.0004360286700539291 --batch_size 858 --hidden_size 1930 --dropout 0.05531258834525942802 --num_dense_layers 2 --filter 34 --num_conv_layers 6,0,,c133,1207687,17_0,COMPLETED,SOBOL,49.46999999999999886313162278384,430,0.000436028670053929096571410096,858,1930,0.055312588345259428024291992188,2,34,6
18,1762015318,74,21991ec7-24fc-46c4-9def-2d379a567e83,1762015392,1762019268,3876,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 333 --learning_rate 0.00080864805895835168 --batch_size 327 --hidden_size 3613 --dropout 0.16101425047963857651 --num_dense_layers 2 --filter 81 --num_conv_layers 7,0,,c130,1207689,18_0,COMPLETED,SOBOL,60.71999999999999886313162278384,333,0.000808648058958351683041254621,327,3613,0.161014250479638576507568359375,2,81,7
19,1762015318,79,21991ec7-24fc-46c4-9def-2d379a567e83,1762015397,1762016093,696,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 66 --learning_rate 0.00016183582851663232 --batch_size 675 --hidden_size 1301 --dropout 0.34339538216590881348 --num_dense_layers 1 --filter 55 --num_conv_layers 6,0,,c132,1207688,19_0,COMPLETED,SOBOL,45.6000000000000014210854715202,66,0.000161835828516632319754378622,675,1301,0.3433953821659088134765625,1,55,6
20,1762021103,42,21991ec7-24fc-46c4-9def-2d379a567e83,1762021145,1762025589,4444,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 371 --learning_rate 0.00058385868802003681 --batch_size 277 --hidden_size 3935 --dropout 0.36495190859280446372 --num_dense_layers 1 --filter 114 --num_conv_layers 5,0,,c139,1207742,20_0,COMPLETED,BOTORCH_MODULAR,67.790000000000006252776074688882,371,0.000583858688020036809690482826,277,3935,0.364951908592804463715708607197,1,114,5
21,1762021103,23,21991ec7-24fc-46c4-9def-2d379a567e83,1762021126,1762025548,4422,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 373 --learning_rate 0.00058363328266948164 --batch_size 280 --hidden_size 2379 --dropout 0.36517195099099430955 --num_dense_layers 1 --filter 114 --num_conv_layers 5,0,,c151,1207733,21_0,COMPLETED,BOTORCH_MODULAR,66.310000000000002273736754432321,373,0.000583633282669481640025921365,280,2379,0.365171950990994309549364515988,1,114,5
22,1762021103,44,21991ec7-24fc-46c4-9def-2d379a567e83,1762021147,1762025631,4484,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 371 --learning_rate 0.00058370043476407005 --batch_size 279 --hidden_size 2858 --dropout 0.36699459044968796295 --num_dense_layers 1 --filter 114 --num_conv_layers 5,0,,c139,1207740,22_0,COMPLETED,BOTORCH_MODULAR,66.989999999999994884092302527279,371,0.000583700434764070053526852089,279,2858,0.366994590449687962951941244683,1,114,5
23,1762021103,22,21991ec7-24fc-46c4-9def-2d379a567e83,1762021125,1762025563,4438,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 372 --learning_rate 0.00058379531944994189 --batch_size 279 --hidden_size 2854 --dropout 0.36395457256045582461 --num_dense_layers 1 --filter 114 --num_conv_layers 5,0,,c143,1207734,23_0,COMPLETED,BOTORCH_MODULAR,67.07999999999999829469743417576,372,0.000583795319449941885019128573,279,2854,0.363954572560455824614678022044,1,114,5
24,1762021103,22,21991ec7-24fc-46c4-9def-2d379a567e83,1762021125,1762025670,4545,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 378 --learning_rate 0.00058278902751956584 --batch_size 283 --hidden_size 2887 --dropout 0.35947496119287314364 --num_dense_layers 1 --filter 115 --num_conv_layers 5,0,,c141,1207736,24_0,COMPLETED,BOTORCH_MODULAR,67.409999999999996589394868351519,378,0.000582789027519565842883064732,283,2887,0.359474961192873143644987976586,1,115,5
25,1762021103,27,21991ec7-24fc-46c4-9def-2d379a567e83,1762021130,1762025651,4521,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 372 --learning_rate 0.00058354842386067532 --batch_size 279 --hidden_size 2854 --dropout 0.36552012397329741722 --num_dense_layers 1 --filter 114 --num_conv_layers 5,0,,c143,1207735,25_0,COMPLETED,BOTORCH_MODULAR,67.299999999999997157829056959599,372,0.000583548423860675321943325411,279,2854,0.365520123973297417219185945214,1,114,5
26,1762021103,22,21991ec7-24fc-46c4-9def-2d379a567e83,1762021125,1762025489,4364,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 376 --learning_rate 0.00058389310371592077 --batch_size 282 --hidden_size 839 --dropout 0.35404749045811212405 --num_dense_layers 1 --filter 116 --num_conv_layers 5,0,,c141,1207737,26_0,COMPLETED,BOTORCH_MODULAR,64.959999999999993747223925311118,376,0.000583893103715920768100045013,282,839,0.354047490458112124045442214992,1,116,5
27,1762021104,21,21991ec7-24fc-46c4-9def-2d379a567e83,1762021125,1762025626,4501,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 371 --learning_rate 0.00058431360896501908 --batch_size 279 --hidden_size 3675 --dropout 0.36437047321553522883 --num_dense_layers 1 --filter 114 --num_conv_layers 5,0,,c140,1207738,27_0,COMPLETED,BOTORCH_MODULAR,66.799999999999997157829056959599,371,0.000584313608965019077624847288,279,3675,0.364370473215535228828088065711,1,114,5
28,1762021104,43,21991ec7-24fc-46c4-9def-2d379a567e83,1762021147,1762025465,4318,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 376 --learning_rate 0.00058281111714699472 --batch_size 280 --hidden_size 1032 --dropout 0.35614367309368272219 --num_dense_layers 1 --filter 116 --num_conv_layers 5,0,,c139,1207741,28_0,COMPLETED,BOTORCH_MODULAR,65.14000000000000056843418860808,376,0.000582811117146994715071395277,280,1032,0.356143673093682722186059663727,1,116,5
29,1762021104,51,21991ec7-24fc-46c4-9def-2d379a567e83,1762021155,1762025552,4397,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 372 --learning_rate 0.00058355242357035846 --batch_size 279 --hidden_size 2857 --dropout 0.36482846018504755392 --num_dense_layers 1 --filter 114 --num_conv_layers 5,0,,c138,1207744,29_0,COMPLETED,BOTORCH_MODULAR,66.959999999999993747223925311118,372,0.000583552423570358460777618426,279,2857,0.364828460185047553920867358102,1,114,5
30,1762021104,81,21991ec7-24fc-46c4-9def-2d379a567e83,1762021185,1762025544,4359,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 374 --learning_rate 0.0005837535373254644 --batch_size 281 --hidden_size 1771 --dropout 0.35907592968621154794 --num_dense_layers 1 --filter 115 --num_conv_layers 5,0,,c136,1207748,30_0,COMPLETED,BOTORCH_MODULAR,66.519999999999996020960679743439,374,0.000583753537325464402253649698,281,1771,0.359075929686211547942065180905,1,115,5
31,1762021104,35,21991ec7-24fc-46c4-9def-2d379a567e83,1762021139,1762025631,4492,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 371 --learning_rate 0.00058389020218378707 --batch_size 279 --hidden_size 3063 --dropout 0.3699290346830187981 --num_dense_layers 1 --filter 114 --num_conv_layers 5,0,,c139,1207739,31_0,COMPLETED,BOTORCH_MODULAR,67.39000000000000056843418860808,371,0.000583890202183787068550280264,279,3063,0.369929034683018798101983293236,1,114,5
32,1762021104,57,21991ec7-24fc-46c4-9def-2d379a567e83,1762021161,1762025561,4400,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 372 --learning_rate 0.00058321364629870256 --batch_size 279 --hidden_size 2476 --dropout 0.36645999606141749227 --num_dense_layers 1 --filter 114 --num_conv_layers 5,0,,c138,1207745,32_0,COMPLETED,BOTORCH_MODULAR,66.840000000000003410605131648481,372,0.000583213646298702558835869159,279,2476,0.366459996061417492274614460257,1,114,5
33,1762021104,86,21991ec7-24fc-46c4-9def-2d379a567e83,1762021190,1762025649,4459,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 372 --learning_rate 0.00058393448367626444 --batch_size 280 --hidden_size 2894 --dropout 0.36665391356077686735 --num_dense_layers 1 --filter 114 --num_conv_layers 5,0,,c133,1207750,33_0,COMPLETED,BOTORCH_MODULAR,66.71999999999999886313162278384,372,0.000583934483676264441849579345,280,2894,0.366653913560776867353041552633,1,114,5
34,1762021104,47,21991ec7-24fc-46c4-9def-2d379a567e83,1762021151,1762025574,4423,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 372 --learning_rate 0.00058318770894866506 --batch_size 278 --hidden_size 2777 --dropout 0.36414424218376628684 --num_dense_layers 1 --filter 114 --num_conv_layers 5,0,,c138,1207743,34_0,COMPLETED,BOTORCH_MODULAR,66.700000000000002842170943040401,372,0.000583187708948665057932803091,278,2777,0.364144242183766286835577830061,1,114,5
35,1762021104,81,21991ec7-24fc-46c4-9def-2d379a567e83,1762021185,1762025614,4429,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 372 --learning_rate 0.00058346638375114494 --batch_size 279 --hidden_size 2800 --dropout 0.36547882533745684741 --num_dense_layers 1 --filter 114 --num_conv_layers 5,0,,c134,1207749,35_0,COMPLETED,BOTORCH_MODULAR,67.14000000000000056843418860808,372,0.000583466383751144943015098931,279,2800,0.36547882533745684741077752733,1,114,5
36,1762021104,61,21991ec7-24fc-46c4-9def-2d379a567e83,1762021165,1762025661,4496,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 371 --learning_rate 0.000583602940340591 --batch_size 278 --hidden_size 3274 --dropout 0.36528625254210783657 --num_dense_layers 1 --filter 114 --num_conv_layers 5,0,,c138,1207746,36_0,COMPLETED,BOTORCH_MODULAR,67.159999999999996589394868351519,371,0.000583602940340590997832237452,278,3274,0.365286252542107836571716461549,1,114,5
37,1762021104,61,21991ec7-24fc-46c4-9def-2d379a567e83,1762021165,1762025558,4393,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 372 --learning_rate 0.00058373109835325814 --batch_size 279 --hidden_size 2852 --dropout 0.36539107528107561684 --num_dense_layers 1 --filter 114 --num_conv_layers 5,0,,c136,1207747,37_0,COMPLETED,BOTORCH_MODULAR,67.129999999999995452526491135359,372,0.00058373109835325814008510914,279,2852,0.365391075281075616842940689821,1,114,5
38,1762021104,81,21991ec7-24fc-46c4-9def-2d379a567e83,1762021185,1762025604,4419,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 372 --learning_rate 0.00058341894598586878 --batch_size 279 --hidden_size 2851 --dropout 0.36608821660528856334 --num_dense_layers 1 --filter 114 --num_conv_layers 5,0,,c133,1207751,38_0,COMPLETED,BOTORCH_MODULAR,66.989999999999994884092302527279,372,0.000583418945985868784599726045,279,2851,0.366088216605288563343378882564,1,114,5
39,1762021109,96,21991ec7-24fc-46c4-9def-2d379a567e83,1762021205,1762025636,4431,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 373 --learning_rate 0.00058335169967330743 --batch_size 280 --hidden_size 2032 --dropout 0.36299026885931540143 --num_dense_layers 1 --filter 115 --num_conv_layers 5,0,,c130,1207752,39_0,COMPLETED,BOTORCH_MODULAR,66.159999999999996589394868351519,373,0.000583351699673307429357127507,280,2032,0.362990268859315401428489167301,1,115,5
40,1762025748,45,21991ec7-24fc-46c4-9def-2d379a567e83,1762025793,1762029938,4145,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 267 --learning_rate 0.00038471065267915131 --batch_size 64 --hidden_size 3123 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c139,1207870,40_0,COMPLETED,BOTORCH_MODULAR,69.870000000000004547473508864641,267,0.000384710652679151306546079248,64,3123,0.5,1,128,5
41,1762025748,5,21991ec7-24fc-46c4-9def-2d379a567e83,1762025753,1762033855,8102,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00040364968474751949 --batch_size 64 --hidden_size 3974 --dropout 0.5 --num_dense_layers 1 --filter 122 --num_conv_layers 5,0,,c151,1207863,41_0,COMPLETED,BOTORCH_MODULAR,69.569999999999993178789736703038,500,0.000403649684747519493267786661,64,3974,0.5,1,122,5
42,1762025748,22,21991ec7-24fc-46c4-9def-2d379a567e83,1762025770,1762033839,8069,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00040109710797169051 --batch_size 64 --hidden_size 4096 --dropout 0.5 --num_dense_layers 1 --filter 123 --num_conv_layers 5,0,,c141,1207867,42_0,COMPLETED,BOTORCH_MODULAR,69.659999999999996589394868351519,500,0.000401097107971690506299233814,64,4096,0.5,1,123,5
43,1762025748,23,21991ec7-24fc-46c4-9def-2d379a567e83,1762025771,1762033867,8096,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00040752476731972012 --batch_size 64 --hidden_size 4096 --dropout 0.5 --num_dense_layers 1 --filter 121 --num_conv_layers 5,0,,c140,1207868,43_0,COMPLETED,BOTORCH_MODULAR,69.950000000000002842170943040401,500,0.000407524767319720115834463803,64,4096,0.5,1,121,5
44,1762025748,5,21991ec7-24fc-46c4-9def-2d379a567e83,1762025753,1762033814,8061,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00040769505439906996 --batch_size 64 --hidden_size 4096 --dropout 0.5 --num_dense_layers 1 --filter 123 --num_conv_layers 5,0,,c143,1207864,44_0,COMPLETED,BOTORCH_MODULAR,70.230000000000003979039320256561,500,0.000407695054399069957504903039,64,4096,0.5,1,123,5
45,1762025748,22,21991ec7-24fc-46c4-9def-2d379a567e83,1762025770,1762033942,8172,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00041032644093742679 --batch_size 64 --hidden_size 4096 --dropout 0.5 --num_dense_layers 1 --filter 122 --num_conv_layers 5,0,,c143,1207865,45_0,COMPLETED,BOTORCH_MODULAR,70.32999999999999829469743417576,500,0.00041032644093742679045760946,64,4096,0.5,1,122,5
46,1762025748,68,21991ec7-24fc-46c4-9def-2d379a567e83,1762025816,1762033895,8079,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00039981832030838851 --batch_size 64 --hidden_size 4096 --dropout 0.5 --num_dense_layers 1 --filter 123 --num_conv_layers 5,0,,c138,1207876,46_0,COMPLETED,BOTORCH_MODULAR,69.939999999999997726263245567679,500,0.0003998183203083885092245231,64,4096,0.5,1,123,5
47,1762025748,46,21991ec7-24fc-46c4-9def-2d379a567e83,1762025794,1762033775,7981,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00041409175686233984 --batch_size 64 --hidden_size 4096 --dropout 0.5 --num_dense_layers 1 --filter 121 --num_conv_layers 5,0,,c139,1207872,47_0,COMPLETED,BOTORCH_MODULAR,69.540000000000006252776074688882,500,0.000414091756862339840233877553,64,4096,0.5,1,121,5
48,1762025749,44,21991ec7-24fc-46c4-9def-2d379a567e83,1762025793,1762033715,7922,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00039340010658546677 --batch_size 64 --hidden_size 3762 --dropout 0.5 --num_dense_layers 1 --filter 124 --num_conv_layers 5,0,,c139,1207869,48_0,COMPLETED,BOTORCH_MODULAR,70.430000000000006821210263296962,500,0.000393400106585466765186237525,64,3762,0.5,1,124,5
49,1762025748,68,21991ec7-24fc-46c4-9def-2d379a567e83,1762025816,1762033827,8011,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00040466946537188033 --batch_size 64 --hidden_size 4096 --dropout 0.5 --num_dense_layers 1 --filter 122 --num_conv_layers 5,0,,c138,1207874,49_0,COMPLETED,BOTORCH_MODULAR,69.900000000000005684341886080801,500,0.000404669465371880325045561566,64,4096,0.5,1,122,5
50,1762025748,68,21991ec7-24fc-46c4-9def-2d379a567e83,1762025816,1762033727,7911,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00040022453257459285 --batch_size 64 --hidden_size 4096 --dropout 0.5 --num_dense_layers 1 --filter 124 --num_conv_layers 5,0,,c138,1207875,50_0,COMPLETED,BOTORCH_MODULAR,70.620000000000004547473508864641,500,0.000400224532574592847290750885,64,4096,0.5,1,124,5
51,1762025749,63,21991ec7-24fc-46c4-9def-2d379a567e83,1762025812,1762033663,7851,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00039463109349426029 --batch_size 64 --hidden_size 4096 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c136,1207877,51_0,COMPLETED,BOTORCH_MODULAR,70.189999999999997726263245567679,500,0.00039463109349426029031498997,64,4096,0.5,1,128,5
52,1762025749,81,21991ec7-24fc-46c4-9def-2d379a567e83,1762025830,1762032496,6666,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 456 --learning_rate 0.00040464834120117091 --batch_size 94 --hidden_size 3996 --dropout 0.5 --num_dense_layers 1 --filter 125 --num_conv_layers 5,0,,c133,1207880,52_0,COMPLETED,BOTORCH_MODULAR,69.25,456,0.000404648341201170906253348214,94,3996,0.5,1,125,5
53,1762025749,44,21991ec7-24fc-46c4-9def-2d379a567e83,1762025793,1762033852,8059,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00040679091101349118 --batch_size 64 --hidden_size 4096 --dropout 0.5 --num_dense_layers 1 --filter 122 --num_conv_layers 5,0,,c139,1207871,53_0,COMPLETED,BOTORCH_MODULAR,70.10999999999999943156581139192,500,0.000406790911013491180217571674,64,4096,0.5,1,122,5
54,1762025749,21,21991ec7-24fc-46c4-9def-2d379a567e83,1762025770,1762032304,6534,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 437 --learning_rate 0.00040710611948915415 --batch_size 83 --hidden_size 3843 --dropout 0.5 --num_dense_layers 1 --filter 123 --num_conv_layers 5,0,,c141,1207866,54_0,COMPLETED,BOTORCH_MODULAR,69.57999999999999829469743417576,437,0.000407106119489154154918869599,83,3843,0.5,1,123,5
55,1762025749,69,21991ec7-24fc-46c4-9def-2d379a567e83,1762025818,1762033852,8034,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00039682383000012406 --batch_size 64 --hidden_size 4096 --dropout 0.5 --num_dense_layers 1 --filter 123 --num_conv_layers 5,0,,c138,1207873,55_0,COMPLETED,BOTORCH_MODULAR,70.090000000000003410605131648481,500,0.00039682383000012405550524508,64,4096,0.5,1,123,5
56,1762025749,81,21991ec7-24fc-46c4-9def-2d379a567e83,1762025830,1762033837,8007,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00040929935055641475 --batch_size 64 --hidden_size 4096 --dropout 0.5 --num_dense_layers 1 --filter 122 --num_conv_layers 5,0,,c136,1207878,56_0,COMPLETED,BOTORCH_MODULAR,69.650000000000005684341886080801,500,0.000409299350556414746893363343,64,4096,0.5,1,122,5
57,1762025749,81,21991ec7-24fc-46c4-9def-2d379a567e83,1762025830,1762033910,8080,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00040290890463716043 --batch_size 64 --hidden_size 4096 --dropout 0.5 --num_dense_layers 1 --filter 122 --num_conv_layers 5,0,,c134,1207879,57_0,COMPLETED,BOTORCH_MODULAR,70.25,500,0.000402908904637160427721076505,64,4096,0.5,1,122,5
58,1762025759,83,21991ec7-24fc-46c4-9def-2d379a567e83,1762025842,1762032605,6763,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 436 --learning_rate 0.00038394572136365925 --batch_size 64 --hidden_size 3030 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c133,1207881,58_0,COMPLETED,BOTORCH_MODULAR,70.269999999999996020960679743439,436,0.000383945721363659247041266731,64,3030,0.5,1,128,5
59,1762025759,84,21991ec7-24fc-46c4-9def-2d379a567e83,1762025843,1762033958,8115,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00040505601570736108 --batch_size 64 --hidden_size 4096 --dropout 0.5 --num_dense_layers 1 --filter 123 --num_conv_layers 5,0,,c130,1207882,59_0,COMPLETED,BOTORCH_MODULAR,69.959999999999993747223925311118,500,0.00040505601570736107699260975,64,4096,0.5,1,123,5
60,1762034035,22,21991ec7-24fc-46c4-9def-2d379a567e83,1762034057,1762041586,7529,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00080699774887886815 --batch_size 64 --hidden_size 3716 --dropout 0.16232354821168618053 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c147,1208023,60_0,COMPLETED,BOTORCH_MODULAR,68.349999999999994315658113919199,500,0.000806997748878868150120002856,64,3716,0.162323548211686180531287959639,1,128,6
61,1762034035,22,21991ec7-24fc-46c4-9def-2d379a567e83,1762034057,1762041640,7583,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00079750185494473593 --batch_size 64 --hidden_size 3718 --dropout 0.13427544717529393825 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c141,1208026,61_0,COMPLETED,BOTORCH_MODULAR,68.209999999999993747223925311118,500,0.000797501854944735930584565065,64,3718,0.134275447175293938251172676246,1,128,6
62,1762034035,21,21991ec7-24fc-46c4-9def-2d379a567e83,1762034056,1762041569,7513,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00080835882793821789 --batch_size 64 --hidden_size 3734 --dropout 0.1501686530673137232 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c143,1208024,62_0,COMPLETED,BOTORCH_MODULAR,68.489999999999994884092302527279,500,0.000808358827938217890801686494,64,3734,0.150168653067313723203923814253,1,128,6
63,1762034035,21,21991ec7-24fc-46c4-9def-2d379a567e83,1762034056,1762041540,7484,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00080208322506244317 --batch_size 64 --hidden_size 3710 --dropout 0.1446049578504228772 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c140,1208028,63_0,COMPLETED,BOTORCH_MODULAR,68.07999999999999829469743417576,500,0.00080208322506244316731083277,64,3710,0.144604957850422877196905346864,1,128,6
64,1762034035,22,21991ec7-24fc-46c4-9def-2d379a567e83,1762034057,1762041601,7544,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00080852417425092101 --batch_size 64 --hidden_size 3723 --dropout 0.1738937757012072316 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c151,1208022,64_0,COMPLETED,BOTORCH_MODULAR,68.840000000000003410605131648481,500,0.000808524174250921010519144172,64,3723,0.173893775701207231598743874201,1,128,6
65,1762034036,20,21991ec7-24fc-46c4-9def-2d379a567e83,1762034056,1762041671,7615,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00079962562564646063 --batch_size 64 --hidden_size 3712 --dropout 0.15507929479828080899 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c139,1208029,65_0,COMPLETED,BOTORCH_MODULAR,68.629999999999995452526491135359,500,0.00079962562564646062594764242,64,3712,0.155079294798280808986845613617,1,128,6
66,1762034035,21,21991ec7-24fc-46c4-9def-2d379a567e83,1762034056,1762041643,7587,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00079795016052841181 --batch_size 64 --hidden_size 3722 --dropout 0.14363881474835660246 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c141,1208027,66_0,COMPLETED,BOTORCH_MODULAR,68.989999999999994884092302527279,500,0.00079795016052841181378868507,64,3722,0.143638814748356602457590724953,1,128,6
67,1762034035,22,21991ec7-24fc-46c4-9def-2d379a567e83,1762034057,1762041679,7622,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00080926391890408819 --batch_size 64 --hidden_size 3725 --dropout 0.15992243373718018074 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c143,1208025,67_0,COMPLETED,BOTORCH_MODULAR,68.700000000000002842170943040401,500,0.000809263918904088190228729438,64,3725,0.159922433737180180735037993145,1,128,6
68,1762034036,47,21991ec7-24fc-46c4-9def-2d379a567e83,1762034083,1762041569,7486,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00081046655964596903 --batch_size 64 --hidden_size 3714 --dropout 0.16175453521778504484 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c138,1208032,68_0,COMPLETED,BOTORCH_MODULAR,69.39000000000000056843418860808,500,0.000810466559645969027853018574,64,3714,0.161754535217785044842742081528,1,128,6
69,1762034036,69,21991ec7-24fc-46c4-9def-2d379a567e83,1762034105,1762041654,7549,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00080737636201804581 --batch_size 64 --hidden_size 3714 --dropout 0.16251474950827826671 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c137,1208039,69_0,COMPLETED,BOTORCH_MODULAR,68.549999999999997157829056959599,500,0.000807376362018045806365207362,64,3714,0.16251474950827826670973763612,1,128,6
70,1762034036,45,21991ec7-24fc-46c4-9def-2d379a567e83,1762034081,1762041594,7513,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00080162838090025749 --batch_size 64 --hidden_size 3707 --dropout 0.17713449903821512632 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c138,1208034,70_0,COMPLETED,BOTORCH_MODULAR,69.409999999999996589394868351519,500,0.00080162838090025749157585544,64,3707,0.177134499038215126320849890362,1,128,6
71,1762034036,26,21991ec7-24fc-46c4-9def-2d379a567e83,1762034062,1762041671,7609,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00080179882845631402 --batch_size 64 --hidden_size 3711 --dropout 0.1457459445272862586 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c139,1208030,71_0,COMPLETED,BOTORCH_MODULAR,68.28000000000000113686837721616,500,0.000801798828456314017706918484,64,3711,0.145745944527286258596276979915,1,128,6
72,1762034036,40,21991ec7-24fc-46c4-9def-2d379a567e83,1762034076,1762041553,7477,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00080195542869585358 --batch_size 64 --hidden_size 3738 --dropout 0.13442837201280533055 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c139,1208031,72_0,COMPLETED,BOTORCH_MODULAR,68.209999999999993747223925311118,500,0.000801955428695853584503128175,64,3738,0.1344283720128053305487014768,1,128,6
73,1762034036,69,21991ec7-24fc-46c4-9def-2d379a567e83,1762034105,1762041657,7552,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00080690609031210223 --batch_size 64 --hidden_size 3727 --dropout 0.14591534740396475134 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c137,1208036,73_0,COMPLETED,BOTORCH_MODULAR,68.790000000000006252776074688882,500,0.000806906090312102227193880033,64,3727,0.145915347403964751338278915682,1,128,6
74,1762034036,45,21991ec7-24fc-46c4-9def-2d379a567e83,1762034081,1762041611,7530,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00080754352220471792 --batch_size 64 --hidden_size 3702 --dropout 0.15102173147714229029 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c138,1208033,74_0,COMPLETED,BOTORCH_MODULAR,68.42000000000000170530256582424,500,0.000807543522204717920294492206,64,3702,0.151021731477142290289705783835,1,128,6
75,1762034036,56,21991ec7-24fc-46c4-9def-2d379a567e83,1762034092,1762041630,7538,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00080711970515386371 --batch_size 64 --hidden_size 3712 --dropout 0.15023667960041303671 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c138,1208035,75_0,COMPLETED,BOTORCH_MODULAR,69.340000000000003410605131648481,500,0.000807119705153863708016470646,64,3712,0.150236679600413036705930380776,1,128,6
76,1762034037,68,21991ec7-24fc-46c4-9def-2d379a567e83,1762034105,1762041641,7536,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00082568243027934807 --batch_size 64 --hidden_size 3703 --dropout 0.19007424302981493214 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c137,1208037,76_0,COMPLETED,BOTORCH_MODULAR,69.540000000000006252776074688882,500,0.000825682430279348067436728797,64,3703,0.190074243029814932137711025462,1,128,6
77,1762034037,68,21991ec7-24fc-46c4-9def-2d379a567e83,1762034105,1762041670,7565,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00080101628763651139 --batch_size 64 --hidden_size 3700 --dropout 0.16562646695994151513 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c137,1208038,77_0,COMPLETED,BOTORCH_MODULAR,69.200000000000002842170943040401,500,0.000801016287636511386573145987,64,3700,0.165626466959941515133536427129,1,128,6
78,1762034042,74,21991ec7-24fc-46c4-9def-2d379a567e83,1762034116,1762041691,7575,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.0008217961034376357 --batch_size 64 --hidden_size 3719 --dropout 0.153854415077578216 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c136,1208041,78_0,COMPLETED,BOTORCH_MODULAR,69.060000000000002273736754432321,500,0.000821796103437635698518715088,64,3719,0.153854415077578215997888833044,1,128,6
79,1762034042,79,21991ec7-24fc-46c4-9def-2d379a567e83,1762034121,1762041647,7526,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.0007936112651446964 --batch_size 64 --hidden_size 3705 --dropout 0.16466587571763594 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c136,1208040,79_0,COMPLETED,BOTORCH_MODULAR,68.680000000000006821210263296962,500,0.00079361126514469640218230051,64,3705,0.164665875717635940000960204088,1,128,6
80,1762041792,41,21991ec7-24fc-46c4-9def-2d379a567e83,1762041833,1762049265,7432,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00083478932258899019 --batch_size 64 --hidden_size 3444 --dropout 0.47705461033330937015 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c146,1208123,80_0,COMPLETED,BOTORCH_MODULAR,70.21999999999999886313162278384,500,0.00083478932258899019459158497,64,3444,0.477054610333309370151511075164,1,128,6
81,1762041791,46,21991ec7-24fc-46c4-9def-2d379a567e83,1762041837,1762049391,7554,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00083308205219490635 --batch_size 64 --hidden_size 3416 --dropout 0.47633287081150271769 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c143,1208126,81_0,COMPLETED,BOTORCH_MODULAR,70.340000000000003410605131648481,500,0.0008330820521949063462568974,64,3416,0.476332870811502717689478458851,1,128,6
82,1762041791,25,21991ec7-24fc-46c4-9def-2d379a567e83,1762041816,1762050007,8191,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00083178008357479732 --batch_size 64 --hidden_size 3445 --dropout 0.47514585364285999436 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c147,1208122,82_0,COMPLETED,BOTORCH_MODULAR,70.480000000000003979039320256561,500,0.000831780083574797319059812573,64,3445,0.475145853642859994359071151848,1,128,6
83,1762041791,63,21991ec7-24fc-46c4-9def-2d379a567e83,1762041854,1762049360,7506,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00083592502410680147 --batch_size 64 --hidden_size 3405 --dropout 0.47758298781647551268 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c139,1208132,83_0,COMPLETED,BOTORCH_MODULAR,70.519999999999996020960679743439,500,0.000835925024106801465260951911,64,3405,0.477582987816475512676817061219,1,128,6
84,1762041792,41,21991ec7-24fc-46c4-9def-2d379a567e83,1762041833,1762049675,7842,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00083867190113110271 --batch_size 64 --hidden_size 3429 --dropout 0.47512001989315877371 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c145,1208124,84_0,COMPLETED,BOTORCH_MODULAR,70.53000000000000113686837721616,500,0.000838671901131102714641030182,64,3429,0.475120019893158773705010844424,1,128,6
85,1762041791,62,21991ec7-24fc-46c4-9def-2d379a567e83,1762041853,1762049393,7540,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.000840216332022825 --batch_size 64 --hidden_size 3443 --dropout 0.47862088531946861414 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c141,1208127,85_0,COMPLETED,BOTORCH_MODULAR,70.230000000000003979039320256561,500,0.000840216332022824998609911162,64,3443,0.47862088531946861413857163825,1,128,6
86,1762041791,22,21991ec7-24fc-46c4-9def-2d379a567e83,1762041813,1762049358,7545,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00083477546675005609 --batch_size 64 --hidden_size 3418 --dropout 0.47693267335699218723 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c147,1208121,86_0,COMPLETED,BOTORCH_MODULAR,70.319999999999993178789736703038,500,0.000834775466750056088262310627,64,3418,0.47693267335699218723021886035,1,128,6
87,1762041791,17,21991ec7-24fc-46c4-9def-2d379a567e83,1762041808,1762049450,7642,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00082874960288537079 --batch_size 64 --hidden_size 3440 --dropout 0.47481988163957383753 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c151,1208118,87_0,COMPLETED,BOTORCH_MODULAR,70.370000000000004547473508864641,500,0.000828749602885370793316222038,64,3440,0.47481988163957383752844521041,1,128,6
88,1762041791,62,21991ec7-24fc-46c4-9def-2d379a567e83,1762041853,1762049340,7487,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.0008329353106442867 --batch_size 64 --hidden_size 3428 --dropout 0.47591981872081312588 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c141,1208128,88_0,COMPLETED,BOTORCH_MODULAR,69.85999999999999943156581139192,500,0.000832935310644286695108684526,64,3428,0.475919818720813125878521532286,1,128,6
89,1762041791,12,21991ec7-24fc-46c4-9def-2d379a567e83,1762041803,1762049275,7472,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00083326692246566021 --batch_size 64 --hidden_size 3415 --dropout 0.47613713100908588993 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c151,1208117,89_0,COMPLETED,BOTORCH_MODULAR,70.180000000000006821210263296962,500,0.00083326692246566021454040607,64,3415,0.476137131009085889932208601749,1,128,6
90,1762041792,22,21991ec7-24fc-46c4-9def-2d379a567e83,1762041814,1762050029,8215,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00083574122949297354 --batch_size 64 --hidden_size 3448 --dropout 0.47661714190797849211 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c148,1208120,90_0,COMPLETED,BOTORCH_MODULAR,70.590000000000003410605131648481,500,0.000835741229492973540862732484,64,3448,0.476617141907978492110231627521,1,128,6
91,1762041791,12,21991ec7-24fc-46c4-9def-2d379a567e83,1762041803,1762049268,7465,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00084101274100073574 --batch_size 64 --hidden_size 3454 --dropout 0.47850421021747213679 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c149,1208119,91_0,COMPLETED,BOTORCH_MODULAR,70.900000000000005684341886080801,500,0.000841012741000735737292859362,64,3454,0.478504210217472136790206604928,1,128,6
92,1762041792,41,21991ec7-24fc-46c4-9def-2d379a567e83,1762041833,1762049331,7498,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00083787076654654531 --batch_size 64 --hidden_size 3444 --dropout 0.47493461449220641946 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c143,1208125,92_0,COMPLETED,BOTORCH_MODULAR,70.799999999999997157829056959599,500,0.000837870766546545313671612298,64,3444,0.474934614492206419456010735303,1,128,6
93,1762041791,69,21991ec7-24fc-46c4-9def-2d379a567e83,1762041860,1762049442,7582,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00083460176667003098 --batch_size 64 --hidden_size 3449 --dropout 0.47657190769147378395 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c139,1208131,93_0,COMPLETED,BOTORCH_MODULAR,70.489999999999994884092302527279,500,0.000834601766670030982206429648,64,3449,0.476571907691473783952318399315,1,128,6
94,1762041791,72,21991ec7-24fc-46c4-9def-2d379a567e83,1762041863,1762049397,7534,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00083515866754231484 --batch_size 64 --hidden_size 3409 --dropout 0.47717550145117992866 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c139,1208130,94_0,COMPLETED,BOTORCH_MODULAR,70.340000000000003410605131648481,500,0.000835158667542314843597328622,64,3409,0.477175501451179928658064000047,1,128,6
95,1762041792,67,21991ec7-24fc-46c4-9def-2d379a567e83,1762041859,1762049324,7465,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00083238784503299364 --batch_size 64 --hidden_size 3414 --dropout 0.4762258212363676968 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c139,1208133,95_0,COMPLETED,BOTORCH_MODULAR,70.549999999999997157829056959599,500,0.000832387845032993636817941763,64,3414,0.476225821236367696798197357566,1,128,6
96,1762041794,75,21991ec7-24fc-46c4-9def-2d379a567e83,1762041869,1762049366,7497,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00083512580684220734 --batch_size 64 --hidden_size 3448 --dropout 0.47610693612200738478 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c138,1208134,96_0,COMPLETED,BOTORCH_MODULAR,70.10999999999999943156581139192,500,0.000835125806842207342103878709,64,3448,0.476106936122007384781795735762,1,128,6
97,1762041794,76,21991ec7-24fc-46c4-9def-2d379a567e83,1762041870,1762049494,7624,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00083554520944043725 --batch_size 64 --hidden_size 3444 --dropout 0.47943878596696665184 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c138,1208135,97_0,COMPLETED,BOTORCH_MODULAR,70.39000000000000056843418860808,500,0.000835545209440437253167743847,64,3444,0.479438785966966651841403290746,1,128,6
98,1762041794,59,21991ec7-24fc-46c4-9def-2d379a567e83,1762041853,1762049496,7643,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00083618081167091435 --batch_size 64 --hidden_size 3446 --dropout 0.47707011187333409064 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c140,1208129,98_0,COMPLETED,BOTORCH_MODULAR,69.900000000000005684341886080801,500,0.000836180811670914352247419021,64,3446,0.477070111873334090635268012193,1,128,6
99,1762041803,70,21991ec7-24fc-46c4-9def-2d379a567e83,1762041873,1762049382,7509,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00083361152152431782 --batch_size 64 --hidden_size 3453 --dropout 0.47477790921621726428 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c138,1208136,99_0,COMPLETED,BOTORCH_MODULAR,70.260000000000005115907697472721,500,0.000833611521524317816006499626,64,3453,0.474777909216217264276593823524,1,128,6
100,1762050141,53,21991ec7-24fc-46c4-9def-2d379a567e83,1762050194,1762058058,7864,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00082930370572521501 --batch_size 64 --hidden_size 3618 --dropout 0.404711654089100481 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c139,1208203,100_0,COMPLETED,BOTORCH_MODULAR,71.019999999999996020960679743439,500,0.000829303705725215013419560073,64,3618,0.404711654089100481002105880179,1,128,5
101,1762050140,25,21991ec7-24fc-46c4-9def-2d379a567e83,1762050165,1762057914,7749,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00084184392430466514 --batch_size 64 --hidden_size 3120 --dropout 0.40677436765865682133 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c146,1208196,101_0,COMPLETED,BOTORCH_MODULAR,70.379999999999995452526491135359,500,0.000841843924304665138132197644,64,3120,0.406774367658656821333806874463,1,128,5
102,1762050141,24,21991ec7-24fc-46c4-9def-2d379a567e83,1762050165,1762058734,8569,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00083691737543605059 --batch_size 64 --hidden_size 3621 --dropout 0.40409352483848043347 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c145,1208197,102_0,COMPLETED,BOTORCH_MODULAR,70.989999999999994884092302527279,500,0.000836917375436050585239822208,64,3621,0.404093524838480433469811714531,1,128,5
103,1762050141,43,21991ec7-24fc-46c4-9def-2d379a567e83,1762050184,1762058045,7861,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00082141260858542911 --batch_size 64 --hidden_size 3618 --dropout 0.40308074430659235343 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c141,1208200,103_0,COMPLETED,BOTORCH_MODULAR,70.439999999999997726263245567679,500,0.000821412608585429110386044727,64,3618,0.403080744306592353431994979474,1,128,5
104,1762050140,44,21991ec7-24fc-46c4-9def-2d379a567e83,1762050184,1762058080,7896,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00083189989955872903 --batch_size 64 --hidden_size 3701 --dropout 0.40301620474710836417 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c143,1208199,104_0,COMPLETED,BOTORCH_MODULAR,71.069999999999993178789736703038,500,0.000831899899558729031753823158,64,3701,0.403016204747108364170316008313,1,128,5
105,1762050140,17,21991ec7-24fc-46c4-9def-2d379a567e83,1762050157,1762057892,7735,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00083755036161059049 --batch_size 64 --hidden_size 3626 --dropout 0.40380245034935008386 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c149,1208194,105_0,COMPLETED,BOTORCH_MODULAR,70.60999999999999943156581139192,500,0.000837550361610590486313721037,64,3626,0.403802450349350083858013249483,1,128,5
106,1762050140,24,21991ec7-24fc-46c4-9def-2d379a567e83,1762050164,1762058033,7869,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00082648091533292858 --batch_size 64 --hidden_size 3627 --dropout 0.40461123834339324246 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c143,1208198,106_0,COMPLETED,BOTORCH_MODULAR,70.5,500,0.000826480915332928581414073665,64,3627,0.404611238343393242455903191512,1,128,5
107,1762050140,5,21991ec7-24fc-46c4-9def-2d379a567e83,1762050145,1762058006,7861,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00084655958048345209 --batch_size 64 --hidden_size 3607 --dropout 0.40516712072232019537 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c151,1208193,107_0,COMPLETED,BOTORCH_MODULAR,71.480000000000003979039320256561,500,0.000846559580483452088148221826,64,3607,0.405167120722320195369547946029,1,128,5
108,1762050140,5,21991ec7-24fc-46c4-9def-2d379a567e83,1762050145,1762057926,7781,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00083899837297018759 --batch_size 64 --hidden_size 3619 --dropout 0.40413747709686953513 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c151,1208191,108_0,COMPLETED,BOTORCH_MODULAR,70.75,500,0.000838998372970187590927371168,64,3619,0.404137477096869535131418160745,1,128,5
109,1762050141,24,21991ec7-24fc-46c4-9def-2d379a567e83,1762050165,1762058806,8641,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00084513400041065468 --batch_size 64 --hidden_size 3634 --dropout 0.40328482025935591393 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c148,1208195,109_0,COMPLETED,BOTORCH_MODULAR,70.870000000000004547473508864641,500,0.0008451340004106546810805356,64,3634,0.40328482025935591392951096168,1,128,5
110,1762050141,56,21991ec7-24fc-46c4-9def-2d379a567e83,1762050197,1762058100,7903,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00084336119897257913 --batch_size 64 --hidden_size 3593 --dropout 0.40354933471660220379 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c139,1208204,110_0,COMPLETED,BOTORCH_MODULAR,71.17000000000000170530256582424,500,0.000843361198972579126885429357,64,3593,0.403549334716602203787516600642,1,128,5
111,1762050140,44,21991ec7-24fc-46c4-9def-2d379a567e83,1762050184,1762058033,7849,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00083017509509995412 --batch_size 64 --hidden_size 3626 --dropout 0.40471808832350913976 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c141,1208201,111_0,COMPLETED,BOTORCH_MODULAR,70.959999999999993747223925311118,500,0.000830175095099954115339391247,64,3626,0.404718088323509139758726860236,1,128,5
112,1762050141,53,21991ec7-24fc-46c4-9def-2d379a567e83,1762050194,1762058078,7884,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00083411634479860447 --batch_size 64 --hidden_size 3633 --dropout 0.40498986326476005271 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c139,1208205,112_0,COMPLETED,BOTORCH_MODULAR,70.849999999999994315658113919199,500,0.000834116344798604470757441565,64,3633,0.404989863264760052707913473569,1,128,5
113,1762050142,42,21991ec7-24fc-46c4-9def-2d379a567e83,1762050184,1762058010,7826,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00083010350325523361 --batch_size 64 --hidden_size 3630 --dropout 0.40352311082241842932 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c140,1208202,113_0,COMPLETED,BOTORCH_MODULAR,70.879999999999995452526491135359,500,0.000830103503255233605463703217,64,3630,0.403523110822418429322055999364,1,128,5
114,1762050141,43,21991ec7-24fc-46c4-9def-2d379a567e83,1762050184,1762058006,7822,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00081997671592606706 --batch_size 64 --hidden_size 3642 --dropout 0.40415075326291732827 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c138,1208208,114_0,COMPLETED,BOTORCH_MODULAR,70.480000000000003979039320256561,500,0.000819976715926067057337023325,64,3642,0.404150753262917328267889160998,1,128,5
115,1762050141,4,21991ec7-24fc-46c4-9def-2d379a567e83,1762050145,1762058101,7956,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00083449294567412131 --batch_size 64 --hidden_size 3607 --dropout 0.40399115408976765673 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c151,1208192,115_0,COMPLETED,BOTORCH_MODULAR,70.590000000000003410605131648481,500,0.000834492945674121305507653368,64,3607,0.403991154089767656731879696963,1,128,5
116,1762050144,52,21991ec7-24fc-46c4-9def-2d379a567e83,1762050196,1762057973,7777,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00082630561758354219 --batch_size 64 --hidden_size 3627 --dropout 0.40457022433591077748 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c139,1208206,116_0,COMPLETED,BOTORCH_MODULAR,71.21999999999999886313162278384,500,0.000826305617583542192060297449,64,3627,0.404570224335910777480052047395,1,128,5
117,1762050144,41,21991ec7-24fc-46c4-9def-2d379a567e83,1762050185,1762058062,7877,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00083252555570806743 --batch_size 64 --hidden_size 3604 --dropout 0.40487508845831193804 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c138,1208207,117_0,COMPLETED,BOTORCH_MODULAR,71.400000000000005684341886080801,500,0.000832525555708067428045682234,64,3604,0.404875088458311938044431599337,1,128,5
118,1762050144,60,21991ec7-24fc-46c4-9def-2d379a567e83,1762050204,1762058464,8260,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00084141446517169421 --batch_size 64 --hidden_size 3592 --dropout 0.40532243092640707349 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c138,1208209,118_0,COMPLETED,BOTORCH_MODULAR,71.14000000000000056843418860808,500,0.000841414465171694205165853209,64,3592,0.405322430926407073492612198606,1,128,5
119,1762050147,57,21991ec7-24fc-46c4-9def-2d379a567e83,1762050204,1762058167,7963,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00083194728316496975 --batch_size 64 --hidden_size 3135 --dropout 0.40744259664233650753 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c136,1208210,119_0,COMPLETED,BOTORCH_MODULAR,70.769999999999996020960679743439,500,0.000831947283164969752372597256,64,3135,0.407442596642336507528625588748,1,128,5
120,1762058924,4,21991ec7-24fc-46c4-9def-2d379a567e83,1762058928,1762066735,7807,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 4096 --dropout 0.35812620962038882455 --num_dense_layers 1 --filter 118 --num_conv_layers 6,0,,c152,1208212,120_0,COMPLETED,BOTORCH_MODULAR,69.790000000000006252776074688882,500,0.001000000000000000020816681712,64,4096,0.35812620962038882455047428266,1,118,6
121,1762058925,51,21991ec7-24fc-46c4-9def-2d379a567e83,1762058976,1762064276,5300,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 355 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 3512 --dropout 0.34144063808810698468 --num_dense_layers 1 --filter 112 --num_conv_layers 6,0,,c143,1208223,121_0,COMPLETED,BOTORCH_MODULAR,68.709999999999993747223925311118,355,0.001000000000000000020816681712,64,3512,0.341440638088106984682212896587,1,112,6
122,1762058925,43,21991ec7-24fc-46c4-9def-2d379a567e83,1762058968,1762067367,8399,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 2128 --dropout 0.46477170332520068019 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c145,1208221,122_0,COMPLETED,BOTORCH_MODULAR,68.950000000000002842170943040401,500,0.001000000000000000020816681712,64,2128,0.464771703325200680190221191879,2,128,6
123,1762058924,23,21991ec7-24fc-46c4-9def-2d379a567e83,1762058947,1762066594,7647,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 4096 --dropout 0.35623360929913322481 --num_dense_layers 1 --filter 118 --num_conv_layers 6,0,,c151,1208215,123_0,COMPLETED,BOTORCH_MODULAR,69.370000000000004547473508864641,500,0.001000000000000000020816681712,64,4096,0.356233609299133224812550224669,1,118,6
124,1762058924,24,21991ec7-24fc-46c4-9def-2d379a567e83,1762058948,1762066434,7486,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 4096 --dropout 0.36900316456166154522 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c151,1208213,124_0,COMPLETED,BOTORCH_MODULAR,69.909999999999996589394868351519,500,0.001000000000000000020816681712,64,4096,0.36900316456166154521767452934,1,128,6
125,1762058924,24,21991ec7-24fc-46c4-9def-2d379a567e83,1762058948,1762064480,5532,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 354 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 3913 --dropout 0.35096110790498691312 --num_dense_layers 1 --filter 117 --num_conv_layers 6,0,,c151,1208214,125_0,COMPLETED,BOTORCH_MODULAR,69.290000000000006252776074688882,354,0.001000000000000000020816681712,64,3913,0.350961107904986913119671498862,1,117,6
126,1762058925,42,21991ec7-24fc-46c4-9def-2d379a567e83,1762058967,1762066462,7495,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 3880 --dropout 0.36741044800536459825 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c143,1208222,126_0,COMPLETED,BOTORCH_MODULAR,70.42000000000000170530256582424,500,0.001000000000000000020816681712,64,3880,0.367410448005364598245137131016,1,128,6
127,1762058925,62,21991ec7-24fc-46c4-9def-2d379a567e83,1762058987,1762066507,7520,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 3816 --dropout 0.35223458706040039479 --num_dense_layers 1 --filter 116 --num_conv_layers 6,0,,c141,1208224,127_0,COMPLETED,BOTORCH_MODULAR,69.069999999999993178789736703038,500,0.001000000000000000020816681712,64,3816,0.352234587060400394786796596236,1,116,6
128,1762058924,23,21991ec7-24fc-46c4-9def-2d379a567e83,1762058947,1762066339,7392,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 4096 --dropout 0.34812149696098082519 --num_dense_layers 1 --filter 112 --num_conv_layers 6,0,,c147,1208218,128_0,COMPLETED,BOTORCH_MODULAR,69.400000000000005684341886080801,500,0.001000000000000000020816681712,64,4096,0.348121496960980825186027232121,1,112,6
129,1762058925,91,21991ec7-24fc-46c4-9def-2d379a567e83,1762059016,1762063779,4763,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 314 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 3959 --dropout 0.35759421606744867805 --num_dense_layers 1 --filter 116 --num_conv_layers 6,0,,c139,1208227,129_0,COMPLETED,BOTORCH_MODULAR,69.349999999999994315658113919199,314,0.001000000000000000020816681712,64,3959,0.357594216067448678053608546179,1,116,6
130,1762058925,43,21991ec7-24fc-46c4-9def-2d379a567e83,1762058968,1762066563,7595,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 4096 --dropout 0.3303440474224583201 --num_dense_layers 1 --filter 100 --num_conv_layers 5,0,,c146,1208220,130_0,COMPLETED,BOTORCH_MODULAR,70.310000000000002273736754432321,500,0.001000000000000000020816681712,64,4096,0.33034404742245832009572836796,1,100,5
131,1762058925,23,21991ec7-24fc-46c4-9def-2d379a567e83,1762058948,1762060970,2022,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 149 --learning_rate 0.00100000000000000002 --batch_size 101 --hidden_size 4010 --dropout 0.34205302873479320747 --num_dense_layers 1 --filter 111 --num_conv_layers 6,0,,c149,1208216,131_0,COMPLETED,BOTORCH_MODULAR,68.560000000000002273736754432321,149,0.001000000000000000020816681712,101,4010,0.342053028734793207465969544501,1,111,6
132,1762058925,81,21991ec7-24fc-46c4-9def-2d379a567e83,1762059006,1762066484,7478,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 4096 --dropout 0.3482587607808832475 --num_dense_layers 1 --filter 112 --num_conv_layers 6,0,,c140,1208226,132_0,COMPLETED,BOTORCH_MODULAR,69.349999999999994315658113919199,500,0.001000000000000000020816681712,64,4096,0.348258760780883247498707078194,1,112,6
133,1762058924,23,21991ec7-24fc-46c4-9def-2d379a567e83,1762058947,1762067591,8644,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 4096 --dropout 0.47572296552500897837 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c148,1208217,133_0,COMPLETED,BOTORCH_MODULAR,70.82999999999999829469743417576,500,0.001000000000000000020816681712,64,4096,0.475722965525008978371346302083,1,128,5
134,1762058925,42,21991ec7-24fc-46c4-9def-2d379a567e83,1762058967,1762067207,8240,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 4096 --dropout 0.3723741080295687178 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c147,1208219,134_0,COMPLETED,BOTORCH_MODULAR,70.200000000000002842170943040401,500,0.001000000000000000020816681712,64,4096,0.372374108029568717803670097055,1,128,6
135,1762058926,80,21991ec7-24fc-46c4-9def-2d379a567e83,1762059006,1762065688,6682,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 440 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 3527 --dropout 0.3465442543892573446 --num_dense_layers 1 --filter 113 --num_conv_layers 6,0,,c141,1208225,135_0,COMPLETED,BOTORCH_MODULAR,69.180000000000006821210263296962,440,0.001000000000000000020816681712,64,3527,0.346544254389257344595165477585,1,113,6
136,1762058926,90,21991ec7-24fc-46c4-9def-2d379a567e83,1762059016,1762066527,7511,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 4096 --dropout 0.3485963006326079916 --num_dense_layers 1 --filter 112 --num_conv_layers 6,0,,c139,1208228,136_0,COMPLETED,BOTORCH_MODULAR,70.049999999999997157829056959599,500,0.001000000000000000020816681712,64,4096,0.348596300632607991598632679597,1,112,6
137,1762058931,86,21991ec7-24fc-46c4-9def-2d379a567e83,1762059017,1762066747,7730,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 4096 --dropout 0.35359698722556059947 --num_dense_layers 1 --filter 117 --num_conv_layers 6,0,,c139,1208229,137_0,COMPLETED,BOTORCH_MODULAR,69.959999999999993747223925311118,500,0.001000000000000000020816681712,64,4096,0.353596987225560599465978839362,1,117,6
138,1762058937,79,21991ec7-24fc-46c4-9def-2d379a567e83,1762059016,1762061459,2443,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 172 --learning_rate 0.00100000000000000002 --batch_size 98 --hidden_size 4096 --dropout 0.33502660412392548661 --num_dense_layers 1 --filter 115 --num_conv_layers 6,0,,c139,1208230,138_0,COMPLETED,BOTORCH_MODULAR,69.75,172,0.001000000000000000020816681712,98,4096,0.335026604123925486611312862806,1,115,6
139,1762058937,69,21991ec7-24fc-46c4-9def-2d379a567e83,1762059006,1762066459,7453,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 4096 --dropout 0.37177651930481286913 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c138,1208231,139_0,COMPLETED,BOTORCH_MODULAR,69.900000000000005684341886080801,500,0.001000000000000000020816681712,64,4096,0.37177651930481286912666405442,1,128,6
140,1762067801,4,21991ec7-24fc-46c4-9def-2d379a567e83,1762067805,1762076203,8398,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 4096 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 5,0,,c154,1208232,140_0,COMPLETED,BOTORCH_MODULAR,69.21999999999999886313162278384,500,0.001000000000000000020816681712,64,4096,0.5,2,128,5
141,,,,,,,,,,,,140_0,ABANDONED,BOTORCH_MODULAR,,500,0.001000000000000000020816681712,64,4096,0.5,2,128,5
142,,,,,,,,,,,,140_0,ABANDONED,BOTORCH_MODULAR,,500,0.001000000000000000020816681712,64,4096,0.5,2,128,5
143,,,,,,,,,,,,140_0,ABANDONED,BOTORCH_MODULAR,,500,0.001000000000000000020816681712,64,4096,0.5,2,128,5
144,,,,,,,,,,,,140_0,ABANDONED,BOTORCH_MODULAR,,500,0.001000000000000000020816681712,64,4096,0.5,2,128,5
145,,,,,,,,,,,,140_0,ABANDONED,BOTORCH_MODULAR,,500,0.001000000000000000020816681712,64,4096,0.5,2,128,5
146,,,,,,,,,,,,140_0,ABANDONED,BOTORCH_MODULAR,,500,0.001000000000000000020816681712,64,4096,0.5,2,128,5
147,,,,,,,,,,,,140_0,ABANDONED,BOTORCH_MODULAR,,500,0.001000000000000000020816681712,64,4096,0.5,2,128,5
148,,,,,,,,,,,,140_0,ABANDONED,BOTORCH_MODULAR,,500,0.001000000000000000020816681712,64,4096,0.5,2,128,5
149,,,,,,,,,,,,140_0,ABANDONED,BOTORCH_MODULAR,,500,0.001000000000000000020816681712,64,4096,0.5,2,128,5
150,,,,,,,,,,,,140_0,ABANDONED,BOTORCH_MODULAR,,500,0.001000000000000000020816681712,64,4096,0.5,2,128,5
151,,,,,,,,,,,,140_0,ABANDONED,BOTORCH_MODULAR,,500,0.001000000000000000020816681712,64,4096,0.5,2,128,5
152,,,,,,,,,,,,140_0,ABANDONED,BOTORCH_MODULAR,,500,0.001000000000000000020816681712,64,4096,0.5,2,128,5
153,,,,,,,,,,,,140_0,ABANDONED,BOTORCH_MODULAR,,500,0.001000000000000000020816681712,64,4096,0.5,2,128,5
154,,,,,,,,,,,,140_0,ABANDONED,BOTORCH_MODULAR,,500,0.001000000000000000020816681712,64,4096,0.5,2,128,5
155,,,,,,,,,,,,140_0,ABANDONED,BOTORCH_MODULAR,,500,0.001000000000000000020816681712,64,4096,0.5,2,128,5
156,,,,,,,,,,,,140_0,ABANDONED,BOTORCH_MODULAR,,500,0.001000000000000000020816681712,64,4096,0.5,2,128,5
157,,,,,,,,,,,,140_0,ABANDONED,BOTORCH_MODULAR,,500,0.001000000000000000020816681712,64,4096,0.5,2,128,5
158,,,,,,,,,,,,140_0,ABANDONED,BOTORCH_MODULAR,,500,0.001000000000000000020816681712,64,4096,0.5,2,128,5
159,1762076427,52,21991ec7-24fc-46c4-9def-2d379a567e83,1762076479,1762079768,3289,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 254 --learning_rate 0.00028498521780048655 --batch_size 158 --hidden_size 3190 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 7,0,,c140,1208255,159_0,COMPLETED,BOTORCH_MODULAR,65.629999999999995452526491135359,254,0.000284985217800486545416255302,158,3190,0.5,2,128,7
160,1762076425,29,21991ec7-24fc-46c4-9def-2d379a567e83,1762076454,1762084295,7841,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00077278213936318296 --batch_size 64 --hidden_size 4096 --dropout 0.44539304705471599588 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c151,1208246,160_0,COMPLETED,BOTORCH_MODULAR,71.42000000000000170530256582424,500,0.000772782139363182955793529771,64,4096,0.445393047054715995880513901284,1,128,5
161,1762076425,24,21991ec7-24fc-46c4-9def-2d379a567e83,1762076449,1762083620,7171,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 458 --learning_rate 0.00019849792289251982 --batch_size 64 --hidden_size 2360 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 7,0,,c143,1208250,161_0,COMPLETED,BOTORCH_MODULAR,66.32999999999999829469743417576,458,0.000198497922892519818504827867,64,2360,0.5,2,128,7
162,1762076425,43,21991ec7-24fc-46c4-9def-2d379a567e83,1762076468,1762084328,7860,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00077211175262876998 --batch_size 64 --hidden_size 4096 --dropout 0.45073113348558041524 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c143,1208252,162_0,COMPLETED,BOTORCH_MODULAR,70.870000000000004547473508864641,500,0.000772111752628769983271272981,64,4096,0.450731133485580415243276775072,1,128,5
163,1762076425,24,21991ec7-24fc-46c4-9def-2d379a567e83,1762076449,1762085101,8652,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00077439021667998918 --batch_size 64 --hidden_size 4096 --dropout 0.4459153989477646074 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c148,1208247,163_0,COMPLETED,BOTORCH_MODULAR,71.17000000000000170530256582424,500,0.000774390216679989181434995427,64,4096,0.4459153989477646073957828321,1,128,5
164,1762076425,24,21991ec7-24fc-46c4-9def-2d379a567e83,1762076449,1762084371,7922,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00077306917441201058 --batch_size 64 --hidden_size 4096 --dropout 0.44746323130829840364 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c152,1208245,164_0,COMPLETED,BOTORCH_MODULAR,70.92000000000000170530256582424,500,0.000773069174412010584954146886,64,4096,0.447463231308298403643419760556,1,128,5
165,1762076425,44,21991ec7-24fc-46c4-9def-2d379a567e83,1762076469,1762084338,7869,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00077308796894754318 --batch_size 64 --hidden_size 4096 --dropout 0.44512228527532454736 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c146,1208251,165_0,COMPLETED,BOTORCH_MODULAR,70.950000000000002842170943040401,500,0.000773087968947543178847847667,64,4096,0.445122285275324547360042970467,1,128,5
166,1762076426,55,21991ec7-24fc-46c4-9def-2d379a567e83,1762076481,1762084151,7670,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00011538117879721583 --batch_size 64 --hidden_size 4004 --dropout 0.47510468034898878376 --num_dense_layers 1 --filter 128 --num_conv_layers 7,0,,c141,1208253,166_0,COMPLETED,BOTORCH_MODULAR,63.89000000000000056843418860808,500,0.00011538117879721582822050846,64,4004,0.475104680348988783755714848667,1,128,7
167,1762076426,66,21991ec7-24fc-46c4-9def-2d379a567e83,1762076492,1762079098,2606,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 174 --learning_rate 0.00023401458819055065 --batch_size 85 --hidden_size 2611 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 7,0,,c139,1208257,167_0,COMPLETED,BOTORCH_MODULAR,66.319999999999993178789736703038,174,0.000234014588190550653972951678,85,2611,0.5,2,128,7
168,1762076426,66,21991ec7-24fc-46c4-9def-2d379a567e83,1762076492,1762084429,7937,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00077560891553343791 --batch_size 64 --hidden_size 4096 --dropout 0.44246261383734403205 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c139,1208256,168_0,COMPLETED,BOTORCH_MODULAR,71.159999999999996589394868351519,500,0.000775608915533437912222247679,64,4096,0.442462613837344032052811826361,1,128,5
169,1762076427,67,21991ec7-24fc-46c4-9def-2d379a567e83,1762076494,1762084052,7558,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00046294475929433278 --batch_size 64 --hidden_size 4028 --dropout 0.43913597483575333991 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c139,1208258,169_0,COMPLETED,BOTORCH_MODULAR,69.459999999999993747223925311118,500,0.000462944759294332775986791084,64,4028,0.439135974835753339906574410634,1,128,6
170,1762076425,24,21991ec7-24fc-46c4-9def-2d379a567e83,1762076449,1762084168,7719,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.0001 --batch_size 64 --hidden_size 3549 --dropout 0.48505274934820769017 --num_dense_layers 1 --filter 128 --num_conv_layers 7,0,,c147,1208248,170_0,COMPLETED,BOTORCH_MODULAR,62.53999999999999914734871708788,500,0.000100000000000000004792173602,64,3549,0.48505274934820769017207453544,1,128,7
171,1762076425,4,21991ec7-24fc-46c4-9def-2d379a567e83,1762076429,1762084340,7911,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00077303910707471357 --batch_size 64 --hidden_size 4096 --dropout 0.45086291268828765366 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c154,1208244,171_0,COMPLETED,BOTORCH_MODULAR,70.980000000000003979039320256561,500,0.000773039107074713566572499168,64,4096,0.450862912688287653661944887062,1,128,5
172,1762076426,82,21991ec7-24fc-46c4-9def-2d379a567e83,1762076508,1762083983,7475,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00046315362551926784 --batch_size 64 --hidden_size 4096 --dropout 0.44122648188405544367 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c139,1208259,172_0,COMPLETED,BOTORCH_MODULAR,70.010000000000005115907697472721,500,0.000463153625519267841178366885,64,4096,0.441226481884055443671854845888,1,128,6
173,1762076426,53,21991ec7-24fc-46c4-9def-2d379a567e83,1762076479,1762084170,7691,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.0001622880463966613 --batch_size 64 --hidden_size 1764 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 7,0,,c141,1208254,173_0,COMPLETED,BOTORCH_MODULAR,64.71999999999999886313162278384,500,0.000162288046396661295210986364,64,1764,0.5,2,128,7
174,1762076425,30,21991ec7-24fc-46c4-9def-2d379a567e83,1762076455,1762085037,8582,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00077703351956094006 --batch_size 64 --hidden_size 4096 --dropout 0.44337683693419899233 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c147,1208249,174_0,COMPLETED,BOTORCH_MODULAR,71.25,500,0.000777033519560940059804632352,64,4096,0.443376836934198992334899003254,1,128,5
175,1762076428,87,21991ec7-24fc-46c4-9def-2d379a567e83,1762076515,1762084027,7512,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00045524291855976944 --batch_size 64 --hidden_size 3893 --dropout 0.43751756592507634602 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c138,1208260,175_0,COMPLETED,BOTORCH_MODULAR,69.769999999999996020960679743439,500,0.000455242918559769442054391275,64,3893,0.437517565925076346022848383654,1,128,6
176,1762076432,87,21991ec7-24fc-46c4-9def-2d379a567e83,1762076519,1762084463,7944,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00077333174247150695 --batch_size 64 --hidden_size 4096 --dropout 0.44424820913542745204 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c138,1208261,176_0,COMPLETED,BOTORCH_MODULAR,70.96999999999999886313162278384,500,0.000773331742471506950603599151,64,4096,0.444248209135427452043387575031,1,128,5
177,1762076437,71,21991ec7-24fc-46c4-9def-2d379a567e83,1762076508,1762084353,7845,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00077204345653668306 --batch_size 64 --hidden_size 4096 --dropout 0.44984499772399877404 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c138,1208262,177_0,COMPLETED,BOTORCH_MODULAR,70.799999999999997157829056959599,500,0.000772043456536683058571979288,64,4096,0.449844997723998774041831438808,1,128,5
178,1762076443,72,21991ec7-24fc-46c4-9def-2d379a567e83,1762076515,1762084090,7575,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 478 --learning_rate 0.00021952727931108857 --batch_size 67 --hidden_size 2912 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 7,0,,c138,1208263,178_0,COMPLETED,BOTORCH_MODULAR,66.200000000000002842170943040401,478,0.000219527279311088567960788542,67,2912,0.5,2,128,7
179,1762085310,52,21991ec7-24fc-46c4-9def-2d379a567e83,1762085362,1762093402,8040,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00075688709839442372 --batch_size 64 --hidden_size 3990 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c138,1208306,179_0,COMPLETED,BOTORCH_MODULAR,70.909999999999996589394868351519,500,0.000756887098394423717996615242,64,3990,0.5,1,128,5
180,1762085309,20,21991ec7-24fc-46c4-9def-2d379a567e83,1762085329,1762093172,7843,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00075005005486980525 --batch_size 64 --hidden_size 3814 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c143,1208294,180_0,COMPLETED,BOTORCH_MODULAR,71.489999999999994884092302527279,500,0.000750050054869805249424530302,64,3814,0.5,1,128,5
181,1762085310,51,21991ec7-24fc-46c4-9def-2d379a567e83,1762085361,1762089415,4054,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 260 --learning_rate 0.00059641845590151894 --batch_size 64 --hidden_size 2666 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c138,1208303,181_0,COMPLETED,BOTORCH_MODULAR,69.540000000000006252776074688882,260,0.000596418455901518936891625433,64,2666,0.5,2,128,6
182,1762085308,7,21991ec7-24fc-46c4-9def-2d379a567e83,1762085315,1762093145,7830,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00075745796479052905 --batch_size 64 --hidden_size 4001 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c152,1208291,182_0,COMPLETED,BOTORCH_MODULAR,71.370000000000004547473508864641,500,0.000757457964790529052027945323,64,4001,0.5,1,128,5
183,1762085309,25,21991ec7-24fc-46c4-9def-2d379a567e83,1762085334,1762090929,5595,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00100000000000000002 --batch_size 616 --hidden_size 4096 --dropout 0 --num_dense_layers 1 --filter 104 --num_conv_layers 5,0,,c143,1208295,183_0,COMPLETED,BOTORCH_MODULAR,63.939999999999997726263245567679,500,0.001000000000000000020816681712,616,4096,0,1,104,5
184,1762085309,20,21991ec7-24fc-46c4-9def-2d379a567e83,1762085329,1762088357,3028,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 187 --learning_rate 0.00066543167893203632 --batch_size 65 --hidden_size 3605 --dropout 0.5 --num_dense_layers 2 --filter 124 --num_conv_layers 6,0,,c141,1208296,184_0,COMPLETED,BOTORCH_MODULAR,69.980000000000003979039320256561,187,0.000665431678932036315722575726,65,3605,0.5,2,124,6
185,1762085309,6,21991ec7-24fc-46c4-9def-2d379a567e83,1762085315,1762090861,5546,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00100000000000000002 --batch_size 616 --hidden_size 3777 --dropout 0 --num_dense_layers 1 --filter 107 --num_conv_layers 5,0,,c151,1208293,185_0,COMPLETED,BOTORCH_MODULAR,64.349999999999994315658113919199,500,0.001000000000000000020816681712,616,3777,0,1,107,5
186,1762085308,7,21991ec7-24fc-46c4-9def-2d379a567e83,1762085315,1762092892,7577,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 483 --learning_rate 0.0006112311779646639 --batch_size 64 --hidden_size 3102 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c152,1208292,186_0,COMPLETED,BOTORCH_MODULAR,69.090000000000003410605131648481,483,0.000611231177964663896159946965,64,3102,0.5,2,128,6
187,1762085309,54,21991ec7-24fc-46c4-9def-2d379a567e83,1762085363,1762088058,2695,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 167 --learning_rate 0.00063188874617333942 --batch_size 64 --hidden_size 3610 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c139,1208301,187_0,COMPLETED,BOTORCH_MODULAR,69.180000000000006821210263296962,167,0.000631888746173339416883907305,64,3610,0.5,2,128,6
188,1762085310,24,21991ec7-24fc-46c4-9def-2d379a567e83,1762085334,1762090895,5561,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00100000000000000002 --batch_size 490 --hidden_size 4096 --dropout 0.00062581913428916107 --num_dense_layers 1 --filter 97 --num_conv_layers 5,0,,c141,1208297,188_0,COMPLETED,BOTORCH_MODULAR,63.60999999999999943156581139192,500,0.001000000000000000020816681712,490,4096,0.000625819134289161069228946133,1,97,5
189,1762085310,44,21991ec7-24fc-46c4-9def-2d379a567e83,1762085354,1762093256,7902,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00075831186201674239 --batch_size 64 --hidden_size 4010 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c140,1208298,189_0,COMPLETED,BOTORCH_MODULAR,71.260000000000005115907697472721,500,0.000758311862016742394519697168,64,4010,0.5,1,128,5
190,1762085310,53,21991ec7-24fc-46c4-9def-2d379a567e83,1762085363,1762093234,7871,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00075139122850349772 --batch_size 64 --hidden_size 3977 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c139,1208302,190_0,COMPLETED,BOTORCH_MODULAR,70.909999999999996589394868351519,500,0.00075139122850349771530475973,64,3977,0.5,1,128,5
191,1762085310,52,21991ec7-24fc-46c4-9def-2d379a567e83,1762085362,1762093189,7827,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00075813746746674325 --batch_size 64 --hidden_size 4074 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c138,1208305,191_0,COMPLETED,BOTORCH_MODULAR,71.10999999999999943156581139192,500,0.000758137467466743248008242961,64,4074,0.5,1,128,5
192,1762085310,53,21991ec7-24fc-46c4-9def-2d379a567e83,1762085363,1762093340,7977,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00053625089038828605 --batch_size 64 --hidden_size 2629 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 5,0,,c139,1208299,192_0,COMPLETED,BOTORCH_MODULAR,69.959999999999993747223925311118,500,0.000536250890388286047434640569,64,2629,0.5,2,128,5
193,1762085310,54,21991ec7-24fc-46c4-9def-2d379a567e83,1762085364,1762091111,5747,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00100000000000000002 --batch_size 460 --hidden_size 4096 --dropout 0.01976469193674256289 --num_dense_layers 1 --filter 99 --num_conv_layers 5,0,,c139,1208300,193_0,COMPLETED,BOTORCH_MODULAR,64.569999999999993178789736703038,500,0.001000000000000000020816681712,460,4096,0.019764691936742562888840168966,1,99,5
194,1762085309,52,21991ec7-24fc-46c4-9def-2d379a567e83,1762085361,1762090881,5520,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00100000000000000002 --batch_size 483 --hidden_size 4096 --dropout 0.01603616734226321131 --num_dense_layers 1 --filter 96 --num_conv_layers 5,0,,c138,1208304,194_0,COMPLETED,BOTORCH_MODULAR,64.57999999999999829469743417576,500,0.001000000000000000020816681712,483,4096,0.016036167342263211305075643054,1,96,5
195,1762085314,61,21991ec7-24fc-46c4-9def-2d379a567e83,1762085375,1762091006,5631,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00100000000000000002 --batch_size 531 --hidden_size 3999 --dropout 0 --num_dense_layers 1 --filter 99 --num_conv_layers 5,0,,c137,1208307,195_0,COMPLETED,BOTORCH_MODULAR,64.450000000000002842170943040401,500,0.001000000000000000020816681712,531,3999,0,1,99,5
196,1762085314,61,21991ec7-24fc-46c4-9def-2d379a567e83,1762085375,1762090721,5346,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 338 --learning_rate 0.00060934979984462133 --batch_size 64 --hidden_size 3055 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c137,1208309,196_0,COMPLETED,BOTORCH_MODULAR,69.82999999999999829469743417576,338,0.000609349799844621331339211689,64,3055,0.5,2,128,6
197,1762085314,60,21991ec7-24fc-46c4-9def-2d379a567e83,1762085374,1762090929,5555,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00100000000000000002 --batch_size 562 --hidden_size 3989 --dropout 0 --num_dense_layers 1 --filter 103 --num_conv_layers 5,0,,c137,1208308,197_0,COMPLETED,BOTORCH_MODULAR,64.209999999999993747223925311118,500,0.001000000000000000020816681712,562,3989,0,1,103,5
198,1762085316,59,21991ec7-24fc-46c4-9def-2d379a567e83,1762085375,1762093113,7738,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00060182331796224087 --batch_size 64 --hidden_size 2844 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c137,1208310,198_0,COMPLETED,BOTORCH_MODULAR,69.310000000000002273736754432321,500,0.000601823317962240874647028566,64,2844,0.5,2,128,6
199,1762093594,22,21991ec7-24fc-46c4-9def-2d379a567e83,1762093616,1762100605,6989,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 449 --learning_rate 0.00097303414244843912 --batch_size 64 --hidden_size 2689 --dropout 0.5 --num_dense_layers 2 --filter 86 --num_conv_layers 5,0,,c141,1208355,199_0,COMPLETED,BOTORCH_MODULAR,68.409999999999996589394868351519,449,0.000973034142448439120370862199,64,2689,0.5,2,86,5
200,1762093592,5,21991ec7-24fc-46c4-9def-2d379a567e83,1762093597,1762099006,5409,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 344 --learning_rate 0.00096157004511519535 --batch_size 64 --hidden_size 2567 --dropout 0.5 --num_dense_layers 2 --filter 87 --num_conv_layers 5,0,,c154,1208348,200_0,COMPLETED,BOTORCH_MODULAR,68.5,344,0.000961570045115195349769154909,64,2567,0.5,2,87,5
201,1762093593,18,21991ec7-24fc-46c4-9def-2d379a567e83,1762093611,1762100132,6521,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 412 --learning_rate 0.00098099037544366417 --batch_size 64 --hidden_size 3121 --dropout 0.5 --num_dense_layers 2 --filter 81 --num_conv_layers 5,0,,c143,1208353,201_0,COMPLETED,BOTORCH_MODULAR,67.89000000000000056843418860808,412,0.0009809903754436641656888618,64,3121,0.5,2,81,5
202,1762093592,5,21991ec7-24fc-46c4-9def-2d379a567e83,1762093597,1762099432,5835,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 376 --learning_rate 0.00097617712391930066 --batch_size 64 --hidden_size 2925 --dropout 0.5 --num_dense_layers 2 --filter 86 --num_conv_layers 5,0,,c153,1208349,202_0,COMPLETED,BOTORCH_MODULAR,67.299999999999997157829056959599,376,0.000976177123919300658051734221,64,2925,0.5,2,86,5
203,1762093593,16,21991ec7-24fc-46c4-9def-2d379a567e83,1762093609,1762100840,7231,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 462 --learning_rate 0.00098253545685565301 --batch_size 64 --hidden_size 2926 --dropout 0.5 --num_dense_layers 2 --filter 83 --num_conv_layers 5,0,,c152,1208351,203_0,COMPLETED,BOTORCH_MODULAR,67.739999999999994884092302527279,462,0.000982535456855653010002638048,64,2926,0.5,2,83,5
204,1762093594,47,21991ec7-24fc-46c4-9def-2d379a567e83,1762093641,1762097503,3862,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 252 --learning_rate 0.0009636391669750208 --batch_size 64 --hidden_size 2168 --dropout 0.5 --num_dense_layers 2 --filter 91 --num_conv_layers 5,0,,c138,1208362,204_0,COMPLETED,BOTORCH_MODULAR,67,252,0.000963639166975020799478512945,64,2168,0.5,2,91,5
205,1762093594,52,21991ec7-24fc-46c4-9def-2d379a567e83,1762093646,1762101552,7906,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00098795416803208443 --batch_size 64 --hidden_size 3148 --dropout 0.5 --num_dense_layers 2 --filter 82 --num_conv_layers 5,0,,c139,1208360,205_0,COMPLETED,BOTORCH_MODULAR,67.840000000000003410605131648481,500,0.000987954168032084429490469191,64,3148,0.5,2,82,5
206,1762093593,48,21991ec7-24fc-46c4-9def-2d379a567e83,1762093641,1762100433,6792,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 435 --learning_rate 0.00097209414089063494 --batch_size 64 --hidden_size 2689 --dropout 0.5 --num_dense_layers 2 --filter 86 --num_conv_layers 5,0,,c138,1208361,206_0,COMPLETED,BOTORCH_MODULAR,68.39000000000000056843418860808,435,0.000972094140890634940584125179,64,2689,0.5,2,86,5
207,1762093593,23,21991ec7-24fc-46c4-9def-2d379a567e83,1762093616,1762101103,7487,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00095321855379746495 --batch_size 64 --hidden_size 1975 --dropout 0.5 --num_dense_layers 2 --filter 92 --num_conv_layers 5,0,,c140,1208356,207_0,COMPLETED,BOTORCH_MODULAR,68.040000000000006252776074688882,500,0.000953218553797464951404805333,64,1975,0.5,2,92,5
208,1762093593,53,21991ec7-24fc-46c4-9def-2d379a567e83,1762093646,1762095735,2089,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 129 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 3772 --dropout 0.5 --num_dense_layers 2 --filter 77 --num_conv_layers 5,0,,c139,1208357,208_0,COMPLETED,BOTORCH_MODULAR,67.14000000000000056843418860808,129,0.001000000000000000020816681712,64,3772,0.5,2,77,5
209,1762093593,16,21991ec7-24fc-46c4-9def-2d379a567e83,1762093609,1762101521,7912,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 3555 --dropout 0.5 --num_dense_layers 2 --filter 78 --num_conv_layers 5,0,,c143,1208352,209_0,COMPLETED,BOTORCH_MODULAR,67.840000000000003410605131648481,500,0.001000000000000000020816681712,64,3555,0.5,2,78,5
210,1762093593,4,21991ec7-24fc-46c4-9def-2d379a567e83,1762093597,1762101569,7972,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 4035 --dropout 0.5 --num_dense_layers 2 --filter 75 --num_conv_layers 5,0,,c152,1208350,210_0,COMPLETED,BOTORCH_MODULAR,67.21999999999999886313162278384,500,0.001000000000000000020816681712,64,4035,0.5,2,75,5
211,1762093594,51,21991ec7-24fc-46c4-9def-2d379a567e83,1762093645,1762101742,8097,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 3804 --dropout 0.5 --num_dense_layers 2 --filter 77 --num_conv_layers 5,0,,c139,1208358,211_0,COMPLETED,BOTORCH_MODULAR,67.310000000000002273736754432321,500,0.001000000000000000020816681712,64,3804,0.5,2,77,5
212,1762093594,52,21991ec7-24fc-46c4-9def-2d379a567e83,1762093646,1762101636,7990,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 3654 --dropout 0.5 --num_dense_layers 2 --filter 77 --num_conv_layers 5,0,,c139,1208359,212_0,COMPLETED,BOTORCH_MODULAR,67.260000000000005115907697472721,500,0.001000000000000000020816681712,64,3654,0.5,2,77,5
213,1762093595,46,21991ec7-24fc-46c4-9def-2d379a567e83,1762093641,1762098776,5135,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 335 --learning_rate 0.00097026486984159836 --batch_size 64 --hidden_size 2583 --dropout 0.5 --num_dense_layers 2 --filter 88 --num_conv_layers 5,0,,c138,1208363,213_0,COMPLETED,BOTORCH_MODULAR,67.310000000000002273736754432321,335,0.000970264869841598359863354961,64,2583,0.5,2,88,5
214,1762093594,15,21991ec7-24fc-46c4-9def-2d379a567e83,1762093609,1762100410,6801,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 433 --learning_rate 0.00099121966682260212 --batch_size 64 --hidden_size 3527 --dropout 0.5 --num_dense_layers 2 --filter 79 --num_conv_layers 5,0,,c141,1208354,214_0,COMPLETED,BOTORCH_MODULAR,68.019999999999996020960679743439,433,0.00099121966682260212455624071,64,3527,0.5,2,79,5
215,1762093599,43,21991ec7-24fc-46c4-9def-2d379a567e83,1762093642,1762101059,7417,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 494 --learning_rate 0.00097311141692120874 --batch_size 64 --hidden_size 1486 --dropout 0.5 --num_dense_layers 2 --filter 92 --num_conv_layers 5,0,,c138,1208364,215_0,COMPLETED,BOTORCH_MODULAR,67.53000000000000113686837721616,494,0.000973111416921208739402859855,64,1486,0.5,2,92,5
216,1762093599,50,21991ec7-24fc-46c4-9def-2d379a567e83,1762093649,1762094373,724,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 46 --learning_rate 0.00098583336156573523 --batch_size 64 --hidden_size 1907 --dropout 0.5 --num_dense_layers 2 --filter 90 --num_conv_layers 5,0,,c137,1208365,216_0,COMPLETED,BOTORCH_MODULAR,65.810000000000002273736754432321,46,0.000985833361565735229528617545,64,1907,0.5,2,90,5
217,1762093599,58,21991ec7-24fc-46c4-9def-2d379a567e83,1762093657,1762098337,4680,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 298 --learning_rate 0.00098904897091682997 --batch_size 64 --hidden_size 3248 --dropout 0.5 --num_dense_layers 2 --filter 82 --num_conv_layers 5,0,,c137,1208366,217_0,COMPLETED,BOTORCH_MODULAR,67.510000000000005115907697472721,298,0.000989048970916829974300843453,64,3248,0.5,2,82,5
218,1762093601,55,21991ec7-24fc-46c4-9def-2d379a567e83,1762093656,1762096860,3204,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 208 --learning_rate 0.0009443157928032853 --batch_size 64 --hidden_size 2091 --dropout 0.5 --num_dense_layers 2 --filter 97 --num_conv_layers 5,0,,c137,1208367,218_0,COMPLETED,BOTORCH_MODULAR,67.78000000000000113686837721616,208,0.000944315792803285302195459572,64,2091,0.5,2,97,5
219,1762101950,5,21991ec7-24fc-46c4-9def-2d379a567e83,1762101955,1762103481,1526,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 139 --learning_rate 0.00100000000000000002 --batch_size 999 --hidden_size 535 --dropout 0.05574258904333279085 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c143,1208427,219_0,COMPLETED,BOTORCH_MODULAR,63.130000000000002557953848736361,139,0.001000000000000000020816681712,999,535,0.055742589043332790854634595235,2,128,6
220,1762101952,42,21991ec7-24fc-46c4-9def-2d379a567e83,1762101994,1762107333,5339,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00100000000000000002 --batch_size 1024 --hidden_size 512 --dropout 0.13370280310340965091 --num_dense_layers 2 --filter 128 --num_conv_layers 5,0,,c124,1208438,220_0,COMPLETED,BOTORCH_MODULAR,62.03999999999999914734871708788,500,0.001000000000000000020816681712,1024,512,0.133702803103409650908872663422,2,128,5
221,1762101951,4,21991ec7-24fc-46c4-9def-2d379a567e83,1762101955,1762107332,5377,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00100000000000000002 --batch_size 1024 --hidden_size 904 --dropout 0.16424735753383531978 --num_dense_layers 2 --filter 128 --num_conv_layers 5,0,,c153,1208426,221_0,COMPLETED,BOTORCH_MODULAR,63.46999999999999886313162278384,500,0.001000000000000000020816681712,1024,904,0.16424735753383531977611653474,2,128,5
222,1762101953,21,21991ec7-24fc-46c4-9def-2d379a567e83,1762101974,1762105765,3791,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 238 --learning_rate 0.00078075278698438695 --batch_size 64 --hidden_size 3883 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c139,1208434,222_0,COMPLETED,BOTORCH_MODULAR,70.82999999999999829469743417576,238,0.000780752786984386954599601793,64,3883,0.5,1,128,5
223,1762101951,23,21991ec7-24fc-46c4-9def-2d379a567e83,1762101974,1762109743,7769,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00075778399099943891 --batch_size 64 --hidden_size 3586 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c141,1208430,223_0,COMPLETED,BOTORCH_MODULAR,70.819999999999993178789736703038,500,0.000757783990999438914620833785,64,3586,0.5,1,128,5
224,1762101952,24,21991ec7-24fc-46c4-9def-2d379a567e83,1762101976,1762107450,5474,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 347 --learning_rate 0.00079802156788944239 --batch_size 64 --hidden_size 4031 --dropout 0.5 --num_dense_layers 1 --filter 124 --num_conv_layers 5,0,,c139,1208433,224_0,COMPLETED,BOTORCH_MODULAR,71.340000000000003410605131648481,347,0.000798021567889442388910037351,64,4031,0.5,1,124,5
225,1762101953,21,21991ec7-24fc-46c4-9def-2d379a567e83,1762101974,1762109870,7896,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.0007544802525838156 --batch_size 64 --hidden_size 3623 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c137,1208436,225_0,COMPLETED,BOTORCH_MODULAR,71.209999999999993747223925311118,500,0.000754480252583815597967886735,64,3623,0.5,1,128,5
226,1762101951,23,21991ec7-24fc-46c4-9def-2d379a567e83,1762101974,1762107292,5318,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00100000000000000002 --batch_size 1024 --hidden_size 512 --dropout 0.15719294364702154909 --num_dense_layers 2 --filter 128 --num_conv_layers 5,0,,c141,1208429,226_0,COMPLETED,BOTORCH_MODULAR,61.46999999999999886313162278384,500,0.001000000000000000020816681712,1024,512,0.157192943647021549091746805971,2,128,5
227,1762101950,5,21991ec7-24fc-46c4-9def-2d379a567e83,1762101955,1762105156,3201,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 200 --learning_rate 0.00078639971515782382 --batch_size 64 --hidden_size 4096 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c154,1208425,227_0,COMPLETED,BOTORCH_MODULAR,71.07999999999999829469743417576,200,0.000786399715157823820006754989,64,4096,0.5,1,128,5
228,1762101950,24,21991ec7-24fc-46c4-9def-2d379a567e83,1762101974,1762109709,7735,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00074305518460342896 --batch_size 64 --hidden_size 3186 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c143,1208428,228_0,COMPLETED,BOTORCH_MODULAR,70.849999999999994315658113919199,500,0.000743055184603428958353688039,64,3186,0.5,1,128,5
229,1762101951,23,21991ec7-24fc-46c4-9def-2d379a567e83,1762101974,1762107420,5446,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00100000000000000002 --batch_size 1024 --hidden_size 512 --dropout 0.15590287906158276088 --num_dense_layers 2 --filter 128 --num_conv_layers 5,0,,c140,1208431,229_0,COMPLETED,BOTORCH_MODULAR,62.380000000000002557953848736361,500,0.001000000000000000020816681712,1024,512,0.155902879061582760877868736316,2,128,5
230,,,,,,,,,,,,230_0,FAILED,BOTORCH_MODULAR,,500,0.000746557313181044372371597539,64,3427,0.5,1,128,5
231,1762101954,45,21991ec7-24fc-46c4-9def-2d379a567e83,1762101999,1762105816,3817,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 245 --learning_rate 0.00078203457038065257 --batch_size 64 --hidden_size 3657 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c124,1208439,231_0,COMPLETED,BOTORCH_MODULAR,70.96999999999999886313162278384,245,0.000782034570380652567685164644,64,3657,0.5,1,128,5
232,1762101953,21,21991ec7-24fc-46c4-9def-2d379a567e83,1762101974,1762107298,5324,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00100000000000000002 --batch_size 1024 --hidden_size 512 --dropout 0.17246406936885386174 --num_dense_layers 2 --filter 128 --num_conv_layers 5,0,,c138,1208435,232_0,COMPLETED,BOTORCH_MODULAR,60.57000000000000028421709430404,500,0.001000000000000000020816681712,1024,512,0.172464069368853861741186506151,2,128,5
233,1762101953,46,21991ec7-24fc-46c4-9def-2d379a567e83,1762101999,1762107609,5610,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 356 --learning_rate 0.00076790385164069146 --batch_size 64 --hidden_size 3774 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c124,1208440,233_0,COMPLETED,BOTORCH_MODULAR,70.569999999999993178789736703038,356,0.000767903851640691463564802888,64,3774,0.5,1,128,5
234,1762101952,23,21991ec7-24fc-46c4-9def-2d379a567e83,1762101975,1762109861,7886,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00074687930093805159 --batch_size 64 --hidden_size 3333 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c139,1208432,234_0,COMPLETED,BOTORCH_MODULAR,70.659999999999996589394868351519,500,0.000746879300938051594177524706,64,3333,0.5,1,128,5
235,1762101959,36,21991ec7-24fc-46c4-9def-2d379a567e83,1762101995,1762109817,7822,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.0007506166778076922 --batch_size 64 --hidden_size 3595 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c123,1208443,235_0,COMPLETED,BOTORCH_MODULAR,70.790000000000006252776074688882,500,0.000750616677807692199951572487,64,3595,0.5,1,128,5
236,1762101958,36,21991ec7-24fc-46c4-9def-2d379a567e83,1762101994,1762109835,7841,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00075455690832486051 --batch_size 64 --hidden_size 3586 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c123,1208441,236_0,COMPLETED,BOTORCH_MODULAR,71.150000000000005684341886080801,500,0.000754556908324860507557285683,64,3586,0.5,1,128,5
237,1762101958,46,21991ec7-24fc-46c4-9def-2d379a567e83,1762102004,1762109736,7732,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00075384674760907335 --batch_size 64 --hidden_size 3539 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c123,1208442,237_0,COMPLETED,BOTORCH_MODULAR,71.120000000000004547473508864641,500,0.000753846747609073354438879999,64,3539,0.5,1,128,5
238,1762101960,39,21991ec7-24fc-46c4-9def-2d379a567e83,1762101999,1762107396,5397,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00100000000000000002 --batch_size 1024 --hidden_size 512 --dropout 0.1597332825846052573 --num_dense_layers 2 --filter 128 --num_conv_layers 5,0,,c123,1208444,238_0,COMPLETED,BOTORCH_MODULAR,61.5,500,0.001000000000000000020816681712,1024,512,0.159733282584605257303778103051,2,128,5
239,1762117047,46,21991ec7-24fc-46c4-9def-2d379a567e83,1762117093,1762124448,7355,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 512 --dropout 0.02963811313035652484 --num_dense_layers 2 --filter 128 --num_conv_layers 5,0,,c122,1209059,239_0,COMPLETED,BOTORCH_MODULAR,67.290000000000006252776074688882,500,0.001000000000000000020816681712,64,512,0.029638113130356524838049381287,2,128,5
240,1762117048,40,21991ec7-24fc-46c4-9def-2d379a567e83,1762117088,1762117331,243,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 20 --learning_rate 0.00100000000000000002 --batch_size 1024 --hidden_size 3352 --dropout 0 --num_dense_layers 2 --filter 128 --num_conv_layers 5,0,,c120,1209063,240_0,COMPLETED,BOTORCH_MODULAR,53.8500000000000014210854715202,20,0.001000000000000000020816681712,1024,3352,0,2,128,5
241,1762117047,38,21991ec7-24fc-46c4-9def-2d379a567e83,1762117085,1762124771,7686,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00095955831026170023 --batch_size 64 --hidden_size 512 --dropout 0.06317523820574486026 --num_dense_layers 2 --filter 128 --num_conv_layers 7,0,,c122,1209060,241_0,COMPLETED,BOTORCH_MODULAR,67.5,500,0.000959558310261700232908499419,64,512,0.063175238205744860264800877303,2,128,7
242,1762117047,44,21991ec7-24fc-46c4-9def-2d379a567e83,1762117091,1762117335,244,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 20 --learning_rate 0.00100000000000000002 --batch_size 1024 --hidden_size 3377 --dropout 0 --num_dense_layers 2 --filter 128 --num_conv_layers 5,0,,c123,1209056,242_0,COMPLETED,BOTORCH_MODULAR,50.090000000000003410605131648481,20,0.001000000000000000020816681712,1024,3377,0,2,128,5
243,1762117047,11,21991ec7-24fc-46c4-9def-2d379a567e83,1762117058,1762124688,7630,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00094166065219415175 --batch_size 64 --hidden_size 512 --dropout 0.08653687267231791047 --num_dense_layers 2 --filter 128 --num_conv_layers 7,0,,c138,1209050,243_0,COMPLETED,BOTORCH_MODULAR,67.519999999999996020960679743439,500,0.000941660652194151745822403576,64,512,0.086536872672317910470951574098,2,128,7
244,1762117047,50,21991ec7-24fc-46c4-9def-2d379a567e83,1762117097,1762124950,7853,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00080771447250635529 --batch_size 64 --hidden_size 4096 --dropout 0.5 --num_dense_layers 1 --filter 103 --num_conv_layers 5,0,,c123,1209055,244_0,COMPLETED,BOTORCH_MODULAR,69.980000000000003979039320256561,500,0.000807714472506355289464774483,64,4096,0.5,1,103,5
245,1762117049,40,21991ec7-24fc-46c4-9def-2d379a567e83,1762117089,1762117334,245,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 20 --learning_rate 0.00100000000000000002 --batch_size 1024 --hidden_size 3440 --dropout 0 --num_dense_layers 2 --filter 128 --num_conv_layers 5,0,,c123,1209058,245_0,COMPLETED,BOTORCH_MODULAR,51.03000000000000113686837721616,20,0.001000000000000000020816681712,1024,3440,0,2,128,5
246,1762117048,35,21991ec7-24fc-46c4-9def-2d379a567e83,1762117083,1762124637,7554,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00099527622493960233 --batch_size 64 --hidden_size 512 --dropout 0.04311450463328853761 --num_dense_layers 2 --filter 128 --num_conv_layers 7,0,,c122,1209061,246_0,COMPLETED,BOTORCH_MODULAR,66.78000000000000113686837721616,500,0.000995276224939602334462751543,64,512,0.043114504633288537605029233646,2,128,7
247,1762117047,41,21991ec7-24fc-46c4-9def-2d379a567e83,1762117088,1762124016,6928,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00099508596398687485 --batch_size 108 --hidden_size 743 --dropout 0.04689564601430497304 --num_dense_layers 2 --filter 128 --num_conv_layers 7,0,,c123,1209057,247_0,COMPLETED,BOTORCH_MODULAR,66.129999999999995452526491135359,500,0.000995085963986874853098862914,108,743,0.046895646014304973037134516289,2,128,7
248,1762117047,18,21991ec7-24fc-46c4-9def-2d379a567e83,1762117065,1762124433,7368,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 936 --dropout 0.07660946747212789287 --num_dense_layers 2 --filter 128 --num_conv_layers 5,0,,c124,1209051,248_0,COMPLETED,BOTORCH_MODULAR,68.760000000000005115907697472721,500,0.001000000000000000020816681712,64,936,0.076609467472127892873068333301,2,128,5
249,1762117049,47,21991ec7-24fc-46c4-9def-2d379a567e83,1762117096,1762124784,7688,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00095881404577994375 --batch_size 64 --hidden_size 512 --dropout 0.04272468172979164425 --num_dense_layers 2 --filter 128 --num_conv_layers 7,0,,c122,1209062,249_0,COMPLETED,BOTORCH_MODULAR,66.939999999999997726263245567679,500,0.000958814045779943745217988038,64,512,0.042724681729791644246851944899,2,128,7
250,1762117047,20,21991ec7-24fc-46c4-9def-2d379a567e83,1762117067,1762122598,5531,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00100000000000000002 --batch_size 1024 --hidden_size 3600 --dropout 0 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c124,1209054,250_0,COMPLETED,BOTORCH_MODULAR,59.78999999999999914734871708788,500,0.001000000000000000020816681712,1024,3600,0,2,128,6
251,1762117048,55,21991ec7-24fc-46c4-9def-2d379a567e83,1762117103,1762117334,231,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 20 --learning_rate 0.00100000000000000002 --batch_size 1024 --hidden_size 3341 --dropout 0 --num_dense_layers 2 --filter 128 --num_conv_layers 5,0,,c120,1209064,251_0,COMPLETED,BOTORCH_MODULAR,51.75,20,0.001000000000000000020816681712,1024,3341,0,2,128,5
252,1762117047,18,21991ec7-24fc-46c4-9def-2d379a567e83,1762117065,1762117309,244,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 20 --learning_rate 0.00100000000000000002 --batch_size 1024 --hidden_size 3376 --dropout 0 --num_dense_layers 2 --filter 128 --num_conv_layers 5,0,,c124,1209052,252_0,COMPLETED,BOTORCH_MODULAR,52.049999999999997157829056959599,20,0.001000000000000000020816681712,1024,3376,0,2,128,5
253,1762117047,21,21991ec7-24fc-46c4-9def-2d379a567e83,1762117068,1762124960,7892,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00080996760222812 --batch_size 64 --hidden_size 4040 --dropout 0.5 --num_dense_layers 1 --filter 109 --num_conv_layers 5,0,,c124,1209053,253_0,COMPLETED,BOTORCH_MODULAR,70.269999999999996020960679743439,500,0.000809967602228119998644673139,64,4040,0.5,1,109,5
254,1762117048,60,21991ec7-24fc-46c4-9def-2d379a567e83,1762117108,1762122644,5536,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00100000000000000002 --batch_size 1024 --hidden_size 3649 --dropout 0 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c120,1209065,254_0,COMPLETED,BOTORCH_MODULAR,59.71000000000000085265128291212,500,0.001000000000000000020816681712,1024,3649,0,2,128,6
255,1762117052,51,21991ec7-24fc-46c4-9def-2d379a567e83,1762117103,1762124728,7625,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.0009799787261303523 --batch_size 64 --hidden_size 512 --dropout 0.02860403080347104221 --num_dense_layers 2 --filter 128 --num_conv_layers 7,0,,c119,1209066,255_0,COMPLETED,BOTORCH_MODULAR,66.71999999999999886313162278384,500,0.000979978726130352299772408031,64,512,0.028604030803471042210261998662,2,128,7
256,1762117052,51,21991ec7-24fc-46c4-9def-2d379a567e83,1762117103,1762124664,7561,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00092296430007752291 --batch_size 64 --hidden_size 512 --dropout 0.06856233949511551795 --num_dense_layers 2 --filter 128 --num_conv_layers 7,0,,c118,1209067,256_0,COMPLETED,BOTORCH_MODULAR,68.060000000000002273736754432321,500,0.000922964300077522910477345608,64,512,0.068562339495115517951084882498,2,128,7
257,1762117055,53,21991ec7-24fc-46c4-9def-2d379a567e83,1762117108,1762125112,8004,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00079864061578592766 --batch_size 64 --hidden_size 4096 --dropout 0.48736987954771948672 --num_dense_layers 1 --filter 123 --num_conv_layers 5,0,,c118,1209068,257_0,COMPLETED,BOTORCH_MODULAR,70.739999999999994884092302527279,500,0.000798640615785927657915843625,64,4096,0.487369879547719486723167392483,1,123,5
258,1762117060,57,21991ec7-24fc-46c4-9def-2d379a567e83,1762117117,1762122614,5497,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00100000000000000002 --batch_size 1024 --hidden_size 3637 --dropout 0 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c118,1209069,258_0,COMPLETED,BOTORCH_MODULAR,60.240000000000001989519660128281,500,0.001000000000000000020816681712,1024,3637,0,2,128,6
259,1762125340,23,21991ec7-24fc-46c4-9def-2d379a567e83,1762125363,1762127557,2194,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 146 --learning_rate 0.000802108963221366 --batch_size 64 --hidden_size 4096 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c139,1209135,259_0,COMPLETED,BOTORCH_MODULAR,69.989999999999994884092302527279,146,0.000802108963221366002248335914,64,4096,0.5,1,128,6
260,1762125340,28,21991ec7-24fc-46c4-9def-2d379a567e83,1762125368,1762129878,4510,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 295 --learning_rate 0.000794377651248799 --batch_size 64 --hidden_size 4096 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c139,1209134,260_0,COMPLETED,BOTORCH_MODULAR,70.340000000000003410605131648481,295,0.000794377651248799002831058047,64,4096,0.5,1,128,6
261,1762125339,10,21991ec7-24fc-46c4-9def-2d379a567e83,1762125349,1762125669,320,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 20 --learning_rate 0.00080624841632062204 --batch_size 64 --hidden_size 4096 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c143,1209131,261_0,COMPLETED,BOTORCH_MODULAR,62.740000000000001989519660128281,20,0.000806248416320622042670340779,64,4096,0.5,1,128,6
262,1762125339,4,21991ec7-24fc-46c4-9def-2d379a567e83,1762125343,1762125669,326,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 20 --learning_rate 0.00081678983235961011 --batch_size 64 --hidden_size 4096 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c143,1209130,262_0,COMPLETED,BOTORCH_MODULAR,61.1000000000000014210854715202,20,0.000816789832359610112888503863,64,4096,0.5,1,128,6
263,1762125339,10,21991ec7-24fc-46c4-9def-2d379a567e83,1762125349,1762125675,326,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 20 --learning_rate 0.00080319418607895836 --batch_size 64 --hidden_size 3884 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c141,1209132,263_0,COMPLETED,BOTORCH_MODULAR,61.909999999999996589394868351519,20,0.000803194186078958361624247075,64,3884,0.5,1,128,6
264,1762125339,5,21991ec7-24fc-46c4-9def-2d379a567e83,1762125344,1762125669,325,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 20 --learning_rate 0.00081240163105028693 --batch_size 64 --hidden_size 4096 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c151,1209128,264_0,COMPLETED,BOTORCH_MODULAR,62.25,20,0.000812401631050286925604664301,64,4096,0.5,1,128,6
265,1762125339,24,21991ec7-24fc-46c4-9def-2d379a567e83,1762125363,1762125670,307,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 20 --learning_rate 0.00080770395620897116 --batch_size 64 --hidden_size 4096 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c141,1209133,265_0,COMPLETED,BOTORCH_MODULAR,61.96000000000000085265128291212,20,0.000807703956208971163115151182,64,4096,0.5,1,128,6
266,1762125342,43,21991ec7-24fc-46c4-9def-2d379a567e83,1762125385,1762125710,325,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 20 --learning_rate 0.00069191567418996967 --batch_size 64 --hidden_size 512 --dropout 0.20030552132680995436 --num_dense_layers 2 --filter 128 --num_conv_layers 7,0,,c135,1209140,266_0,COMPLETED,BOTORCH_MODULAR,59.1499999999999985789145284798,20,0.000691915674189969671578626098,64,512,0.200305521326809954363312726855,2,128,7
267,1762125339,5,21991ec7-24fc-46c4-9def-2d379a567e83,1762125344,1762133053,7709,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.0006254429441919741 --batch_size 64 --hidden_size 1329 --dropout 0.18879672271632699787 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c151,1209129,267_0,COMPLETED,BOTORCH_MODULAR,68.14000000000000056843418860808,500,0.000625442944191974097012387546,64,1329,0.18879672271632699787069498143,2,128,6
268,1762125340,23,21991ec7-24fc-46c4-9def-2d379a567e83,1762125363,1762127844,2481,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 164 --learning_rate 0.00079782669579243318 --batch_size 64 --hidden_size 4063 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c138,1209138,268_0,COMPLETED,BOTORCH_MODULAR,70.35999999999999943156581139192,164,0.000797826695792433178769376134,64,4063,0.5,1,128,6
269,1762125342,39,21991ec7-24fc-46c4-9def-2d379a567e83,1762125381,1762125706,325,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 20 --learning_rate 0.00069344753621257329 --batch_size 64 --hidden_size 512 --dropout 0.19953036276592694964 --num_dense_layers 2 --filter 128 --num_conv_layers 7,0,,c133,1209143,269_0,COMPLETED,BOTORCH_MODULAR,57.880000000000002557953848736361,20,0.00069344753621257328862759195,64,512,0.199530362765926949641936971602,2,128,7
270,1762125340,39,21991ec7-24fc-46c4-9def-2d379a567e83,1762125379,1762125704,325,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 20 --learning_rate 0.00082002721925317657 --batch_size 64 --hidden_size 4096 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c133,1209142,270_0,COMPLETED,BOTORCH_MODULAR,61.840000000000003410605131648481,20,0.000820027219253176569042917965,64,4096,0.5,1,128,6
271,1762125340,25,21991ec7-24fc-46c4-9def-2d379a567e83,1762125365,1762126211,846,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 54 --learning_rate 0.00080560887757922855 --batch_size 64 --hidden_size 4096 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c138,1209137,271_0,COMPLETED,BOTORCH_MODULAR,69.730000000000003979039320256561,54,0.000805608877579228554142998231,64,4096,0.5,1,128,6
272,1762125340,23,21991ec7-24fc-46c4-9def-2d379a567e83,1762125363,1762127562,2199,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 145 --learning_rate 0.00079943399112615023 --batch_size 64 --hidden_size 4096 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c139,1209136,272_0,COMPLETED,BOTORCH_MODULAR,70.599999999999994315658113919199,145,0.000799433991126150228327673641,64,4096,0.5,1,128,6
273,1762125342,37,21991ec7-24fc-46c4-9def-2d379a567e83,1762125379,1762126503,1124,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 80 --learning_rate 0.00068898225068310533 --batch_size 97 --hidden_size 546 --dropout 0.20027892655846740722 --num_dense_layers 2 --filter 128 --num_conv_layers 7,0,,c134,1209141,273_0,COMPLETED,BOTORCH_MODULAR,67.950000000000002842170943040401,80,0.000688982250683105334511380224,97,546,0.200278926558467407215147204624,2,128,7
274,1762125339,24,21991ec7-24fc-46c4-9def-2d379a567e83,1762125363,1762125683,320,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 20 --learning_rate 0.00079457225335692312 --batch_size 64 --hidden_size 4096 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c137,1209139,274_0,COMPLETED,BOTORCH_MODULAR,61.89000000000000056843418860808,20,0.000794572253356923123047972357,64,4096,0.5,1,128,6
275,1762125348,33,21991ec7-24fc-46c4-9def-2d379a567e83,1762125381,1762125700,319,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 20 --learning_rate 0.00081527836172111184 --batch_size 64 --hidden_size 4096 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c132,1209144,275_0,COMPLETED,BOTORCH_MODULAR,62.259999999999998010480339871719,20,0.000815278361721111840404452309,64,4096,0.5,1,128,6
276,1762125348,31,21991ec7-24fc-46c4-9def-2d379a567e83,1762125379,1762125698,319,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 20 --learning_rate 0.00080810553325434513 --batch_size 64 --hidden_size 4096 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c132,1209146,276_0,COMPLETED,BOTORCH_MODULAR,61.57999999999999829469743417576,20,0.000808105533254345129168250139,64,4096,0.5,1,128,6
277,1762125349,30,21991ec7-24fc-46c4-9def-2d379a567e83,1762125379,1762125698,319,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 20 --learning_rate 0.0008085192920844642 --batch_size 64 --hidden_size 3973 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c132,1209145,277_0,COMPLETED,BOTORCH_MODULAR,61.810000000000002273736754432321,20,0.000808519292084464201789129056,64,3973,0.5,1,128,6
278,1762125350,33,21991ec7-24fc-46c4-9def-2d379a567e83,1762125383,1762125709,326,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 20 --learning_rate 0.00069861040393068654 --batch_size 64 --hidden_size 512 --dropout 0.20261433853597751731 --num_dense_layers 2 --filter 128 --num_conv_layers 7,0,,c131,1209147,278_0,COMPLETED,BOTORCH_MODULAR,59.479999999999996873611962655559,20,0.000698610403930686541321137817,64,512,0.202614338535977517308239725935,2,128,7
279,1762133343,5,21991ec7-24fc-46c4-9def-2d379a567e83,1762133348,1762134786,1438,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 90 --learning_rate 0.00097281597895864898 --batch_size 64 --hidden_size 3380 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c152,1209170,279_0,COMPLETED,BOTORCH_MODULAR,69.17000000000000170530256582424,90,0.000972815978958648983586365855,64,3380,0.5,2,128,6
280,1762133343,16,21991ec7-24fc-46c4-9def-2d379a567e83,1762133359,1762134812,1453,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 90 --learning_rate 0.00096864651603417945 --batch_size 64 --hidden_size 3531 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c143,1209173,280_0,COMPLETED,BOTORCH_MODULAR,69.810000000000002273736754432321,90,0.000968646516034179453497054979,64,3531,0.5,2,128,6
281,1762133344,43,21991ec7-24fc-46c4-9def-2d379a567e83,1762133387,1762134843,1456,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 90 --learning_rate 0.00097219320358164752 --batch_size 64 --hidden_size 3382 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c139,1209179,281_0,COMPLETED,BOTORCH_MODULAR,69.189999999999997726263245567679,90,0.000972193203581647518926600604,64,3382,0.5,2,128,6
282,1762133343,5,21991ec7-24fc-46c4-9def-2d379a567e83,1762133348,1762134762,1414,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 90 --learning_rate 0.00097275452530927312 --batch_size 64 --hidden_size 2931 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c149,1209172,282_0,COMPLETED,BOTORCH_MODULAR,69.620000000000004547473508864641,90,0.000972754525309273121967679199,64,2931,0.5,2,128,6
283,1762133343,19,21991ec7-24fc-46c4-9def-2d379a567e83,1762133362,1762134811,1449,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 90 --learning_rate 0.00097464460283422317 --batch_size 64 --hidden_size 3366 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c143,1209174,283_0,COMPLETED,BOTORCH_MODULAR,70.040000000000006252776074688882,90,0.000974644602834223174568639703,64,3366,0.5,2,128,6
284,1762133344,43,21991ec7-24fc-46c4-9def-2d379a567e83,1762133387,1762134825,1438,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 90 --learning_rate 0.00097062423303198695 --batch_size 64 --hidden_size 3389 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c139,1209178,284_0,COMPLETED,BOTORCH_MODULAR,70.10999999999999943156581139192,90,0.000970624233031986945532954003,64,3389,0.5,2,128,6
285,1762133343,24,21991ec7-24fc-46c4-9def-2d379a567e83,1762133367,1762134817,1450,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 90 --learning_rate 0.00096588498685951194 --batch_size 64 --hidden_size 3414 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c139,1209177,285_0,COMPLETED,BOTORCH_MODULAR,69.349999999999994315658113919199,90,0.000965884986859511939123745794,64,3414,0.5,2,128,6
286,1762133345,42,21991ec7-24fc-46c4-9def-2d379a567e83,1762133387,1762134847,1460,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 90 --learning_rate 0.00097022850320215503 --batch_size 64 --hidden_size 3400 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c138,1209181,286_0,COMPLETED,BOTORCH_MODULAR,69.75,90,0.000970228503202155028763142841,64,3400,0.5,2,128,6
287,1762133343,5,21991ec7-24fc-46c4-9def-2d379a567e83,1762133348,1762134805,1457,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 90 --learning_rate 0.00096900698333857659 --batch_size 64 --hidden_size 3569 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c151,1209171,287_0,COMPLETED,BOTORCH_MODULAR,69.239999999999994884092302527279,90,0.000969006983338576593535462766,64,3569,0.5,2,128,6
288,1762133344,24,21991ec7-24fc-46c4-9def-2d379a567e83,1762133368,1762134824,1456,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 90 --learning_rate 0.00096842453689738144 --batch_size 64 --hidden_size 3379 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c141,1209175,288_0,COMPLETED,BOTORCH_MODULAR,69.35999999999999943156581139192,90,0.000968424536897381435518461501,64,3379,0.5,2,128,6
289,1762133346,41,21991ec7-24fc-46c4-9def-2d379a567e83,1762133387,1762134832,1445,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 90 --learning_rate 0.00096499343639958534 --batch_size 64 --hidden_size 3799 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c137,1209183,289_0,COMPLETED,BOTORCH_MODULAR,69.689999999999997726263245567679,90,0.000964993436399585340947082646,64,3799,0.5,2,128,6
290,1762133346,41,21991ec7-24fc-46c4-9def-2d379a567e83,1762133387,1762134839,1452,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 90 --learning_rate 0.00096398761404793806 --batch_size 64 --hidden_size 3708 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c135,1209184,290_0,COMPLETED,BOTORCH_MODULAR,70.159999999999996589394868351519,90,0.000963987614047938064579246209,64,3708,0.5,2,128,6
291,1762133345,22,21991ec7-24fc-46c4-9def-2d379a567e83,1762133367,1762134822,1455,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 90 --learning_rate 0.00096617893002063997 --batch_size 64 --hidden_size 3398 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c141,1209176,291_0,COMPLETED,BOTORCH_MODULAR,70.42000000000000170530256582424,90,0.000966178930020639972417462182,64,3398,0.5,2,128,6
292,1762133345,44,21991ec7-24fc-46c4-9def-2d379a567e83,1762133389,1762134849,1460,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 90 --learning_rate 0.00096786026867550152 --batch_size 64 --hidden_size 3382 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c138,1209182,292_0,COMPLETED,BOTORCH_MODULAR,69.590000000000003410605131648481,90,0.000967860268675501517719739208,64,3382,0.5,2,128,6
293,1762133347,40,21991ec7-24fc-46c4-9def-2d379a567e83,1762133387,1762134832,1445,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 89 --learning_rate 0.00096875582717372781 --batch_size 67 --hidden_size 3719 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c134,1209185,293_0,COMPLETED,BOTORCH_MODULAR,70.090000000000003410605131648481,89,0.000968755827173727805494418686,67,3719,0.5,2,128,6
294,1762133345,44,21991ec7-24fc-46c4-9def-2d379a567e83,1762133389,1762134830,1441,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 90 --learning_rate 0.00096774864413778114 --batch_size 64 --hidden_size 3392 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c138,1209180,294_0,COMPLETED,BOTORCH_MODULAR,69.57999999999999829469743417576,90,0.000967748644137781137072873427,64,3392,0.5,2,128,6
295,1762133352,37,21991ec7-24fc-46c4-9def-2d379a567e83,1762133389,1762134842,1453,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 90 --learning_rate 0.00096838256472896135 --batch_size 64 --hidden_size 3379 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c133,1209187,295_0,COMPLETED,BOTORCH_MODULAR,70.099999999999994315658113919199,90,0.000968382564728961347383373592,64,3379,0.5,2,128,6
296,1762133352,35,21991ec7-24fc-46c4-9def-2d379a567e83,1762133387,1762134833,1446,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 90 --learning_rate 0.0009700300788301814 --batch_size 64 --hidden_size 3395 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c133,1209186,296_0,COMPLETED,BOTORCH_MODULAR,69.5,90,0.000970030078830181404121735245,64,3395,0.5,2,128,6
297,1762133353,54,21991ec7-24fc-46c4-9def-2d379a567e83,1762133407,1762134817,1410,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 90 --learning_rate 0.00097056767745558 --batch_size 64 --hidden_size 3340 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c132,1209188,297_0,COMPLETED,BOTORCH_MODULAR,70.39000000000000056843418860808,90,0.00097056767745558000272387833,64,3340,0.5,2,128,6
298,1762133354,58,21991ec7-24fc-46c4-9def-2d379a567e83,1762133412,1762134761,1349,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 91 --learning_rate 0.00099654911639082537 --batch_size 77 --hidden_size 1847 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c132,1209189,298_0,COMPLETED,BOTORCH_MODULAR,69.450000000000002842170943040401,91,0.000996549116390825365577321726,77,1847,0.5,2,128,6
299,1762135575,24,21991ec7-24fc-46c4-9def-2d379a567e83,1762135599,1762140503,4904,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 313 --learning_rate 0.00064598191718641287 --batch_size 64 --hidden_size 4096 --dropout 0.39495164852561026603 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c141,1209204,299_0,COMPLETED,BOTORCH_MODULAR,70.5,313,0.000645981917186412872219913872,64,4096,0.394951648525610266027285888413,1,128,5
300,1762135577,32,21991ec7-24fc-46c4-9def-2d379a567e83,1762135609,1762136997,1388,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 88 --learning_rate 0.00070170107571948753 --batch_size 64 --hidden_size 3714 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c139,1209206,300_0,COMPLETED,BOTORCH_MODULAR,71.230000000000003979039320256561,88,0.000701701075719487533423335268,64,3714,0.5,1,128,5
301,1762135576,35,21991ec7-24fc-46c4-9def-2d379a567e83,1762135611,1762137017,1406,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 89 --learning_rate 0.00070191628538171839 --batch_size 64 --hidden_size 3412 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c139,1209205,301_0,COMPLETED,BOTORCH_MODULAR,70.67000000000000170530256582424,89,0.000701916285381718385236182733,64,3412,0.5,1,128,5
302,1762135576,33,21991ec7-24fc-46c4-9def-2d379a567e83,1762135609,1762136948,1339,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 88 --learning_rate 0.00070233698833535867 --batch_size 64 --hidden_size 2256 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c138,1209208,302_0,COMPLETED,BOTORCH_MODULAR,70.810000000000002273736754432321,88,0.000702336988335358668525398862,64,2256,0.5,1,128,5
303,1762135578,61,21991ec7-24fc-46c4-9def-2d379a567e83,1762135639,1762136869,1230,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 88 --learning_rate 0.00071956027853531943 --batch_size 110 --hidden_size 3124 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c134,1209213,303_0,COMPLETED,BOTORCH_MODULAR,70.269999999999996020960679743439,88,0.000719560278535319431357508702,110,3124,0.5,1,128,5
304,1762135575,4,21991ec7-24fc-46c4-9def-2d379a567e83,1762135579,1762136950,1371,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 88 --learning_rate 0.00070283636766320715 --batch_size 64 --hidden_size 2940 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c151,1209200,304_0,COMPLETED,BOTORCH_MODULAR,70.680000000000006821210263296962,88,0.000702836367663207148108461819,64,2940,0.5,1,128,5
305,1762135577,35,21991ec7-24fc-46c4-9def-2d379a567e83,1762135612,1762140561,4949,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 313 --learning_rate 0.00064683202080762794 --batch_size 64 --hidden_size 4096 --dropout 0.3912013706396940127 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c139,1209207,305_0,COMPLETED,BOTORCH_MODULAR,70.42000000000000170530256582424,313,0.000646832020807627935607420078,64,4096,0.391201370639694012698583946985,1,128,5
306,1762135578,61,21991ec7-24fc-46c4-9def-2d379a567e83,1762135639,1762137033,1394,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 89 --learning_rate 0.00070115565570951356 --batch_size 64 --hidden_size 3555 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c135,1209212,306_0,COMPLETED,BOTORCH_MODULAR,71.549999999999997157829056959599,89,0.000701155655709513559933898641,64,3555,0.5,1,128,5
307,1762135575,5,21991ec7-24fc-46c4-9def-2d379a567e83,1762135580,1762136911,1331,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 89 --learning_rate 0.00069742318911778076 --batch_size 64 --hidden_size 990 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c143,1209202,307_0,COMPLETED,BOTORCH_MODULAR,70.049999999999997157829056959599,89,0.000697423189117780755429121253,64,990,0.5,1,128,5
308,1762135576,24,21991ec7-24fc-46c4-9def-2d379a567e83,1762135600,1762137005,1405,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 89 --learning_rate 0.00070088237957848843 --batch_size 64 --hidden_size 3867 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c141,1209203,308_0,COMPLETED,BOTORCH_MODULAR,70.900000000000005684341886080801,89,0.000700882379578488434908323246,64,3867,0.5,1,128,5
309,1762135577,42,21991ec7-24fc-46c4-9def-2d379a567e83,1762135619,1762136851,1232,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 90 --learning_rate 0.00071788424001952456 --batch_size 112 --hidden_size 2259 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c138,1209210,309_0,COMPLETED,BOTORCH_MODULAR,69.92000000000000170530256582424,90,0.000717884240019524559779651174,112,2259,0.5,1,128,5
310,1762135578,61,21991ec7-24fc-46c4-9def-2d379a567e83,1762135639,1762137032,1393,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 89 --learning_rate 0.00070145091670381057 --batch_size 64 --hidden_size 3712 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c133,1209214,310_0,COMPLETED,BOTORCH_MODULAR,70.629999999999995452526491135359,89,0.000701450916703810572160049386,64,3712,0.5,1,128,5
311,1762135578,41,21991ec7-24fc-46c4-9def-2d379a567e83,1762135619,1762137004,1385,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 88 --learning_rate 0.00070168178454183905 --batch_size 64 --hidden_size 3720 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c138,1209209,311_0,COMPLETED,BOTORCH_MODULAR,70.689999999999997726263245567679,88,0.00070168178454183905215502115,64,3720,0.5,1,128,5
312,1762135575,4,21991ec7-24fc-46c4-9def-2d379a567e83,1762135579,1762136851,1272,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 85 --learning_rate 0.00070034561174555558 --batch_size 64 --hidden_size 1507 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c143,1209201,312_0,COMPLETED,BOTORCH_MODULAR,70.75,85,0.000700345611745555583250999465,64,1507,0.5,1,128,5
313,1762135578,66,21991ec7-24fc-46c4-9def-2d379a567e83,1762135644,1762139107,3463,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 221 --learning_rate 0.00077655206420373078 --batch_size 64 --hidden_size 4096 --dropout 0.22594263759706373351 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c133,1209215,313_0,COMPLETED,BOTORCH_MODULAR,71.14000000000000056843418860808,221,0.000776552064203730779863577016,64,4096,0.225942637597063733512214867005,1,128,5
314,1762135577,42,21991ec7-24fc-46c4-9def-2d379a567e83,1762135619,1762136963,1344,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 88 --learning_rate 0.00070197473402581719 --batch_size 64 --hidden_size 2739 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c137,1209211,314_0,COMPLETED,BOTORCH_MODULAR,70.700000000000002842170943040401,88,0.000701974734025817190784246602,64,2739,0.5,1,128,5
315,1762135584,80,21991ec7-24fc-46c4-9def-2d379a567e83,1762135664,1762137041,1377,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 89 --learning_rate 0.0007013836378847488 --batch_size 64 --hidden_size 3713 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c132,1209216,315_0,COMPLETED,BOTORCH_MODULAR,70.96999999999999886313162278384,89,0.000701383637884748795815470501,64,3713,0.5,1,128,5
316,1762135584,75,21991ec7-24fc-46c4-9def-2d379a567e83,1762135659,1762137061,1402,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 88 --learning_rate 0.00070049863549826146 --batch_size 64 --hidden_size 3871 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c132,1209217,316_0,COMPLETED,BOTORCH_MODULAR,71.069999999999993178789736703038,88,0.000700498635498261463909475122,64,3871,0.5,1,128,5
317,1762135584,77,21991ec7-24fc-46c4-9def-2d379a567e83,1762135661,1762137034,1373,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 88 --learning_rate 0.00070129605038929345 --batch_size 64 --hidden_size 3782 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c132,1209218,317_0,COMPLETED,BOTORCH_MODULAR,71.42000000000000170530256582424,88,0.000701296050389293447978322771,64,3782,0.5,1,128,5
318,1762135589,70,21991ec7-24fc-46c4-9def-2d379a567e83,1762135659,1762137050,1391,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 89 --learning_rate 0.00070170765607060885 --batch_size 64 --hidden_size 3708 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c131,1209219,318_0,COMPLETED,BOTORCH_MODULAR,71.46999999999999886313162278384,89,0.00070170765607060884595791439,64,3708,0.5,1,128,5
319,1762140929,47,21991ec7-24fc-46c4-9def-2d379a567e83,1762140976,1762142322,1346,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 86 --learning_rate 0.00066435434621540024 --batch_size 64 --hidden_size 3612 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 7,0,,c143,1209227,319_0,COMPLETED,BOTORCH_MODULAR,68.900000000000005684341886080801,86,0.000664354346215400236828896308,64,3612,0.5,1,128,7
320,1762140929,43,21991ec7-24fc-46c4-9def-2d379a567e83,1762140972,1762144203,3231,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 212 --learning_rate 0.00076558095998121862 --batch_size 64 --hidden_size 3837 --dropout 0.34129697316713980548 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c145,1209226,320_0,COMPLETED,BOTORCH_MODULAR,69.989999999999994884092302527279,212,0.000765580959981218621239473787,64,3837,0.341296973167139805482861447672,1,128,6
321,1762140927,5,21991ec7-24fc-46c4-9def-2d379a567e83,1762140932,1762142356,1424,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 91 --learning_rate 0.00066256286129410429 --batch_size 64 --hidden_size 4096 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 7,0,,c151,1209223,321_0,COMPLETED,BOTORCH_MODULAR,68.939999999999997726263245567679,91,0.000662562861294104291608186852,64,4096,0.5,1,128,7
322,1762140931,59,21991ec7-24fc-46c4-9def-2d379a567e83,1762140990,1762144102,3112,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 206 --learning_rate 0.00077059421885107289 --batch_size 64 --hidden_size 2417 --dropout 0.3168975116841454831 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c139,1209231,322_0,COMPLETED,BOTORCH_MODULAR,70.159999999999996589394868351519,206,0.000770594218851072885849429195,64,2417,0.316897511684145483101815443661,1,128,6
323,1762140930,71,21991ec7-24fc-46c4-9def-2d379a567e83,1762141001,1762144189,3188,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 211 --learning_rate 0.0007657805519147128 --batch_size 64 --hidden_size 3553 --dropout 0.33863438515453753164 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c138,1209235,323_0,COMPLETED,BOTORCH_MODULAR,70.21999999999999886313162278384,211,0.000765780551914712801463147596,64,3553,0.338634385154537531636975700167,1,128,6
324,1762140929,42,21991ec7-24fc-46c4-9def-2d379a567e83,1762140971,1762142388,1417,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 91 --learning_rate 0.0006630236820207051 --batch_size 64 --hidden_size 3940 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 7,0,,c141,1209229,324_0,COMPLETED,BOTORCH_MODULAR,69.230000000000003979039320256561,91,0.00066302368202070510044832119,64,3940,0.5,1,128,7
325,1762140929,42,21991ec7-24fc-46c4-9def-2d379a567e83,1762140971,1762142342,1371,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 91 --learning_rate 0.00068608337963003735 --batch_size 72 --hidden_size 812 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 7,0,,c143,1209228,325_0,COMPLETED,BOTORCH_MODULAR,69.629999999999995452526491135359,91,0.000686083379630037350563331877,72,812,0.5,1,128,7
326,1762140927,5,21991ec7-24fc-46c4-9def-2d379a567e83,1762140932,1762142345,1413,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 91 --learning_rate 0.00067145251230700856 --batch_size 64 --hidden_size 2170 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 7,0,,c152,1209222,326_0,COMPLETED,BOTORCH_MODULAR,69.60999999999999943156581139192,91,0.000671452512307008564026999942,64,2170,0.5,1,128,7
327,1762140931,57,21991ec7-24fc-46c4-9def-2d379a567e83,1762140988,1762142413,1425,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 92 --learning_rate 0.00066973277696580119 --batch_size 64 --hidden_size 2476 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 7,0,,c139,1209234,327_0,COMPLETED,BOTORCH_MODULAR,69.260000000000005115907697472721,92,0.000669732776965801190026394973,64,2476,0.5,1,128,7
328,1762140927,5,21991ec7-24fc-46c4-9def-2d379a567e83,1762140932,1762146973,6041,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 364 --learning_rate 0.00044057680880876625 --batch_size 64 --hidden_size 4088 --dropout 0.5 --num_dense_layers 1 --filter 109 --num_conv_layers 5,0,,c153,1209221,328_0,COMPLETED,BOTORCH_MODULAR,69.489999999999994884092302527279,364,0.000440576808808766250038363443,64,4088,0.5,1,109,5
329,1762140928,23,21991ec7-24fc-46c4-9def-2d379a567e83,1762140951,1762144132,3181,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 212 --learning_rate 0.00076375013467914706 --batch_size 64 --hidden_size 4096 --dropout 0.3411606539260652049 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c148,1209225,329_0,COMPLETED,BOTORCH_MODULAR,69.819999999999993178789736703038,212,0.000763750134679147063901383241,64,4096,0.341160653926065204899487071089,1,128,6
330,1762140931,57,21991ec7-24fc-46c4-9def-2d379a567e83,1762140988,1762142390,1402,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 94 --learning_rate 0.00068071970969857864 --batch_size 80 --hidden_size 2811 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 7,0,,c139,1209232,330_0,COMPLETED,BOTORCH_MODULAR,68.769999999999996020960679743439,94,0.000680719709698578644661848269,80,2811,0.5,1,128,7
331,1762140930,58,21991ec7-24fc-46c4-9def-2d379a567e83,1762140988,1762142475,1487,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 95 --learning_rate 0.00066246959944007229 --batch_size 64 --hidden_size 3719 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 7,0,,c139,1209233,331_0,COMPLETED,BOTORCH_MODULAR,69.879999999999995452526491135359,95,0.000662469599440072289507630554,64,3719,0.5,1,128,7
332,1762140927,23,21991ec7-24fc-46c4-9def-2d379a567e83,1762140950,1762144465,3515,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 212 --learning_rate 0.00076366446991625592 --batch_size 64 --hidden_size 4096 --dropout 0.34489798120831322015 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c148,1209224,332_0,COMPLETED,BOTORCH_MODULAR,70.239999999999994884092302527279,212,0.000763664469916255916892566802,64,4096,0.344897981208313220147232414092,1,128,6
333,1762140930,42,21991ec7-24fc-46c4-9def-2d379a567e83,1762140972,1762144046,3074,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 207 --learning_rate 0.00077309628156252842 --batch_size 64 --hidden_size 2372 --dropout 0.31549586505936016989 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c141,1209230,333_0,COMPLETED,BOTORCH_MODULAR,69.989999999999994884092302527279,207,0.000773096281562528418566937471,64,2372,0.315495865059360169890823044625,1,128,6
334,1762140932,78,21991ec7-24fc-46c4-9def-2d379a567e83,1762141010,1762146578,5568,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 362 --learning_rate 0.00043584895244400075 --batch_size 64 --hidden_size 4096 --dropout 0.5 --num_dense_layers 1 --filter 108 --num_conv_layers 5,0,,c138,1209236,334_0,COMPLETED,BOTORCH_MODULAR,69.519999999999996020960679743439,362,0.000435848952444000748481650609,64,4096,0.5,1,108,5
335,1762140937,73,21991ec7-24fc-46c4-9def-2d379a567e83,1762141010,1762142341,1331,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 89 --learning_rate 0.00067598774885901025 --batch_size 72 --hidden_size 2354 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 7,0,,c138,1209237,335_0,COMPLETED,BOTORCH_MODULAR,69.049999999999997157829056959599,89,0.000675987748859010247753920098,72,2354,0.5,1,128,7
336,1762140937,73,21991ec7-24fc-46c4-9def-2d379a567e83,1762141010,1762142471,1461,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 96 --learning_rate 0.00067694610153648104 --batch_size 64 --hidden_size 1321 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 7,0,,c137,1209239,336_0,COMPLETED,BOTORCH_MODULAR,69.03000000000000113686837721616,96,0.000676946101536481039014081507,64,1321,0.5,1,128,7
337,1762140937,72,21991ec7-24fc-46c4-9def-2d379a567e83,1762141009,1762142376,1367,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 90 --learning_rate 0.00066282944704454806 --batch_size 71 --hidden_size 3942 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 7,0,,c138,1209238,337_0,COMPLETED,BOTORCH_MODULAR,69.629999999999995452526491135359,90,0.000662829447044548060105628728,71,3942,0.5,1,128,7
338,1762140941,68,21991ec7-24fc-46c4-9def-2d379a567e83,1762141009,1762144324,3315,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 221 --learning_rate 0.00076333442997457846 --batch_size 64 --hidden_size 3812 --dropout 0.34937345423584847959 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c137,1209240,338_0,COMPLETED,BOTORCH_MODULAR,69.980000000000003979039320256561,221,0.000763334429974578464010714907,64,3812,0.349373454235848479587644987987,1,128,6
339,1762147329,40,21991ec7-24fc-46c4-9def-2d379a567e83,1762147369,1762148811,1442,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 90 --learning_rate 0.00086632081784036874 --batch_size 64 --hidden_size 3951 --dropout 0.32002905647761659136 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c143,1209254,339_0,COMPLETED,BOTORCH_MODULAR,70.689999999999997726263245567679,90,0.000866320817840368737235146046,64,3951,0.320029056477616591358525965916,1,128,5
340,1762147328,42,21991ec7-24fc-46c4-9def-2d379a567e83,1762147370,1762148770,1400,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 96 --learning_rate 0.00091735387260667462 --batch_size 64 --hidden_size 636 --dropout 0.17076472595364902696 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c147,1209249,340_0,COMPLETED,BOTORCH_MODULAR,69.629999999999995452526491135359,96,0.000917353872606674618402078369,64,636,0.170764725953649026957137380123,1,128,5
341,1762147328,24,21991ec7-24fc-46c4-9def-2d379a567e83,1762147352,1762150167,2815,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 180 --learning_rate 0.00093188654992816652 --batch_size 64 --hidden_size 3241 --dropout 0.19770818500863049372 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c148,1209247,341_0,COMPLETED,BOTORCH_MODULAR,70.549999999999997157829056959599,180,0.000931886549928166523469597049,64,3241,0.197708185008630493717518561425,1,128,5
342,1762147328,4,21991ec7-24fc-46c4-9def-2d379a567e83,1762147332,1762150353,3021,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 183 --learning_rate 0.00091930313165986791 --batch_size 64 --hidden_size 4096 --dropout 0.23593296223741996864 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c153,1209241,342_0,COMPLETED,BOTORCH_MODULAR,70.090000000000003410605131648481,183,0.000919303131659867907646277452,64,4096,0.235932962237419968642981871199,1,128,5
343,1762147329,42,21991ec7-24fc-46c4-9def-2d379a567e83,1762147371,1762149275,1904,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 120 --learning_rate 0.00088490516384972422 --batch_size 64 --hidden_size 3629 --dropout 0.18002978254104776146 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c147,1209248,343_0,COMPLETED,BOTORCH_MODULAR,70.950000000000002842170943040401,120,0.000884905163849724219621295518,64,3629,0.180029782541047761457164710919,1,128,5
344,1762147329,40,21991ec7-24fc-46c4-9def-2d379a567e83,1762147369,1762150032,2663,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 170 --learning_rate 0.0009063828339815409 --batch_size 64 --hidden_size 3928 --dropout 0.18799941927757790605 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c141,1209256,344_0,COMPLETED,BOTORCH_MODULAR,70.89000000000000056843418860808,170,0.000906382833981540900376849823,64,3928,0.1879994192775779060511354146,1,128,5
345,1762147328,23,21991ec7-24fc-46c4-9def-2d379a567e83,1762147351,1762148715,1364,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 90 --learning_rate 0.00087667954839534953 --batch_size 81 --hidden_size 3715 --dropout 0.29822704619364581724 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c151,1209244,345_0,COMPLETED,BOTORCH_MODULAR,70.430000000000006821210263296962,90,0.000876679548395349530348630296,81,3715,0.298227046193645817240280848637,1,128,5
346,1762147328,43,21991ec7-24fc-46c4-9def-2d379a567e83,1762147371,1762150133,2762,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 177 --learning_rate 0.00092491463598189832 --batch_size 64 --hidden_size 3091 --dropout 0.18156156840261514218 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c141,1209255,346_0,COMPLETED,BOTORCH_MODULAR,70.209999999999993747223925311118,177,0.000924914635981898317594607217,64,3091,0.181561568402615142181488749884,1,128,5
347,1762147328,24,21991ec7-24fc-46c4-9def-2d379a567e83,1762147352,1762148782,1430,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 90 --learning_rate 0.00086740372761561922 --batch_size 64 --hidden_size 4096 --dropout 0.3294947954724469219 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c149,1209245,347_0,COMPLETED,BOTORCH_MODULAR,70.730000000000003979039320256561,90,0.000867403727615619220790710298,64,4096,0.32949479547244692190233195106,1,128,5
348,1762147328,12,21991ec7-24fc-46c4-9def-2d379a567e83,1762147340,1762148678,1338,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 84 --learning_rate 0.0008790878819948828 --batch_size 64 --hidden_size 3235 --dropout 0.31600649941971103996 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c152,1209242,348_0,COMPLETED,BOTORCH_MODULAR,70.730000000000003979039320256561,84,0.000879087881994882803550483974,64,3235,0.316006499419711039955416254088,1,128,5
349,1762147329,41,21991ec7-24fc-46c4-9def-2d379a567e83,1762147370,1762148732,1362,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 90 --learning_rate 0.00089324334694752881 --batch_size 64 --hidden_size 2066 --dropout 0.25570027986457305458 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c146,1209251,349_0,COMPLETED,BOTORCH_MODULAR,70.370000000000004547473508864641,90,0.000893243346947528811183292241,64,2066,0.255700279864573054577903121753,1,128,5
350,1762147329,45,21991ec7-24fc-46c4-9def-2d379a567e83,1762147374,1762150247,2873,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 183 --learning_rate 0.0009225846105641336 --batch_size 64 --hidden_size 4005 --dropout 0.22470301147706187028 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c143,1209253,350_0,COMPLETED,BOTORCH_MODULAR,70.590000000000003410605131648481,183,0.000922584610564133596015412575,64,4005,0.224703011477061870282412314737,1,128,5
351,1762147329,46,21991ec7-24fc-46c4-9def-2d379a567e83,1762147375,1762148817,1442,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 90 --learning_rate 0.00086517351074713329 --batch_size 64 --hidden_size 4096 --dropout 0.33204549001098809802 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c146,1209250,351_0,COMPLETED,BOTORCH_MODULAR,70.909999999999996589394868351519,90,0.00086517351074713328556997638,64,4096,0.332045490010988098017463698852,1,128,5
352,1762147328,42,21991ec7-24fc-46c4-9def-2d379a567e83,1762147370,1762148826,1456,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 90 --learning_rate 0.00087307320738851026 --batch_size 64 --hidden_size 3567 --dropout 0.30023986509974270875 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c145,1209252,352_0,COMPLETED,BOTORCH_MODULAR,70.5,90,0.000873073207388510262594305544,64,3567,0.300239865099742708753893793983,1,128,5
353,1762147328,12,21991ec7-24fc-46c4-9def-2d379a567e83,1762147340,1762148776,1436,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 90 --learning_rate 0.00086921662671167845 --batch_size 64 --hidden_size 4096 --dropout 0.32168622922010531306 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c151,1209243,353_0,COMPLETED,BOTORCH_MODULAR,71.090000000000003410605131648481,90,0.000869216626711678450566134213,64,4096,0.32168622922010531306469260926,1,128,5
354,1762147328,24,21991ec7-24fc-46c4-9def-2d379a567e83,1762147352,1762149660,2308,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 130 --learning_rate 0.00087886606896921745 --batch_size 64 --hidden_size 4005 --dropout 0.1722365821600235769 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c148,1209246,354_0,COMPLETED,BOTORCH_MODULAR,70.409999999999996589394868351519,130,0.000878866068969217447033603907,64,4005,0.172236582160023576903995490284,1,128,5
355,1762147331,40,21991ec7-24fc-46c4-9def-2d379a567e83,1762147371,1762148814,1443,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 90 --learning_rate 0.00087099316387363366 --batch_size 64 --hidden_size 4096 --dropout 0.33757320258717660177 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c141,1209257,355_0,COMPLETED,BOTORCH_MODULAR,71.090000000000003410605131648481,90,0.000870993163873633657531825314,64,4096,0.337573202587176601774388018384,1,128,5
356,1762147338,55,21991ec7-24fc-46c4-9def-2d379a567e83,1762147393,1762148753,1360,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 93 --learning_rate 0.00090290572633702965 --batch_size 64 --hidden_size 1267 --dropout 0.21722637438262770715 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c140,1209258,356_0,COMPLETED,BOTORCH_MODULAR,70.25,93,0.000902905726337029654673949075,64,1267,0.217226374382627707149140405818,1,128,5
357,1762147338,53,21991ec7-24fc-46c4-9def-2d379a567e83,1762147391,1762148793,1402,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 91 --learning_rate 0.00089604199196440524 --batch_size 64 --hidden_size 2111 --dropout 0.25917023720114085172 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c140,1209259,357_0,COMPLETED,BOTORCH_MODULAR,70.730000000000003979039320256561,91,0.000896041991964405238300928058,64,2111,0.259170237201140851723835112352,1,128,5
358,1762147342,63,21991ec7-24fc-46c4-9def-2d379a567e83,1762147405,1762148841,1436,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 90 --learning_rate 0.00086513351213555556 --batch_size 64 --hidden_size 4010 --dropout 0.32214743523089772737 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c139,1209260,358_0,COMPLETED,BOTORCH_MODULAR,71.25,90,0.000865133512135555561052557838,64,4010,0.322147435230897727365118043963,1,128,5
359,1762150771,42,21991ec7-24fc-46c4-9def-2d379a567e83,1762150813,1762156663,5850,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 500 --learning_rate 0.00100000000000000002 --batch_size 320 --hidden_size 4096 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c143,1209276,359_0,COMPLETED,BOTORCH_MODULAR,68.040000000000006252776074688882,500,0.001000000000000000020816681712,320,4096,0.5,1,128,5
360,1762150768,22,21991ec7-24fc-46c4-9def-2d379a567e83,1762150790,1762155698,4908,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 294 --learning_rate 0.00080126081311429468 --batch_size 64 --hidden_size 4096 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 5,0,,c152,1209264,360_0,COMPLETED,BOTORCH_MODULAR,69.980000000000003979039320256561,294,0.000801260813114294681916427443,64,4096,0.5,2,128,5
361,1762150770,20,21991ec7-24fc-46c4-9def-2d379a567e83,1762150790,1762155765,4975,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 300 --learning_rate 0.00085230752093734151 --batch_size 64 --hidden_size 3630 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 5,0,,c147,1209271,361_0,COMPLETED,BOTORCH_MODULAR,69.769999999999996020960679743439,300,0.000852307520937341505512518935,64,3630,0.5,2,128,5
362,1762150769,21,21991ec7-24fc-46c4-9def-2d379a567e83,1762150790,1762153337,2547,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 169 --learning_rate 0.00073989136374811768 --batch_size 64 --hidden_size 3127 --dropout 0 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c148,1209270,362_0,COMPLETED,BOTORCH_MODULAR,67.35999999999999943156581139192,169,0.000739891363748117680473881386,64,3127,0,1,128,6
363,1762150768,22,21991ec7-24fc-46c4-9def-2d379a567e83,1762150790,1762156095,5305,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 311 --learning_rate 0.00084977703890365647 --batch_size 64 --hidden_size 3923 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 5,0,,c151,1209267,363_0,COMPLETED,BOTORCH_MODULAR,69.60999999999999943156581139192,311,0.000849777038903656465815283916,64,3923,0.5,2,128,5
364,1762150768,4,21991ec7-24fc-46c4-9def-2d379a567e83,1762150772,1762155662,4890,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 276 --learning_rate 0.00075099152088001935 --batch_size 64 --hidden_size 4096 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 5,0,,c153,1209263,364_0,COMPLETED,BOTORCH_MODULAR,70.239999999999994884092302527279,276,0.00075099152088001935347050253,64,4096,0.5,2,128,5
365,1762150768,22,21991ec7-24fc-46c4-9def-2d379a567e83,1762150790,1762155934,5144,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 304 --learning_rate 0.00082286404498499877 --batch_size 64 --hidden_size 4096 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 5,0,,c152,1209265,365_0,COMPLETED,BOTORCH_MODULAR,70.200000000000002842170943040401,304,0.000822864044984998772858109106,64,4096,0.5,2,128,5
366,1762150770,42,21991ec7-24fc-46c4-9def-2d379a567e83,1762150812,1762155882,5070,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 307 --learning_rate 0.00086335488488918947 --batch_size 64 --hidden_size 3630 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 5,0,,c146,1209274,366_0,COMPLETED,BOTORCH_MODULAR,69.519999999999996020960679743439,307,0.000863354884889189471558479383,64,3630,0.5,2,128,5
367,1762150769,22,21991ec7-24fc-46c4-9def-2d379a567e83,1762150791,1762157728,6937,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 445 --learning_rate 0.000895125239834948 --batch_size 64 --hidden_size 3802 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c151,1209266,367_0,COMPLETED,BOTORCH_MODULAR,71.340000000000003410605131648481,445,0.000895125239834947995787306496,64,3802,0.5,1,128,5
368,1762150771,41,21991ec7-24fc-46c4-9def-2d379a567e83,1762150812,1762152226,1414,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 88 --learning_rate 0.00084100438789535615 --batch_size 64 --hidden_size 3826 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c145,1209275,368_0,COMPLETED,BOTORCH_MODULAR,71.21999999999999886313162278384,88,0.000841004387895356148550918274,64,3826,0.5,1,128,5
369,1762150770,41,21991ec7-24fc-46c4-9def-2d379a567e83,1762150811,1762152850,2039,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 134 --learning_rate 0.00084326881206477067 --batch_size 64 --hidden_size 976 --dropout 0 --num_dense_layers 1 --filter 128 --num_conv_layers 7,0,,c147,1209272,369_0,COMPLETED,BOTORCH_MODULAR,66.82999999999999829469743417576,134,0.000843268812064770670149094212,64,976,0,1,128,7
370,1762150772,39,21991ec7-24fc-46c4-9def-2d379a567e83,1762150811,1762156836,6025,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 399 --learning_rate 0.00065973576322090547 --batch_size 64 --hidden_size 4096 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c141,1209278,370_0,COMPLETED,BOTORCH_MODULAR,69.879999999999995452526491135359,399,0.00065973576322090547296300711,64,4096,0.5,1,128,6
371,1762150770,43,21991ec7-24fc-46c4-9def-2d379a567e83,1762150813,1762155892,5079,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 304 --learning_rate 0.00083463812161458175 --batch_size 64 --hidden_size 3974 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 5,0,,c146,1209273,371_0,COMPLETED,BOTORCH_MODULAR,69.840000000000003410605131648481,304,0.000834638121614581754599548891,64,3974,0.5,2,128,5
372,1762150769,21,21991ec7-24fc-46c4-9def-2d379a567e83,1762150790,1762152543,1753,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 116 --learning_rate 0.00077109471502528578 --batch_size 64 --hidden_size 3953 --dropout 0.27566336173847516555 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c149,1209268,372_0,COMPLETED,BOTORCH_MODULAR,69.310000000000002273736754432321,116,0.000771094715025285779540220599,64,3953,0.275663361738475165552131329605,1,128,6
373,1762150769,23,21991ec7-24fc-46c4-9def-2d379a567e83,1762150792,1762158423,7631,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 438 --learning_rate 0.00085515229216550444 --batch_size 64 --hidden_size 4096 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c148,1209269,373_0,COMPLETED,BOTORCH_MODULAR,70.92000000000000170530256582424,438,0.000855152292165504437047862663,64,4096,0.5,1,128,5
374,1762150771,40,21991ec7-24fc-46c4-9def-2d379a567e83,1762150811,1762157892,7081,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 446 --learning_rate 0.00085259427103798766 --batch_size 64 --hidden_size 4013 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c143,1209277,374_0,COMPLETED,BOTORCH_MODULAR,71.200000000000002842170943040401,446,0.00085259427103798765632675094,64,4013,0.5,1,128,5
375,1762150778,33,21991ec7-24fc-46c4-9def-2d379a567e83,1762150811,1762157723,6912,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 438 --learning_rate 0.00083172756102225414 --batch_size 64 --hidden_size 4096 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c141,1209279,375_0,COMPLETED,BOTORCH_MODULAR,71.10999999999999943156581139192,438,0.000831727561022254139287690489,64,4096,0.5,1,128,5
376,1762150778,41,21991ec7-24fc-46c4-9def-2d379a567e83,1762150819,1762157873,7054,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 444 --learning_rate 0.00084468674875366235 --batch_size 64 --hidden_size 3958 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c141,1209280,376_0,COMPLETED,BOTORCH_MODULAR,70.709999999999993747223925311118,444,0.000844686748753662353279836328,64,3958,0.5,1,128,5
377,1762150778,44,21991ec7-24fc-46c4-9def-2d379a567e83,1762150822,1762156567,5745,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 387 --learning_rate 0.00066576216081062727 --batch_size 64 --hidden_size 4024 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c140,1209281,377_0,COMPLETED,BOTORCH_MODULAR,70.75,387,0.000665762160810627265372652062,64,4024,0.5,1,128,6
378,1762150781,38,21991ec7-24fc-46c4-9def-2d379a567e83,1762150819,1762158116,7297,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 462 --learning_rate 0.00080971346055110885 --batch_size 64 --hidden_size 4096 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c140,1209282,378_0,COMPLETED,BOTORCH_MODULAR,71.60999999999999943156581139192,462,0.000809713460551108850718482479,64,4096,0.5,1,128,5
379,1762158919,34,21991ec7-24fc-46c4-9def-2d379a567e83,1762158953,1762160594,1641,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 104 --learning_rate 0.00089616512364746193 --batch_size 64 --hidden_size 3236 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c143,1209339,379_0,COMPLETED,BOTORCH_MODULAR,71.60999999999999943156581139192,104,0.000896165123647461934856817134,64,3236,0.5,1,128,5
380,1762158919,23,21991ec7-24fc-46c4-9def-2d379a567e83,1762158942,1762163465,4523,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 292 --learning_rate 0.00056404638303713176 --batch_size 64 --hidden_size 3360 --dropout 0.5 --num_dense_layers 1 --filter 91 --num_conv_layers 5,0,,c152,1209333,380_0,COMPLETED,BOTORCH_MODULAR,69.64000000000000056843418860808,292,0.000564046383037131757003102006,64,3360,0.5,1,91,5
381,1762158920,24,21991ec7-24fc-46c4-9def-2d379a567e83,1762158944,1762166270,7326,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 465 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 4096 --dropout 0.38873451420504995246 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c148,1209337,381_0,COMPLETED,BOTORCH_MODULAR,71.069999999999993178789736703038,465,0.001000000000000000020816681712,64,4096,0.388734514205049952462189821745,1,128,5
382,1762158920,67,21991ec7-24fc-46c4-9def-2d379a567e83,1762158987,1762166272,7285,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 461 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 4096 --dropout 0.38668623657621958856 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c140,1209344,382_0,COMPLETED,BOTORCH_MODULAR,71.150000000000005684341886080801,461,0.001000000000000000020816681712,64,4096,0.386686236576219588556568851345,1,128,5
383,1762158920,62,21991ec7-24fc-46c4-9def-2d379a567e83,1762158982,1762166178,7196,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 460 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 4096 --dropout 0.37345587437923633001 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c140,1209343,383_0,COMPLETED,BOTORCH_MODULAR,71.370000000000004547473508864641,460,0.001000000000000000020816681712,64,4096,0.373455874379236330007358901639,1,128,5
384,1762158920,62,21991ec7-24fc-46c4-9def-2d379a567e83,1762158982,1762160575,1593,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 100 --learning_rate 0.00087747598793633469 --batch_size 64 --hidden_size 4096 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c141,1209342,384_0,COMPLETED,BOTORCH_MODULAR,70.659999999999996589394868351519,100,0.000877475987936334692746109809,64,4096,0.5,1,128,5
385,1762158919,4,21991ec7-24fc-46c4-9def-2d379a567e83,1762158923,1762160656,1733,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 112 --learning_rate 0.00091247843284195259 --batch_size 64 --hidden_size 3010 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c152,1209332,385_0,COMPLETED,BOTORCH_MODULAR,71.21999999999999886313162278384,112,0.000912478432841952588269740509,64,3010,0.5,1,128,5
386,1762158920,73,21991ec7-24fc-46c4-9def-2d379a567e83,1762158993,1762166219,7226,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 463 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 3174 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c139,1209347,386_0,COMPLETED,BOTORCH_MODULAR,70.75,463,0.001000000000000000020816681712,64,3174,0.5,1,128,5
387,1762158919,43,21991ec7-24fc-46c4-9def-2d379a567e83,1762158962,1762160736,1774,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 113 --learning_rate 0.00090167133283833149 --batch_size 64 --hidden_size 3700 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c141,1209340,387_0,COMPLETED,BOTORCH_MODULAR,71.049999999999997157829056959599,113,0.000901671332838331488282457293,64,3700,0.5,1,128,5
388,1762158921,62,21991ec7-24fc-46c4-9def-2d379a567e83,1762158983,1762160632,1649,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 107 --learning_rate 0.00092662737615436435 --batch_size 64 --hidden_size 2768 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c141,1209341,388_0,COMPLETED,BOTORCH_MODULAR,71.620000000000004547473508864641,107,0.000926627376154364346821923348,64,2768,0.5,1,128,5
389,1762158919,24,21991ec7-24fc-46c4-9def-2d379a567e83,1762158943,1762160565,1622,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 100 --learning_rate 0.00087131688376929594 --batch_size 64 --hidden_size 4059 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c151,1209335,389_0,COMPLETED,BOTORCH_MODULAR,70.5,100,0.00087131688376929593547320918,64,4059,0.5,1,128,5
390,1762158918,25,21991ec7-24fc-46c4-9def-2d379a567e83,1762158943,1762167182,8239,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 462 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 4096 --dropout 0.37849505033484276417 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c148,1209336,390_0,COMPLETED,BOTORCH_MODULAR,70.689999999999997726263245567679,462,0.001000000000000000020816681712,64,4096,0.378495050334842764172549323121,1,128,5
391,1762158920,22,21991ec7-24fc-46c4-9def-2d379a567e83,1762158942,1762160550,1608,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 101 --learning_rate 0.00088085635861983431 --batch_size 64 --hidden_size 4001 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c143,1209338,391_0,COMPLETED,BOTORCH_MODULAR,70.39000000000000056843418860808,101,0.000880856358619834306153406622,64,4001,0.5,1,128,5
392,1762158920,71,21991ec7-24fc-46c4-9def-2d379a567e83,1762158991,1762162359,3368,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 215 --learning_rate 0.00065419054460040917 --batch_size 64 --hidden_size 3012 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c139,1209345,392_0,COMPLETED,BOTORCH_MODULAR,70.430000000000006821210263296962,215,0.000654190544600409171725752255,64,3012,0.5,1,128,5
393,1762158919,24,21991ec7-24fc-46c4-9def-2d379a567e83,1762158943,1762160566,1623,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 103 --learning_rate 0.00089475578425245845 --batch_size 64 --hidden_size 3443 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c151,1209334,393_0,COMPLETED,BOTORCH_MODULAR,70.900000000000005684341886080801,103,0.000894755784252458446700884132,64,3443,0.5,1,128,5
394,1762158921,70,21991ec7-24fc-46c4-9def-2d379a567e83,1762158991,1762162061,3070,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 190 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 4096 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c139,1209346,394_0,COMPLETED,BOTORCH_MODULAR,71.269999999999996020960679743439,190,0.001000000000000000020816681712,64,4096,0.5,1,128,5
395,1762158923,66,21991ec7-24fc-46c4-9def-2d379a567e83,1762158989,1762160949,1960,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 124 --learning_rate 0.00093831256148174257 --batch_size 64 --hidden_size 3360 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c138,1209349,395_0,COMPLETED,BOTORCH_MODULAR,70.989999999999994884092302527279,124,0.000938312561481742567551234124,64,3360,0.5,1,128,5
396,1762158927,64,21991ec7-24fc-46c4-9def-2d379a567e83,1762158991,1762165514,6523,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 416 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 4096 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c139,1209348,396_0,COMPLETED,BOTORCH_MODULAR,71.159999999999996589394868351519,416,0.001000000000000000020816681712,64,4096,0.5,1,128,5
397,1762158937,65,21991ec7-24fc-46c4-9def-2d379a567e83,1762159002,1762165304,6302,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 404 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 4096 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c138,1209351,397_0,COMPLETED,BOTORCH_MODULAR,70.980000000000003979039320256561,404,0.001000000000000000020816681712,64,4096,0.5,1,128,5
398,1762158937,67,21991ec7-24fc-46c4-9def-2d379a567e83,1762159004,1762166382,7378,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 473 --learning_rate 0.00076151450209817079 --batch_size 64 --hidden_size 4096 --dropout 0.45004945487585423791 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c138,1209350,398_0,COMPLETED,BOTORCH_MODULAR,70.89000000000000056843418860808,473,0.000761514502098170793786824362,64,4096,0.450049454875854237911880773026,1,128,5
399,1762167886,46,21991ec7-24fc-46c4-9def-2d379a567e83,1762167932,1762170391,2459,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 166 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 537 --dropout 0.49863121123942755197 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c123,1210139,399_0,COMPLETED,BOTORCH_MODULAR,69,166,0.001000000000000000020816681712,64,537,0.498631211239427551973335539515,1,128,5
400,1762167887,66,21991ec7-24fc-46c4-9def-2d379a567e83,1762167953,1762169992,2039,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 159 --learning_rate 0.00100000000000000002 --batch_size 142 --hidden_size 1727 --dropout 0.47110782183039978666 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c122,1210143,400_0,COMPLETED,BOTORCH_MODULAR,70.25,159,0.001000000000000000020816681712,142,1727,0.471107821830399786655618754594,1,128,5
401,1762167886,45,21991ec7-24fc-46c4-9def-2d379a567e83,1762167931,1762170378,2447,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 165 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 1166 --dropout 0.48258793385660636588 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c123,1210138,401_0,COMPLETED,BOTORCH_MODULAR,70.810000000000002273736754432321,165,0.001000000000000000020816681712,64,1166,0.482587933856606365878860742669,1,128,5
402,1762167886,37,21991ec7-24fc-46c4-9def-2d379a567e83,1762167923,1762170507,2584,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 171 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 1308 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c124,1210137,402_0,COMPLETED,BOTORCH_MODULAR,70.739999999999994884092302527279,171,0.001000000000000000020816681712,64,1308,0.5,1,128,5
403,1762167885,24,21991ec7-24fc-46c4-9def-2d379a567e83,1762167909,1762170395,2486,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 168 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 1687 --dropout 0.48482629245495911796 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c124,1210135,403_0,COMPLETED,BOTORCH_MODULAR,70.200000000000002842170943040401,168,0.001000000000000000020816681712,64,1687,0.484826292454959117961266201746,1,128,5
404,1762167886,53,21991ec7-24fc-46c4-9def-2d379a567e83,1762167939,1762170514,2575,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 169 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 1516 --dropout 0.49768382874599820243 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c123,1210141,404_0,COMPLETED,BOTORCH_MODULAR,70.840000000000003410605131648481,169,0.001000000000000000020816681712,64,1516,0.497683828745998202425226963896,1,128,5
405,1762167886,37,21991ec7-24fc-46c4-9def-2d379a567e83,1762167923,1762170336,2413,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 167 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 622 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c124,1210136,405_0,COMPLETED,BOTORCH_MODULAR,69.689999999999997726263245567679,167,0.001000000000000000020816681712,64,622,0.5,1,128,5
406,1762167887,67,21991ec7-24fc-46c4-9def-2d379a567e83,1762167954,1762170450,2496,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 169 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 713 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c122,1210144,406_0,COMPLETED,BOTORCH_MODULAR,70.21999999999999886313162278384,169,0.001000000000000000020816681712,64,713,0.5,1,128,5
407,1762167892,91,21991ec7-24fc-46c4-9def-2d379a567e83,1762167983,1762170846,2863,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 189 --learning_rate 0.00099700658012245196 --batch_size 64 --hidden_size 1676 --dropout 0.49507219236251875927 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c120,1210151,407_0,COMPLETED,BOTORCH_MODULAR,70.599999999999994315658113919199,189,0.00099700658012245196339107256,64,1676,0.495072192362518759267686618841,1,128,5
408,1762167888,75,21991ec7-24fc-46c4-9def-2d379a567e83,1762167963,1762170412,2449,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 167 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 653 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c122,1210146,408_0,COMPLETED,BOTORCH_MODULAR,69.599999999999994315658113919199,167,0.001000000000000000020816681712,64,653,0.5,1,128,5
409,1762167887,94,21991ec7-24fc-46c4-9def-2d379a567e83,1762167981,1762170452,2471,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 167 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 516 --dropout 0.49443982726737756295 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c120,1210148,409_0,COMPLETED,BOTORCH_MODULAR,69.430000000000006821210263296962,167,0.001000000000000000020816681712,64,516,0.494439827267377562947103797342,1,128,5
410,1762167887,76,21991ec7-24fc-46c4-9def-2d379a567e83,1762167963,1762170600,2637,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 172 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 1320 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c139,1210145,410_0,COMPLETED,BOTORCH_MODULAR,70.35999999999999943156581139192,172,0.001000000000000000020816681712,64,1320,0.5,1,128,5
411,1762167887,96,21991ec7-24fc-46c4-9def-2d379a567e83,1762167983,1762173108,5125,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 421 --learning_rate 0.00100000000000000002 --batch_size 207 --hidden_size 3876 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c120,1210150,411_0,COMPLETED,BOTORCH_MODULAR,69.540000000000006252776074688882,421,0.001000000000000000020816681712,207,3876,0.5,1,128,5
412,1762167888,93,21991ec7-24fc-46c4-9def-2d379a567e83,1762167981,1762170465,2484,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 168 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 539 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c120,1210149,412_0,COMPLETED,BOTORCH_MODULAR,69.519999999999996020960679743439,168,0.001000000000000000020816681712,64,539,0.5,1,128,5
413,1762167887,81,21991ec7-24fc-46c4-9def-2d379a567e83,1762167968,1762170489,2521,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 168 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 1501 --dropout 0.49305990596770299383 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c122,1210147,413_0,COMPLETED,BOTORCH_MODULAR,70.53000000000000113686837721616,168,0.001000000000000000020816681712,64,1501,0.493059905967702993834222979785,1,128,5
414,1762167886,48,21991ec7-24fc-46c4-9def-2d379a567e83,1762167934,1762170509,2575,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 172 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 1740 --dropout 0.48914784171098790733 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c123,1210140,414_0,COMPLETED,BOTORCH_MODULAR,71.150000000000005684341886080801,172,0.001000000000000000020816681712,64,1740,0.489147841710987907326568802091,1,128,5
415,1762167900,83,21991ec7-24fc-46c4-9def-2d379a567e83,1762167983,1762170661,2678,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 173 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 3301 --dropout 0.48400426401145990596 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c119,1210152,415_0,COMPLETED,BOTORCH_MODULAR,70.96999999999999886313162278384,173,0.001000000000000000020816681712,64,3301,0.484004264011459905958645322244,1,128,5
416,1762167912,76,21991ec7-24fc-46c4-9def-2d379a567e83,1762167988,1762170177,2189,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 158 --learning_rate 0.00100000000000000002 --batch_size 93 --hidden_size 1282 --dropout 0.47203900744244137178 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c119,1210153,416_0,COMPLETED,BOTORCH_MODULAR,70.25,158,0.001000000000000000020816681712,93,1282,0.472039007442441371775743164108,1,128,5
417,1762167912,71,21991ec7-24fc-46c4-9def-2d379a567e83,1762167983,1762170482,2499,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 169 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 1129 --dropout 0.4940824382956492955 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c118,1210154,417_0,COMPLETED,BOTORCH_MODULAR,69.78000000000000113686837721616,169,0.001000000000000000020816681712,64,1129,0.494082438295649295501021924792,1,128,5
418,1762167915,72,21991ec7-24fc-46c4-9def-2d379a567e83,1762167987,1762170638,2651,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 174 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 2601 --dropout 0.46218995920367167418 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c118,1210155,418_0,COMPLETED,BOTORCH_MODULAR,71.189999999999997726263245567679,174,0.001000000000000000020816681712,64,2601,0.462189959203671674181634898559,1,128,5
419,1762173648,14,21991ec7-24fc-46c4-9def-2d379a567e83,1762173662,1762176646,2984,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 197 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 3254 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c152,1211145,419_0,COMPLETED,BOTORCH_MODULAR,70.290000000000006252776074688882,197,0.001000000000000000020816681712,64,3254,0.5,1,128,6
420,1762173649,73,21991ec7-24fc-46c4-9def-2d379a567e83,1762173722,1762176880,3158,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 203 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 3779 --dropout 0.41125850106011091478 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c108,1211158,420_0,COMPLETED,BOTORCH_MODULAR,71.28000000000000113686837721616,203,0.001000000000000000020816681712,64,3779,0.411258501060110914782086410924,1,128,5
421,1762173648,46,21991ec7-24fc-46c4-9def-2d379a567e83,1762173694,1762180568,6874,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 448 --learning_rate 0.0008403726330601408 --batch_size 64 --hidden_size 2904 --dropout 0.36807461559842030718 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c117,1211149,421_0,COMPLETED,BOTORCH_MODULAR,70.82999999999999829469743417576,448,0.000840372633060140804620030686,64,2904,0.3680746155984203071831473153,1,128,5
422,1762173649,70,21991ec7-24fc-46c4-9def-2d379a567e83,1762173719,1762176903,3184,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 204 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 3703 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c115,1211155,422_0,COMPLETED,BOTORCH_MODULAR,70.459999999999993747223925311118,204,0.001000000000000000020816681712,64,3703,0.5,1,128,6
423,1762173648,14,21991ec7-24fc-46c4-9def-2d379a567e83,1762173662,1762176888,3226,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 194 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 3307 --dropout 0.38711423521627874589 --num_dense_layers 2 --filter 128 --num_conv_layers 5,0,,c120,1211146,423_0,COMPLETED,BOTORCH_MODULAR,70.78000000000000113686837721616,194,0.001000000000000000020816681712,64,3307,0.387114235216278745888018875121,2,128,5
424,1762173650,46,21991ec7-24fc-46c4-9def-2d379a567e83,1762173696,1762176723,3027,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 200 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 3667 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c116,1211154,424_0,COMPLETED,BOTORCH_MODULAR,70.739999999999994884092302527279,200,0.001000000000000000020816681712,64,3667,0.5,1,128,6
425,1762173648,51,21991ec7-24fc-46c4-9def-2d379a567e83,1762173699,1762180304,6605,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 414 --learning_rate 0.00081090198774519092 --batch_size 64 --hidden_size 4096 --dropout 0.33970838960766414072 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c117,1211150,425_0,COMPLETED,BOTORCH_MODULAR,70.629999999999995452526491135359,414,0.0008109019877451909170951172,64,4096,0.339708389607664140719123224699,1,128,5
426,1762173648,15,21991ec7-24fc-46c4-9def-2d379a567e83,1762173663,1762176900,3237,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 205 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 3592 --dropout 0.41136676003951211378 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c119,1211147,426_0,COMPLETED,BOTORCH_MODULAR,70.28000000000000113686837721616,205,0.001000000000000000020816681712,64,3592,0.411366760039512113777959712024,1,128,5
427,1762173650,77,21991ec7-24fc-46c4-9def-2d379a567e83,1762173727,1762180383,6656,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 425 --learning_rate 0.00084971806382191006 --batch_size 64 --hidden_size 3712 --dropout 0.33906912292450691604 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c108,1211159,427_0,COMPLETED,BOTORCH_MODULAR,70.769999999999996020960679743439,425,0.000849718063821910062592690505,64,3712,0.339069122924506916039177895072,1,128,5
428,1762173650,69,21991ec7-24fc-46c4-9def-2d379a567e83,1762173719,1762176645,2926,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 194 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 2503 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c115,1211156,428_0,COMPLETED,BOTORCH_MODULAR,70.230000000000003979039320256561,194,0.001000000000000000020816681712,64,2503,0.5,1,128,6
429,1762173648,46,21991ec7-24fc-46c4-9def-2d379a567e83,1762173694,1762176744,3050,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 201 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 3535 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c116,1211152,429_0,COMPLETED,BOTORCH_MODULAR,70.409999999999996589394868351519,201,0.001000000000000000020816681712,64,3535,0.5,1,128,6
430,1762173649,45,21991ec7-24fc-46c4-9def-2d379a567e83,1762173694,1762180423,6729,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 436 --learning_rate 0.00085456955750336293 --batch_size 64 --hidden_size 3188 --dropout 0.35376576544719134931 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c116,1211153,430_0,COMPLETED,BOTORCH_MODULAR,71.25,436,0.000854569557503362929075374499,64,3188,0.353765765447191349313271757637,1,128,5
431,1762173649,45,21991ec7-24fc-46c4-9def-2d379a567e83,1762173694,1762180129,6435,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 415 --learning_rate 0.00082993910521473788 --batch_size 64 --hidden_size 2919 --dropout 0.30811388643285381184 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c117,1211151,431_0,COMPLETED,BOTORCH_MODULAR,70.32999999999999829469743417576,415,0.000829939105214737879272213217,64,2919,0.308113886432853811836451995987,1,128,5
432,1762173649,66,21991ec7-24fc-46c4-9def-2d379a567e83,1762173715,1762176581,2866,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 193 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 2254 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c108,1211157,432_0,COMPLETED,BOTORCH_MODULAR,70.549999999999997157829056959599,193,0.001000000000000000020816681712,64,2254,0.5,1,128,6
433,1762173649,20,21991ec7-24fc-46c4-9def-2d379a567e83,1762173669,1762176818,3149,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 202 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 3817 --dropout 0.41401542366821825203 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c118,1211148,433_0,COMPLETED,BOTORCH_MODULAR,70.689999999999997726263245567679,202,0.001000000000000000020816681712,64,3817,0.414015423668218252029049608609,1,128,5
434,1762173649,78,21991ec7-24fc-46c4-9def-2d379a567e83,1762173727,1762176852,3125,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 198 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 3674 --dropout 0.40946393510578482644 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c108,1211160,434_0,COMPLETED,BOTORCH_MODULAR,70.730000000000003979039320256561,198,0.001000000000000000020816681712,64,3674,0.409463935105784826440356027888,1,128,5
435,1762173653,101,21991ec7-24fc-46c4-9def-2d379a567e83,1762173754,1762178019,4265,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 273 --learning_rate 0.00080967127610278612 --batch_size 64 --hidden_size 3901 --dropout 0 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c107,1211161,435_0,COMPLETED,BOTORCH_MODULAR,68.069999999999993178789736703038,273,0.000809671276102786122152998871,64,3901,0,1,128,5
436,1762173656,100,21991ec7-24fc-46c4-9def-2d379a567e83,1762173756,1762176583,2827,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 169 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 3944 --dropout 0.42773015787042195646 --num_dense_layers 2 --filter 128 --num_conv_layers 5,0,,c107,1211162,436_0,COMPLETED,BOTORCH_MODULAR,69.049999999999997157829056959599,169,0.001000000000000000020816681712,64,3944,0.427730157870421956456397083457,2,128,5
437,1762173661,95,21991ec7-24fc-46c4-9def-2d379a567e83,1762173756,1762176723,2967,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 197 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 2840 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c107,1211163,437_0,COMPLETED,BOTORCH_MODULAR,70.319999999999993178789736703038,197,0.001000000000000000020816681712,64,2840,0.5,1,128,6
438,1762173666,88,21991ec7-24fc-46c4-9def-2d379a567e83,1762173754,1762180416,6662,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 420 --learning_rate 0.00082130457303821694 --batch_size 64 --hidden_size 4096 --dropout 0.33391220344478272919 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c107,1211164,438_0,COMPLETED,BOTORCH_MODULAR,71.159999999999996589394868351519,420,0.000821304573038216943932365854,64,4096,0.333912203444782729189199699249,1,128,5
439,1762181759,15,21991ec7-24fc-46c4-9def-2d379a567e83,1762181774,1762184529,2755,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 177 --learning_rate 0.00085102783202139337 --batch_size 64 --hidden_size 3473 --dropout 0.48976172193674483157 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c137,1211723,439_0,COMPLETED,BOTORCH_MODULAR,71.349999999999994315658113919199,150,0.001000000000000000020816681712,1024,4096,0.5,2,128,5
⚠ Job 1208437 (task: 0) with path /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/runs/mnist_mono/4/single_runs/1208437/1208437_0_result.pkl
has not produced any output (state: TIMEOUT)
No error stream produced. Look at stdout: /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/runs/mnist_mono/4/single_runs/1208437/1208437_0_log.out
----------------------------------------
submitit INFO (2025-11-02 17:46:21,875) - Starting with JobEnvironment(job_id=1208437, hostname=c124, local_rank=0(1), node=0(1), global_rank=0(1))
submitit INFO (2025-11-02 17:46:21,876) - Loading pickle: /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/runs/mnist_mono/4/single_runs/1208437/1208437_submitted.pkl
Trial-Index: 230
slurmstepd: error: *** JOB 1208437 ON c124 CANCELLED AT 2025-11-02T21:46:36 DUE TO TIME LIMIT ***
get_ax_client_trial: trial_index 445 failed
execute_evaluation: _trial was not in execute_evaluation for params [445, {'epochs': 340, 'lr': 0.00024750500974596686, 'batch_size': 64, 'hidden_size': 3554, 'dropout': 0.5, 'num_dense_layers': 1, 'filter': 128, 'num_conv_layers': 7}, 7, 'systematic']
get_ax_client_trial: trial_index 442 failed
get_ax_client_trial: trial_index 441 failed
get_ax_client_trial: trial_index 440 failed
get_ax_client_trial: trial_index 443 failed
execute_evaluation: _trial was not in execute_evaluation for params [442, {'epochs': 417, 'lr': 0.0001750568141097309, 'batch_size': 64, 'hidden_size': 2924, 'dropout': 0.0, 'num_dense_layers': 2, 'filter': 128, 'num_conv_layers': 5}, 4, 'systematic']
get_ax_client_trial: trial_index 454 failed
execute_evaluation: _trial was not in execute_evaluation for params [441, {'epochs': 151, 'lr': 0.001, 'batch_size': 1024, 'hidden_size': 4096, 'dropout': 0.5, 'num_dense_layers': 2, 'filter': 128, 'num_conv_layers': 5}, 3, 'systematic']
get_ax_client_trial: trial_index 448 failed
execute_evaluation: _trial was not in execute_evaluation for params [443, {'epochs': 92, 'lr': 0.000750537853968684, 'batch_size': 64, 'hidden_size': 3924, 'dropout': 0.5, 'num_dense_layers': 1, 'filter': 128, 'num_conv_layers': 6}, 5, 'systematic']
execute_evaluation: _trial was not in execute_evaluation for params [440, {'epochs': 97, 'lr': 0.000825176101861256, 'batch_size': 64, 'hidden_size': 3018, 'dropout': 0.5, 'num_dense_layers': 1, 'filter': 128, 'num_conv_layers': 6}, 2, 'systematic']
execute_evaluation: _trial was not in execute_evaluation for params [448, {'epochs': 346, 'lr': 0.00022765610649565034, 'batch_size': 64, 'hidden_size': 4096, 'dropout': 0.5, 'num_dense_layers': 1, 'filter': 128, 'num_conv_layers': 7}, 10, 'systematic']
execute_evaluation: _trial was not in execute_evaluation for params [454, {'epochs': 101, 'lr': 0.0008309433833078211, 'batch_size': 64, 'hidden_size': 2014, 'dropout': 0.5, 'num_dense_layers': 1, 'filter': 128, 'num_conv_layers': 6}, 15, 'systematic']
get_ax_client_trial: trial_index 446 failed
get_ax_client_trial: trial_index 447 failed
execute_evaluation: _trial was not in execute_evaluation for params [446, {'epochs': 431, 'lr': 0.0007762519140956109, 'batch_size': 64, 'hidden_size': 4031, 'dropout': 0.4411770700768548, 'num_dense_layers': 2, 'filter': 128, 'num_conv_layers': 5}, 8, 'systematic']
execute_evaluation: _trial was not in execute_evaluation for params [447, {'epochs': 103, 'lr': 0.0008662624015333994, 'batch_size': 64, 'hidden_size': 2212, 'dropout': 0.5, 'num_dense_layers': 1, 'filter': 128, 'num_conv_layers': 6}, 9, 'systematic']
get_ax_client_trial: trial_index 449 failed
get_ax_client_trial: trial_index 453 failed
execute_evaluation: _trial was not in execute_evaluation for params [449, {'epochs': 433, 'lr': 0.0007194819495007069, 'batch_size': 64, 'hidden_size': 3896, 'dropout': 0.40187069798103736, 'num_dense_layers': 2, 'filter': 128, 'num_conv_layers': 5}, 11, 'systematic']
execute_evaluation: _trial was not in execute_evaluation for params [453, {'epochs': 95, 'lr': 0.0008045252317924025, 'batch_size': 64, 'hidden_size': 3362, 'dropout': 0.5, 'num_dense_layers': 1, 'filter': 128, 'num_conv_layers': 6}, 14, 'systematic']
get_ax_client_trial: trial_index 455 failed
execute_evaluation: _trial was not in execute_evaluation for params [455, {'epochs': 415, 'lr': 0.0007592187347799277, 'batch_size': 64, 'hidden_size': 3744, 'dropout': 0.48641157448429456, 'num_dense_layers': 2, 'filter': 128, 'num_conv_layers': 5}, 16, 'systematic']
get_ax_client_trial: trial_index 452 failed
execute_evaluation: _trial was not in execute_evaluation for params [452, {'epochs': 96, 'lr': 0.0008205128356167226, 'batch_size': 70, 'hidden_size': 2939, 'dropout': 0.5, 'num_dense_layers': 1, 'filter': 128, 'num_conv_layers': 6}, 13, 'systematic']
get_ax_client_trial: trial_index 444 failed
execute_evaluation: _trial was not in execute_evaluation for params [444, {'epochs': 423, 'lr': 0.0008332559298239117, 'batch_size': 64, 'hidden_size': 2170, 'dropout': 0.5, 'num_dense_layers': 1, 'filter': 128, 'num_conv_layers': 5}, 6, 'systematic']
get_ax_client_trial: trial_index 450 failed
execute_evaluation: _trial was not in execute_evaluation for params [450, {'epochs': 153, 'lr': 0.001, 'batch_size': 1024, 'hidden_size': 4096, 'dropout': 0.5, 'num_dense_layers': 2, 'filter': 128, 'num_conv_layers': 5}, 12, 'systematic']
get_ax_client_trial: trial_index 456 failed
execute_evaluation: _trial was not in execute_evaluation for params [456, {'epochs': 103, 'lr': 0.0008466481580691556, 'batch_size': 64, 'hidden_size': 1584, 'dropout': 0.5, 'num_dense_layers': 1, 'filter': 128, 'num_conv_layers': 6}, 17, 'systematic']
get_ax_client_trial: trial_index 458 failed
execute_evaluation: _trial was not in execute_evaluation for params [458, {'epochs': 96, 'lr': 0.0008302359247140662, 'batch_size': 64, 'hidden_size': 3037, 'dropout': 0.5, 'num_dense_layers': 1, 'filter': 128, 'num_conv_layers': 6}, 19, 'systematic']
get_ax_client_trial: trial_index 457 failed
execute_evaluation: _trial was not in execute_evaluation for params [457, {'epochs': 421, 'lr': 0.0007716644569729742, 'batch_size': 64, 'hidden_size': 3174, 'dropout': 0.4537545618413937, 'num_dense_layers': 2, 'filter': 128, 'num_conv_layers': 5}, 18, 'systematic']
To cancel, press CTRL c, then run 'scancel 1207669'
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[WARNING 11-01 17:41:07] ax.service.utils.with_db_settings_base: Ax currently requires a sqlalchemy version below 2.0. This will be addressed in a future release. Disabling SQL storage in Ax for now, if you would like to use SQL storage please install Ax with mysql extras via `pip install ax-platform[mysql]`.
⠧ Importing ax...
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Run-UUID: 457b5d5a-a20f-4d85-9ef2-819d0ab02567
_____ _____ __ ___
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\ \ \/\ \ ___ ___ ___ /\_\ \ \/\ \ _____\ \ ,_\/\_\ /\ \
\ \ \ \ \ /' __` __`\ /' _ `\/\ \ \ \ \ \/\ '__`\ \ \/\/_/// /__
\ \ \_\ \/\ \/\ \/\ \/\ \/\ \ \ \ \ \_\ \ \ \L\ \ \ \_ // /_\ \
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\/_____/\/_/\/_/\/_/\/_/\/_/\/_/\/_____/\ \ \/ \/__/\/_____/
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⠋ Writing worker creation log...
omniopt --partition=alpha --experiment_name=mnist_mono --mem_gb=40 --time=2880 --worker_timeout=240 --max_eval=1000 --num_parallel_jobs=20 --gpus=1 --num_random_steps=20 --follow --live_share --send_anonymized_usage_stats --result_names VAL_ACC=max --run_program=cHl0aG9uMyAvZGF0YS9ob3JzZS93cy9zMzgxMTE0MS1vbW5pb3B0X21uaXN0X3Rlc3RfY2FsbC9vbW5pb3B0Ly50ZXN0cy9tbmlzdC90cmFpbiAtLWVwb2NocyAlZXBvY2hzIC0tbGVhcm5pbmdfcmF0ZSAlbHIgLS1iYXRjaF9zaXplICViYXRjaF9zaXplIC0taGlkZGVuX3NpemUgJWhpZGRlbl9zaXplIC0tZHJvcG91dCAlZHJvcG91dCAtLW51bV9kZW5zZV9sYXllcnMgJW51bV9kZW5zZV9sYXllcnMgLS1maWx0ZXIgJShmaWx0ZXIpIC0tbnVtX2NvbnZfbGF5ZXJzICUobnVtX2NvbnZfbGF5ZXJzKQo= --run_program_once=cHl0aG9uMyAvZGF0YS9ob3JzZS93cy9zMzgxMTE0MS1vbW5pb3B0X21uaXN0X3Rlc3RfY2FsbC9vbW5pb3B0Ly50ZXN0cy9tbmlzdC90cmFpbiAtLWluc3RhbGw= --cpus_per_task=1 --nodes_per_job=1 --revert_to_random_when_seemingly_exhausted --model=BOTORCH_MODULAR --n_estimators_randomforest=100 --run_mode=local --occ_type=euclid --main_process_gb=20 --max_nr_of_zero_results=50 --slurm_signal_delay_s=0 --max_failed_jobs=0 --max_attempts_for_generation=20 --num_restarts=20 --raw_samples=1024 --max_abandoned_retrial=20 --max_num_of_parallel_sruns=16 --number_of_generators=1 --generate_all_jobs_at_once --parameter epochs range 20 500 int false --parameter lr range 0.0001 0.001 float false --parameter batch_size range 64 1024 int false --parameter hidden_size range 512 4096 int false --parameter dropout range 0 0.5 float false --parameter num_dense_layers range 1 2 int false --parameter filter range 16 128 int false --parameter num_conv_layers range 5 7 int false
⠋ Disabling logging...
⠋ Setting run folder...
⠋ Creating folder /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/runs/mnist_mono/4...
⠋ Writing revert_to_random_when_seemingly_exhausted file ...
⠋ Writing username state file...
⠋ Writing result names file...
⠋ Writing result min/max file...
Executing command: python3
/data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train
--install
Hyperparameters
╭──────────────────┬─────────╮
│ Parameter │ Value │
├──────────────────┼─────────┤
│ Epochs │ 60 │
│ Num Dense Layers │ 2 │
│ Batch size │ 128 │
│ Learning rate │ 0.001 │
│ Hidden size │ 128 │
│ Dropout │ 0.2 │
│ Optimizer │ adam │
│ Momentum │ 0.9 │
│ Weight Decay │ 0.0001 │
│ Activation │ relu │
│ Init Method │ kaiming │
│ Seed │ None │
│ Conv Filters │ 16 │
│ Num Conv Layers │ 4 │
│ Conv Kernel │ 3 │
│ Conv Stride │ 1 │
│ Conv Padding │ 1 │
╰──────────────────┴─────────╯
Exiting, since the installation should now be done
Setup script completed successfully ✅
⠋ Saving state files...
Run-folder: /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/runs/mnist_mono/4
⠋ Writing live_share file if it is present...
⠋ Writing job_start_time file...
⠹ Writing git information
⠋ Checking max_eval...
⠋ Calculating number of steps...
⠋ Adding excluded nodes...
⠋ Initializing ax_client...
⠋ Setting orchestrator...
See https://imageseg.scads.de/omniax/share?user_id=s3811141&experiment_name=mnist_mono&run_nr=5 for live-results.
You have 1 CPUs available for the main process. Using CUDA device NVIDIA H100.
Generation strategy: SOBOL for 20 steps and then BOTORCH_MODULAR for 980 steps.
Run-Program: python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs %epochs --learning_rate %lr --batch_size %batch_size --hidden_size %hidden_size --dropout %dropout --num_dense_layers %num_dense_layers --filter %(filter) --num_conv_layers %(num_conv_layers)
Experiment parameters
┏━━━━━━━━━━━━━━━━━━┳━━━━━━━┳━━━━━━━━━━━━━┳━━━━━━━━━━━━━┳━━━━━━━┳━━━━━━━━━━━━┓
┃ Name ┃ Type ┃ Lower bound ┃ Upper bound ┃ Type ┃ Log Scale? ┃
┡━━━━━━━━━━━━━━━━━━╇━━━━━━━╇━━━━━━━━━━━━━╇━━━━━━━━━━━━━╇━━━━━━━╇━━━━━━━━━━━━┩
│ epochs │ range │ 20 │ 500 │ int │ No │
│ lr │ range │ 0.0001 │ 0.001 │ float │ No │
│ batch_size │ range │ 64 │ 1024 │ int │ No │
│ hidden_size │ range │ 512 │ 4096 │ int │ No │
│ dropout │ range │ 0 │ 0.5 │ float │ No │
│ num_dense_layers │ range │ 1 │ 2 │ int │ No │
│ filter │ range │ 16 │ 128 │ int │ No │
│ num_conv_layers │ range │ 5 │ 7 │ int │ No │
└──────────────────┴───────┴─────────────┴─────────────┴───────┴────────────┘
Result-Names
┏━━━━━━━━━━━━━┳━━━━━━━━━━━━━┓
┃ Result-Name ┃ Min or max? ┃
┡━━━━━━━━━━━━━╇━━━━━━━━━━━━━┩
│ VAL_ACC │ max │
└─────────────┴─────────────┘
⠋ Write files and show overview
BOTORCH_MODULAR, best VAL_ACC: 67.79, running 20 = ∑20/20, waiting for 20 jobs : 4%|░░░░░░░░░░| 40/1000 [2:55:55<10:26:38, 39.17s/it]
Exit-Code 3, this means: Invalid exit code detected
BOTORCH_MODULAR, best VAL_ACC: 71.49, running 1 = ∑1/20, waiting for 1 job : 22%|██░░░░░░░░| 220/1000 [26:17:00<24:07:15, 111.33s/it]
⚠ Job 1208437 (task: 0) with path /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/runs/mnist_mono/4/single_runs/1208437/1208437_0_result.pkl
has not produced any output (state: TIMEOUT)
No error stream produced. Look at stdout: /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/runs/mnist_mono/4/single_runs/1208437/1208437_0_log.out
----------------------------------------
submitit INFO (2025-11-02 17:46:21,875) - Starting with JobEnvironment(job_id=1208437, hostname=c124, local_rank=0(1), node=0(1), global_rank=0(1))
submitit INFO (2025-11-02 17:46:21,876) - Loading pickle: /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/runs/mnist_mono/4/single_runs/1208437/1208437_submitted.pkl
Trial-Index: 230
slurmstepd: error: *** JOB 1208437 ON c124 CANCELLED AT 2025-11-02T21:46:36 DUE TO TIME LIMIT ***
BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 1 = ∑1/20, new result: VAL_ACC: 71.350000 : 42%|████░░░░░░| 421/1000 [47:00:41<167:44:17, 1042.93s/it]
2025-11-01 17:41:31 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, Started OmniOpt2 run...
2025-11-01 17:41:31 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, getting new HP set #1/20
2025-11-01 17:41:31 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, getting new HP set #2/20
2025-11-01 17:41:31 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, getting new HP set #3/20
2025-11-01 17:41:31 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, getting new HP set #4/20
2025-11-01 17:41:31 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, getting new HP set #5/20
2025-11-01 17:41:31 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, getting new HP set #6/20
2025-11-01 17:41:31 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, getting new HP set #7/20
2025-11-01 17:41:31 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, getting new HP set #8/20
2025-11-01 17:41:31 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, getting new HP set #9/20
2025-11-01 17:41:31 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, getting new HP set #10/20
2025-11-01 17:41:32 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, getting new HP set #11/20
2025-11-01 17:41:32 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, getting new HP set #12/20
2025-11-01 17:41:32 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, getting new HP set #13/20
2025-11-01 17:41:32 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, getting new HP set #14/20
2025-11-01 17:41:32 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, getting new HP set #15/20
2025-11-01 17:41:33 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, getting new HP set #16/20
2025-11-01 17:41:33 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, getting new HP set #17/20
2025-11-01 17:41:33 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, getting new HP set #18/20
2025-11-01 17:41:33 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, getting new HP set #19/20
2025-11-01 17:41:33 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, getting new HP set #20/20
2025-11-01 17:41:33 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, requested 20 jobs, got 20, 0.10 s/job
2025-11-01 17:41:33 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, eval #1/20 start
2025-11-01 17:41:33 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, eval #2/20 start
2025-11-01 17:41:33 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, eval #3/20 start
2025-11-01 17:41:33 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, eval #4/20 start
2025-11-01 17:41:34 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, eval #5/20 start
2025-11-01 17:41:34 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, eval #6/20 start
2025-11-01 17:41:34 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, eval #7/20 start
2025-11-01 17:41:34 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, eval #8/20 start
2025-11-01 17:41:35 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, eval #9/20 start
2025-11-01 17:41:35 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, eval #10/20 start
2025-11-01 17:41:35 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, eval #11/20 start
2025-11-01 17:41:36 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, eval #12/20 start
2025-11-01 17:41:36 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, eval #13/20 start
2025-11-01 17:41:38 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, eval #14/20 start
2025-11-01 17:41:38 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, eval #15/20 start
2025-11-01 17:41:40 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, eval #16/20 start
2025-11-01 17:41:42 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, eval #17/20 start
2025-11-01 17:41:42 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, eval #18/20 start
2025-11-01 17:41:42 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, eval #19/20 start
2025-11-01 17:41:42 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, eval #20/20 start
2025-11-01 17:41:43 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, starting new job
2025-11-01 17:41:44 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, unknown 1 = ∑1/20, started new job
2025-11-01 17:41:44 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, unknown 1 = ∑1/20, starting new job
2025-11-01 17:41:48 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, pending/unknown 1/1 = ∑2/20, started new job
2025-11-01 17:41:48 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, pending/unknown 1/1 = ∑2/20, starting new job
2025-11-01 17:41:58 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, running/unknown 2/2 = ∑4/20, started new job
2025-11-01 17:41:58 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, running/unknown 2/3 = ∑5/20, started new job
2025-11-01 17:41:58 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, running/unknown 2/3 = ∑5/20, starting new job
2025-11-01 17:42:08 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, running/pending/unknown 2/3/1 = ∑6/20, started new job
2025-11-01 17:42:08 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, running/pending/unknown 2/3/2 = ∑7/20, started new job
2025-11-01 17:42:13 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, running/unknown 7/1 = ∑8/20, started new job
2025-11-01 17:42:19 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, running/unknown 8/1 = ∑9/20, started new job
2025-11-01 17:42:23 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, running/pending/unknown 8/1/1 = ∑10/20, started new job
2025-11-01 17:42:28 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, running/pending/unknown 8/2/1 = ∑11/20, started new job
2025-11-01 17:42:33 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, running/pending/unknown 8/3/1 = ∑12/20, started new job
2025-11-01 17:42:38 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, running/unknown 12/1 = ∑13/20, started new job
2025-11-01 17:42:43 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, running/unknown 13/1 = ∑14/20, started new job
2025-11-01 17:42:48 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, running/pending/unknown 13/1/1 = ∑15/20, started new job
2025-11-01 17:42:53 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, running/pending/unknown 13/2/1 = ∑16/20, started new job
2025-11-01 17:42:58 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, running/unknown 16/1 = ∑17/20, started new job
2025-11-01 17:43:08 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, running/pending/unknown 16/1/2 = ∑19/20, started new job
2025-11-01 17:43:08 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, running/pending/unknown 16/1/3 = ∑20/20, started new job
2025-11-01 17:43:10 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, running/pending/unknown 16/1/3 = ∑20/20, waiting for 20 jobs
2025-11-01 17:43:11 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, running/pending 17/3 = ∑20/20, waiting for 20 jobs
2025-11-01 17:43:14 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, running 20 = ∑20/20, waiting for 20 jobs
2025-11-01 17:51:44 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, running 20 = ∑20/20, new result: VAL_ACC: 57.880000
2025-11-01 17:51:47 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 57.88, running 19 = ∑19/20, waiting for 20 jobs, finished 1 job
2025-11-01 17:51:47 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 57.88, running 19 = ∑19/20, waiting for 19 jobs
2025-11-01 17:54:54 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 57.88, running 19 = ∑19/20, new result: VAL_ACC: 45.600000
2025-11-01 17:54:57 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 57.88, running 18 = ∑18/20, waiting for 19 jobs, finished 1 job
2025-11-01 17:54:57 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 57.88, running 18 = ∑18/20, waiting for 18 jobs
2025-11-01 17:55:51 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 57.88, running 18 = ∑18/20, new result: VAL_ACC: 57.140000
2025-11-01 17:55:54 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 57.88, running 17 = ∑17/20, waiting for 18 jobs, finished 1 job
2025-11-01 17:55:54 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 57.88, running 17 = ∑17/20, waiting for 17 jobs
2025-11-01 17:59:45 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 57.88, running 17 = ∑17/20, new result: VAL_ACC: 59.480000
2025-11-01 17:59:47 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 59.48, running 16 = ∑16/20, waiting for 17 jobs, finished 1 job
2025-11-01 17:59:47 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 59.48, running 16 = ∑16/20, waiting for 16 jobs
2025-11-01 18:06:38 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 59.48, running 16 = ∑16/20, new result: VAL_ACC: 59.030000
2025-11-01 18:06:41 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 59.48, running 15 = ∑15/20, waiting for 16 jobs, finished 1 job
2025-11-01 18:06:41 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 59.48, running 15 = ∑15/20, waiting for 15 jobs
2025-11-01 18:08:56 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 59.48, running 15 = ∑15/20, new result: VAL_ACC: 59.290000
2025-11-01 18:08:59 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 59.48, running 14 = ∑14/20, waiting for 15 jobs, finished 1 job
2025-11-01 18:08:59 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 59.48, running 14 = ∑14/20, waiting for 14 jobs
2025-11-01 18:21:12 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 59.48, running 14 = ∑14/20, new result: VAL_ACC: 61.420000
2025-11-01 18:21:15 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 61.42, running 13 = ∑13/20, waiting for 14 jobs, finished 1 job
2025-11-01 18:21:15 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 61.42, running 13 = ∑13/20, waiting for 13 jobs
2025-11-01 18:21:22 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 61.42, running 13 = ∑13/20, new result: VAL_ACC: 55.550000
2025-11-01 18:21:24 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 61.42, running 12 = ∑12/20, waiting for 13 jobs, finished 1 job
2025-11-01 18:21:24 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 61.42, running 12 = ∑12/20, waiting for 12 jobs
2025-11-01 18:23:28 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 61.42, running 12 = ∑12/20, new result: VAL_ACC: 52.800000
2025-11-01 18:23:31 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 61.42, running 11 = ∑11/20, waiting for 12 jobs, finished 1 job
2025-11-01 18:23:31 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 61.42, running 11 = ∑11/20, waiting for 11 jobs
2025-11-01 18:23:52 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 61.42, running 11 = ∑11/20, new result: VAL_ACC: 66.360000
2025-11-01 18:23:55 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 66.36, running 10 = ∑10/20, waiting for 11 jobs, finished 1 job
2025-11-01 18:23:55 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 66.36, running 10 = ∑10/20, waiting for 10 jobs
2025-11-01 18:26:42 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 66.36, running 10 = ∑10/20, new result: VAL_ACC: 50.520000
2025-11-01 18:26:45 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 66.36, running 9 = ∑9/20, waiting for 10 jobs, finished 1 job
2025-11-01 18:26:45 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 66.36, running 9 = ∑9/20, waiting for 9 jobs
2025-11-01 18:38:49 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 66.36, running 9 = ∑9/20, new result: VAL_ACC: 59.000000
2025-11-01 18:38:51 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 66.36, running 8 = ∑8/20, waiting for 9 jobs, finished 1 job
2025-11-01 18:38:51 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 66.36, running 8 = ∑8/20, waiting for 8 jobs
2025-11-01 18:44:27 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 66.36, running 8 = ∑8/20, new result: VAL_ACC: 55.910000
2025-11-01 18:44:31 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 66.36, running 7 = ∑7/20, waiting for 8 jobs, finished 1 job
2025-11-01 18:44:31 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 66.36, running 7 = ∑7/20, waiting for 7 jobs
2025-11-01 18:47:48 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 66.36, running 7 = ∑7/20, new result: VAL_ACC: 60.720000
2025-11-01 18:47:51 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 66.36, running 6 = ∑6/20, waiting for 7 jobs, finished 1 job
2025-11-01 18:47:51 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 66.36, running 6 = ∑6/20, waiting for 6 jobs
2025-11-01 18:53:05 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 66.36, running 6 = ∑6/20, new result: VAL_ACC: 62.230000
2025-11-01 18:53:07 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 66.36, running 5 = ∑5/20, waiting for 6 jobs, finished 1 job
2025-11-01 18:53:07 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 66.36, running 5 = ∑5/20, waiting for 5 jobs
2025-11-01 18:54:40 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 66.36, running 5 = ∑5/20, new result: VAL_ACC: 49.470000
2025-11-01 18:54:43 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 66.36, running 4 = ∑4/20, waiting for 5 jobs, finished 1 job
2025-11-01 18:54:43 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 66.36, running 4 = ∑4/20, waiting for 4 jobs
2025-11-01 18:56:21 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 66.36, running 4 = ∑4/20, new result: VAL_ACC: 60.940000
2025-11-01 18:56:23 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 66.36, running 3 = ∑3/20, waiting for 4 jobs, finished 1 job
2025-11-01 18:56:23 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 66.36, running 3 = ∑3/20, waiting for 3 jobs
2025-11-01 18:56:24 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 66.36, running 3 = ∑3/20, new result: VAL_ACC: 60.020000
2025-11-01 18:56:26 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 66.36, running 2 = ∑2/20, waiting for 3 jobs, finished 1 job
2025-11-01 18:56:27 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 66.36, running 2 = ∑2/20, waiting for 2 jobs
2025-11-01 18:56:56 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 66.36, running 2 = ∑2/20, new result: VAL_ACC: 47.780000
2025-11-01 18:56:58 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 66.36, running 1 = ∑1/20, waiting for 2 jobs, finished 1 job
2025-11-01 18:56:58 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 66.36, running 1 = ∑1/20, waiting for 1 job
2025-11-01 19:17:24 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 66.36, running 1 = ∑1/20, new result: VAL_ACC: 64.330000
2025-11-01 19:17:27 (21991ec7-24fc-46c4-9def-2d379a567e83): SOBOL, best VAL_ACC: 66.36, waiting for 1 job, finished 1 job
2025-11-01 19:18:06 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, getting new HP set #1/20
2025-11-01 19:18:06 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, getting new HP set #2/20
2025-11-01 19:18:06 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, getting new HP set #3/20
2025-11-01 19:18:06 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, getting new HP set #4/20
2025-11-01 19:18:06 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, getting new HP set #5/20
2025-11-01 19:18:06 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, getting new HP set #6/20
2025-11-01 19:18:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, getting new HP set #7/20
2025-11-01 19:18:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, getting new HP set #8/20
2025-11-01 19:18:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, getting new HP set #9/20
2025-11-01 19:18:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, getting new HP set #10/20
2025-11-01 19:18:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, getting new HP set #11/20
2025-11-01 19:18:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, getting new HP set #12/20
2025-11-01 19:18:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, getting new HP set #13/20
2025-11-01 19:18:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, getting new HP set #14/20
2025-11-01 19:18:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, getting new HP set #15/20
2025-11-01 19:18:08 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, getting new HP set #16/20
2025-11-01 19:18:08 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, getting new HP set #17/20
2025-11-01 19:18:08 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, getting new HP set #18/20
2025-11-01 19:18:08 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, getting new HP set #19/20
2025-11-01 19:18:08 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, getting new HP set #20/20
2025-11-01 19:18:08 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, requested 20 jobs, got 20, 2.01 s/job
2025-11-01 19:18:08 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, eval #1/20 start
2025-11-01 19:18:09 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, eval #2/20 start
2025-11-01 19:18:15 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, eval #3/20 start
2025-11-01 19:18:15 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, eval #4/20 start
2025-11-01 19:18:16 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, eval #5/20 start
2025-11-01 19:18:16 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, eval #6/20 start
2025-11-01 19:18:16 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, eval #7/20 start
2025-11-01 19:18:16 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, eval #8/20 start
2025-11-01 19:18:17 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, eval #9/20 start
2025-11-01 19:18:17 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, eval #10/20 start
2025-11-01 19:18:17 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, eval #11/20 start
2025-11-01 19:18:17 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, eval #12/20 start
2025-11-01 19:18:18 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, eval #13/20 start
2025-11-01 19:18:18 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, eval #14/20 start
2025-11-01 19:18:18 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, eval #15/20 start
2025-11-01 19:18:19 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, eval #16/20 start
2025-11-01 19:18:20 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, eval #17/20 start
2025-11-01 19:18:20 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, eval #18/20 start
2025-11-01 19:18:21 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, eval #19/20 start
2025-11-01 19:18:22 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, eval #20/20 start
2025-11-01 19:18:23 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, starting new job
2025-11-01 19:18:24 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, unknown 3 = ∑3/20, started new job
2025-11-01 19:18:24 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, unknown 3 = ∑3/20, starting new job
2025-11-01 19:18:29 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, pending/unknown 3/1 = ∑4/20, started new job
2025-11-01 19:18:29 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, pending/unknown 3/1 = ∑4/20, starting new job
2025-11-01 19:18:39 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, pending/unknown 4/3 = ∑7/20, started new job
2025-11-01 19:18:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, running/unknown 7/1 = ∑8/20, started new job
2025-11-01 19:18:50 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, running/pending/unknown 7/1/1 = ∑9/20, started new job
2025-11-01 19:18:54 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, running/pending/unknown 7/2/1 = ∑10/20, started new job
2025-11-01 19:18:59 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, running/pending/unknown 7/3/1 = ∑11/20, started new job
2025-11-01 19:19:04 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, running/unknown 11/1 = ∑12/20, started new job
2025-11-01 19:19:10 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, running/pending/unknown 11/1/1 = ∑13/20, started new job
2025-11-01 19:19:14 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, running/unknown 13/1 = ∑14/20, started new job
2025-11-01 19:19:19 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, running/pending/unknown 13/1/1 = ∑15/20, started new job
2025-11-01 19:19:24 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, running/unknown 15/1 = ∑16/20, started new job
2025-11-01 19:19:29 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, running/pending/unknown 15/1/2 = ∑18/20, started new job
2025-11-01 19:19:34 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, running/pending/unknown 15/3/1 = ∑19/20, started new job
2025-11-01 19:19:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, running/unknown 19/1 = ∑20/20, started new job
2025-11-01 19:19:45 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, running/unknown 19/1 = ∑20/20, waiting for 20 jobs
2025-11-01 19:19:52 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, running/pending 19/1 = ∑20/20, waiting for 20 jobs
2025-11-01 19:20:16 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, running 20 = ∑20/20, waiting for 20 jobs
2025-11-01 20:31:05 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, running 20 = ∑20/20, new result: VAL_ACC: 65.140000
2025-11-01 20:31:09 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, running 19 = ∑19/20, waiting for 20 jobs, finished 1 job
2025-11-01 20:31:10 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, running 19 = ∑19/20, waiting for 19 jobs
2025-11-01 20:31:30 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, running 19 = ∑19/20, new result: VAL_ACC: 64.960000
2025-11-01 20:31:33 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, running 18 = ∑18/20, waiting for 19 jobs, finished 1 job
2025-11-01 20:31:33 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, running 18 = ∑18/20, waiting for 18 jobs
2025-11-01 20:32:25 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.36, running 18 = ∑18/20, new result: VAL_ACC: 66.520000
2025-11-01 20:32:28 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.52, running 17 = ∑17/20, waiting for 18 jobs, finished 1 job
2025-11-01 20:32:28 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.52, running 17 = ∑17/20, waiting for 17 jobs
2025-11-01 20:32:29 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.52, running 17 = ∑17/20, new result: VAL_ACC: 66.310000
2025-11-01 20:32:32 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.52, running 16 = ∑16/20, waiting for 17 jobs, finished 1 job
2025-11-01 20:32:32 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.52, running 16 = ∑16/20, waiting for 16 jobs
2025-11-01 20:32:33 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.52, running 16 = ∑16/20, new result: VAL_ACC: 66.960000
2025-11-01 20:32:36 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.96, running 15 = ∑15/20, waiting for 16 jobs, finished 1 job
2025-11-01 20:32:37 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.96, running 15 = ∑15/20, waiting for 15 jobs
2025-11-01 20:32:38 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 66.96, running 15 = ∑15/20, new result: VAL_ACC: 67.130000
2025-11-01 20:32:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.13, running 14 = ∑14/20, waiting for 15 jobs, finished 1 job
2025-11-01 20:32:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.13, running 14 = ∑14/20, waiting for 14 jobs
2025-11-01 20:32:43 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.13, running 14 = ∑14/20, new result: VAL_ACC: 66.840000
2025-11-01 20:32:46 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.13, running 13 = ∑13/20, waiting for 14 jobs, finished 1 job
2025-11-01 20:32:46 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.13, running 13 = ∑13/20, waiting for 13 jobs
2025-11-01 20:32:47 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.13, running 13 = ∑13/20, new result: VAL_ACC: 67.080000
2025-11-01 20:32:50 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.13, running 12 = ∑12/20, waiting for 13 jobs, finished 1 job
2025-11-01 20:32:50 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.13, running 12 = ∑12/20, waiting for 12 jobs
2025-11-01 20:32:54 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.13, running 12 = ∑12/20, new result: VAL_ACC: 66.700000
2025-11-01 20:32:58 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.13, running 11 = ∑11/20, waiting for 12 jobs, finished 1 job
2025-11-01 20:32:58 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.13, running 11 = ∑11/20, waiting for 11 jobs
2025-11-01 20:33:10 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.13, running 11 = ∑11/20, new result: VAL_ACC: 67.790000
2025-11-01 20:33:13 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running 10 = ∑10/20, waiting for 11 jobs, finished 1 job
2025-11-01 20:33:14 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running 10 = ∑10/20, waiting for 10 jobs
2025-11-01 20:33:25 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running 10 = ∑10/20, new result: VAL_ACC: 66.990000
2025-11-01 20:33:28 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running 9 = ∑9/20, waiting for 10 jobs, finished 1 job
2025-11-01 20:33:28 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running 9 = ∑9/20, waiting for 9 jobs
2025-11-01 20:33:34 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running 9 = ∑9/20, new result: VAL_ACC: 67.140000
2025-11-01 20:33:38 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running 8 = ∑8/20, waiting for 9 jobs, finished 1 job
2025-11-01 20:33:38 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running 8 = ∑8/20, waiting for 8 jobs
2025-11-01 20:33:47 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running 8 = ∑8/20, new result: VAL_ACC: 66.800000
2025-11-01 20:33:50 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running 7 = ∑7/20, waiting for 8 jobs, finished 1 job
2025-11-01 20:33:50 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running 7 = ∑7/20, waiting for 7 jobs
2025-11-01 20:33:52 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running 7 = ∑7/20, new result: VAL_ACC: 67.390000
2025-11-01 20:33:52 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running 7 = ∑7/20, new result: VAL_ACC: 66.990000
2025-11-01 20:33:57 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running 5 = ∑5/20, waiting for 7 jobs, finished 2 jobs
2025-11-01 20:33:57 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running 5 = ∑5/20, waiting for 5 jobs
2025-11-01 20:33:58 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running 5 = ∑5/20, new result: VAL_ACC: 66.160000
2025-11-01 20:34:01 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running 4 = ∑4/20, waiting for 5 jobs, finished 1 job
2025-11-01 20:34:01 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running 4 = ∑4/20, waiting for 4 jobs
2025-11-01 20:34:10 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running 4 = ∑4/20, new result: VAL_ACC: 66.720000
2025-11-01 20:34:13 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running 3 = ∑3/20, waiting for 4 jobs, finished 1 job
2025-11-01 20:34:13 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running 3 = ∑3/20, waiting for 3 jobs
2025-11-01 20:34:14 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running 3 = ∑3/20, new result: VAL_ACC: 67.300000
2025-11-01 20:34:17 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running 2 = ∑2/20, waiting for 3 jobs, finished 1 job
2025-11-01 20:34:17 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running 2 = ∑2/20, waiting for 2 jobs
2025-11-01 20:34:21 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running 2 = ∑2/20, new result: VAL_ACC: 67.160000
2025-11-01 20:34:25 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running 1 = ∑1/20, waiting for 2 jobs, finished 1 job
2025-11-01 20:34:25 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running 1 = ∑1/20, waiting for 1 job
2025-11-01 20:34:30 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running 1 = ∑1/20, new result: VAL_ACC: 67.410000
2025-11-01 20:34:34 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, waiting for 1 job, finished 1 job
2025-11-01 20:35:22 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, getting new HP set #1/20
2025-11-01 20:35:22 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, getting new HP set #2/20
2025-11-01 20:35:24 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, getting new HP set #3/20
2025-11-01 20:35:24 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, getting new HP set #4/20
2025-11-01 20:35:24 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, getting new HP set #5/20
2025-11-01 20:35:24 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, getting new HP set #6/20
2025-11-01 20:35:24 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, getting new HP set #7/20
2025-11-01 20:35:24 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, getting new HP set #8/20
2025-11-01 20:35:24 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, getting new HP set #9/20
2025-11-01 20:35:25 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, getting new HP set #10/20
2025-11-01 20:35:25 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, getting new HP set #11/20
2025-11-01 20:35:25 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, getting new HP set #12/20
2025-11-01 20:35:25 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, getting new HP set #13/20
2025-11-01 20:35:25 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, getting new HP set #14/20
2025-11-01 20:35:26 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, getting new HP set #15/20
2025-11-01 20:35:26 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, getting new HP set #16/20
2025-11-01 20:35:27 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, getting new HP set #17/20
2025-11-01 20:35:27 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, getting new HP set #18/20
2025-11-01 20:35:27 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, getting new HP set #19/20
2025-11-01 20:35:27 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, getting new HP set #20/20
2025-11-01 20:35:27 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, requested 20 jobs, got 20, 2.64 s/job
2025-11-01 20:35:28 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, eval #1/20 start
2025-11-01 20:35:29 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, eval #2/20 start
2025-11-01 20:35:29 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, eval #3/20 start
2025-11-01 20:35:30 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, eval #4/20 start
2025-11-01 20:35:36 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, eval #5/20 start
2025-11-01 20:35:38 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, eval #6/20 start
2025-11-01 20:35:38 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, eval #7/20 start
2025-11-01 20:35:40 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, eval #8/20 start
2025-11-01 20:35:41 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, eval #9/20 start
2025-11-01 20:35:41 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, eval #10/20 start
2025-11-01 20:35:41 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, eval #11/20 start
2025-11-01 20:35:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, eval #12/20 start
2025-11-01 20:35:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, eval #13/20 start
2025-11-01 20:35:43 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, eval #14/20 start
2025-11-01 20:35:43 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, eval #15/20 start
2025-11-01 20:35:43 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, eval #16/20 start
2025-11-01 20:35:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, eval #17/20 start
2025-11-01 20:35:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, eval #18/20 start
2025-11-01 20:35:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, eval #19/20 start
2025-11-01 20:35:46 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, eval #20/20 start
2025-11-01 20:35:48 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, starting new job
2025-11-01 20:35:49 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, unknown 2 = ∑2/20, started new job
2025-11-01 20:35:49 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, unknown 2 = ∑2/20, starting new job
2025-11-01 20:35:59 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running/unknown 2/2 = ∑4/20, started new job
2025-11-01 20:35:59 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running/unknown 2/2 = ∑4/20, starting new job
2025-11-01 20:36:00 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running/unknown 2/3 = ∑5/20, started new job
2025-11-01 20:36:04 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running/pending/unknown 2/3/1 = ∑6/20, started new job
2025-11-01 20:36:09 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running/unknown 6/1 = ∑7/20, started new job
2025-11-01 20:36:14 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running/pending/unknown 6/1/1 = ∑8/20, started new job
2025-11-01 20:36:19 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running/pending/unknown 6/2/1 = ∑9/20, started new job
2025-11-01 20:36:24 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running/unknown 9/1 = ∑10/20, started new job
2025-11-01 20:36:29 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running/unknown 10/1 = ∑11/20, started new job
2025-11-01 20:36:34 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running/pending/unknown 10/1/1 = ∑12/20, started new job
2025-11-01 20:36:39 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running/pending/unknown 10/2/1 = ∑13/20, started new job
2025-11-01 20:36:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running/pending/unknown 10/3/1 = ∑14/20, started new job
2025-11-01 20:36:49 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running/unknown 14/1 = ∑15/20, started new job
2025-11-01 20:36:54 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running/unknown 15/1 = ∑16/20, started new job
2025-11-01 20:36:59 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running/pending/unknown 15/1/1 = ∑17/20, started new job
2025-11-01 20:37:04 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running/pending/unknown 15/2/1 = ∑18/20, started new job
2025-11-01 20:37:09 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running/unknown 18/1 = ∑19/20, started new job
2025-11-01 20:37:14 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running/pending/unknown 18/1/1 = ∑20/20, started new job
2025-11-01 20:37:15 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running/pending/unknown 18/1/1 = ∑20/20, waiting for 20 jobs
2025-11-01 20:37:20 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running/pending 18/2 = ∑20/20, waiting for 20 jobs
2025-11-01 20:37:26 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running 20 = ∑20/20, waiting for 20 jobs
2025-11-01 21:45:39 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 67.79, running 20 = ∑20/20, new result: VAL_ACC: 69.870000
2025-11-01 21:45:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 69.87, running 19 = ∑19/20, waiting for 20 jobs, finished 1 job
2025-11-01 21:45:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 69.87, running 19 = ∑19/20, waiting for 19 jobs
2025-11-01 22:25:05 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 69.87, running 19 = ∑19/20, new result: VAL_ACC: 69.580000
2025-11-01 22:25:10 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 69.87, running 18 = ∑18/20, waiting for 19 jobs, finished 1 job
2025-11-01 22:25:10 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 69.87, running 18 = ∑18/20, waiting for 18 jobs
2025-11-01 22:28:16 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 69.87, running 18 = ∑18/20, new result: VAL_ACC: 69.250000
2025-11-01 22:28:21 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 69.87, running 17 = ∑17/20, waiting for 18 jobs, finished 1 job
2025-11-01 22:28:21 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 69.87, running 17 = ∑17/20, waiting for 17 jobs
2025-11-01 22:30:06 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 69.87, running 17 = ∑17/20, new result: VAL_ACC: 70.270000
2025-11-01 22:30:11 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.27, running 16 = ∑16/20, waiting for 17 jobs, finished 1 job
2025-11-01 22:30:11 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.27, running 16 = ∑16/20, waiting for 16 jobs
2025-11-01 22:47:43 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.27, running 16 = ∑16/20, new result: VAL_ACC: 70.190000
2025-11-01 22:47:48 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.27, running 15 = ∑15/20, waiting for 16 jobs, finished 1 job
2025-11-01 22:47:48 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.27, running 15 = ∑15/20, waiting for 15 jobs
2025-11-01 22:48:35 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.27, running 15 = ∑15/20, new result: VAL_ACC: 70.430000
2025-11-01 22:48:40 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.43, running 14 = ∑14/20, waiting for 15 jobs, finished 1 job
2025-11-01 22:48:40 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.43, running 14 = ∑14/20, waiting for 14 jobs
2025-11-01 22:48:48 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.43, running 14 = ∑14/20, new result: VAL_ACC: 70.620000
2025-11-01 22:48:53 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 13 = ∑13/20, waiting for 14 jobs, finished 1 job
2025-11-01 22:48:53 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 13 = ∑13/20, waiting for 13 jobs
2025-11-01 22:49:36 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 13 = ∑13/20, new result: VAL_ACC: 69.540000
2025-11-01 22:49:40 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 12 = ∑12/20, waiting for 13 jobs, finished 1 job
2025-11-01 22:49:40 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 12 = ∑12/20, waiting for 12 jobs
2025-11-01 22:50:15 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 12 = ∑12/20, new result: VAL_ACC: 70.230000
2025-11-01 22:50:20 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 11 = ∑11/20, waiting for 12 jobs, finished 1 job
2025-11-01 22:50:20 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 11 = ∑11/20, waiting for 11 jobs
2025-11-01 22:50:27 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 11 = ∑11/20, new result: VAL_ACC: 69.900000
2025-11-01 22:50:32 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 10 = ∑10/20, waiting for 11 jobs, finished 1 job
2025-11-01 22:50:32 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 10 = ∑10/20, waiting for 10 jobs
2025-11-01 22:50:38 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 10 = ∑10/20, new result: VAL_ACC: 69.650000
2025-11-01 22:50:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 9 = ∑9/20, waiting for 10 jobs, finished 1 job
2025-11-01 22:50:43 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 9 = ∑9/20, waiting for 9 jobs
2025-11-01 22:50:43 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 9 = ∑9/20, new result: VAL_ACC: 69.660000
2025-11-01 22:50:48 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 8 = ∑8/20, waiting for 9 jobs, finished 1 job
2025-11-01 22:50:48 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 8 = ∑8/20, waiting for 8 jobs
2025-11-01 22:50:53 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 8 = ∑8/20, new result: VAL_ACC: 70.090000
2025-11-01 22:50:57 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 7 = ∑7/20, waiting for 8 jobs, finished 1 job
2025-11-01 22:50:58 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 7 = ∑7/20, waiting for 7 jobs
2025-11-01 22:50:59 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 7 = ∑7/20, new result: VAL_ACC: 69.570000
2025-11-01 22:50:59 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 7 = ∑7/20, new result: VAL_ACC: 70.110000
2025-11-01 22:51:08 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 5 = ∑5/20, waiting for 7 jobs, finished 2 jobs
2025-11-01 22:51:08 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 5 = ∑5/20, waiting for 5 jobs
2025-11-01 22:51:08 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 5 = ∑5/20, new result: VAL_ACC: 69.950000
2025-11-01 22:51:13 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 4 = ∑4/20, waiting for 5 jobs, finished 1 job
2025-11-01 22:51:13 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 4 = ∑4/20, waiting for 4 jobs
2025-11-01 22:51:36 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 4 = ∑4/20, new result: VAL_ACC: 69.940000
2025-11-01 22:51:40 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 3 = ∑3/20, waiting for 4 jobs, finished 1 job
2025-11-01 22:51:40 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 3 = ∑3/20, waiting for 3 jobs
2025-11-01 22:51:51 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 3 = ∑3/20, new result: VAL_ACC: 70.250000
2025-11-01 22:51:55 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 2 = ∑2/20, waiting for 3 jobs, finished 1 job
2025-11-01 22:51:55 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 2 = ∑2/20, waiting for 2 jobs
2025-11-01 22:52:23 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 2 = ∑2/20, new result: VAL_ACC: 70.330000
2025-11-01 22:52:28 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 1 = ∑1/20, waiting for 2 jobs, finished 1 job
2025-11-01 22:52:28 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 1 = ∑1/20, waiting for 1 job
2025-11-01 22:52:39 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 1 = ∑1/20, new result: VAL_ACC: 69.960000
2025-11-01 22:52:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, waiting for 1 job, finished 1 job
2025-11-01 22:53:34 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, getting new HP set #1/20
2025-11-01 22:53:34 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, getting new HP set #2/20
2025-11-01 22:53:34 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, getting new HP set #3/20
2025-11-01 22:53:34 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, getting new HP set #4/20
2025-11-01 22:53:35 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, getting new HP set #5/20
2025-11-01 22:53:35 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, getting new HP set #6/20
2025-11-01 22:53:35 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, getting new HP set #7/20
2025-11-01 22:53:35 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, getting new HP set #8/20
2025-11-01 22:53:35 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, getting new HP set #9/20
2025-11-01 22:53:35 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, getting new HP set #10/20
2025-11-01 22:53:36 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, getting new HP set #11/20
2025-11-01 22:53:36 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, getting new HP set #12/20
2025-11-01 22:53:36 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, getting new HP set #13/20
2025-11-01 22:53:36 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, getting new HP set #14/20
2025-11-01 22:53:36 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, getting new HP set #15/20
2025-11-01 22:53:36 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, getting new HP set #16/20
2025-11-01 22:53:37 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, getting new HP set #17/20
2025-11-01 22:53:37 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, getting new HP set #18/20
2025-11-01 22:53:37 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, getting new HP set #19/20
2025-11-01 22:53:37 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, getting new HP set #20/20
2025-11-01 22:53:37 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, requested 20 jobs, got 20, 2.57 s/job
2025-11-01 22:53:38 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, eval #1/20 start
2025-11-01 22:53:39 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, eval #2/20 start
2025-11-01 22:53:40 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, eval #3/20 start
2025-11-01 22:53:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, eval #4/20 start
2025-11-01 22:53:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, eval #5/20 start
2025-11-01 22:53:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, eval #6/20 start
2025-11-01 22:53:43 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, eval #7/20 start
2025-11-01 22:53:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, eval #8/20 start
2025-11-01 22:53:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, eval #9/20 start
2025-11-01 22:53:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, eval #10/20 start
2025-11-01 22:53:45 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, eval #11/20 start
2025-11-01 22:53:45 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, eval #12/20 start
2025-11-01 22:53:46 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, eval #13/20 start
2025-11-01 22:53:46 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, eval #14/20 start
2025-11-01 22:53:47 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, eval #15/20 start
2025-11-01 22:53:48 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, eval #16/20 start
2025-11-01 22:53:49 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, eval #17/20 start
2025-11-01 22:53:49 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, eval #18/20 start
2025-11-01 22:53:51 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, eval #19/20 start
2025-11-01 22:53:51 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, eval #20/20 start
2025-11-01 22:53:55 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, starting new job
2025-11-01 22:53:57 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, unknown 2 = ∑2/20, started new job
2025-11-01 22:53:57 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, unknown 2 = ∑2/20, starting new job
2025-11-01 22:54:01 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, pending/unknown 2/2 = ∑4/20, started new job
2025-11-01 22:54:02 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, pending/unknown 2/2 = ∑4/20, starting new job
2025-11-01 22:54:06 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, pending/unknown 4/2 = ∑6/20, started new job
2025-11-01 22:54:11 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, pending/unknown 6/2 = ∑8/20, started new job
2025-11-01 22:54:16 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running/unknown 8/1 = ∑9/20, started new job
2025-11-01 22:54:21 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running/unknown 9/1 = ∑10/20, started new job
2025-11-01 22:54:26 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running/pending/unknown 9/1/1 = ∑11/20, started new job
2025-11-01 22:54:31 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running/pending/unknown 9/2/2 = ∑13/20, started new job
2025-11-01 22:54:37 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running/unknown 13/1 = ∑14/20, started new job
2025-11-01 22:54:41 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running/pending/unknown 13/1/2 = ∑16/20, started new job
2025-11-01 22:54:46 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running/pending/unknown 13/3/1 = ∑17/20, started new job
2025-11-01 22:54:51 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running/unknown 17/1 = ∑18/20, started new job
2025-11-01 22:55:02 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running/unknown 18/1 = ∑19/20, started new job
2025-11-01 22:55:06 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running/pending/unknown 18/1/1 = ∑20/20, started new job
2025-11-01 22:55:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running/pending/unknown 18/1/1 = ∑20/20, waiting for 20 jobs
2025-11-01 22:55:11 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running/pending 18/2 = ∑20/20, waiting for 20 jobs
2025-11-01 22:55:17 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 20 = ∑20/20, waiting for 20 jobs
2025-11-02 00:59:00 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 20 = ∑20/20, new result: VAL_ACC: 68.080000
2025-11-02 00:59:13 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 19 = ∑19/20, waiting for 20 jobs, finished 1 job
2025-11-02 00:59:13 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 19 = ∑19/20, waiting for 19 jobs
2025-11-02 00:59:14 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 19 = ∑19/20, new result: VAL_ACC: 68.210000
2025-11-02 00:59:20 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 18 = ∑18/20, waiting for 19 jobs, finished 1 job
2025-11-02 00:59:20 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 18 = ∑18/20, waiting for 18 jobs
2025-11-02 00:59:30 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 18 = ∑18/20, new result: VAL_ACC: 68.490000
2025-11-02 00:59:30 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 18 = ∑18/20, new result: VAL_ACC: 69.390000
2025-11-02 00:59:39 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 16 = ∑16/20, waiting for 18 jobs, finished 2 jobs
2025-11-02 00:59:39 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 16 = ∑16/20, waiting for 16 jobs
2025-11-02 00:59:47 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 16 = ∑16/20, new result: VAL_ACC: 68.350000
2025-11-02 00:59:54 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 15 = ∑15/20, waiting for 16 jobs, finished 1 job
2025-11-02 00:59:54 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 15 = ∑15/20, waiting for 15 jobs
2025-11-02 00:59:55 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 15 = ∑15/20, new result: VAL_ACC: 69.410000
2025-11-02 01:00:01 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 14 = ∑14/20, waiting for 15 jobs, finished 1 job
2025-11-02 01:00:02 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 14 = ∑14/20, waiting for 14 jobs
2025-11-02 01:00:02 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 14 = ∑14/20, new result: VAL_ACC: 68.840000
2025-11-02 01:00:09 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 13 = ∑13/20, waiting for 14 jobs, finished 1 job
2025-11-02 01:00:10 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 13 = ∑13/20, waiting for 13 jobs
2025-11-02 01:00:12 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 13 = ∑13/20, new result: VAL_ACC: 68.420000
2025-11-02 01:00:18 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 12 = ∑12/20, waiting for 13 jobs, finished 1 job
2025-11-02 01:00:18 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 12 = ∑12/20, waiting for 12 jobs
2025-11-02 01:00:31 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 12 = ∑12/20, new result: VAL_ACC: 69.340000
2025-11-02 01:00:37 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 11 = ∑11/20, waiting for 12 jobs, finished 1 job
2025-11-02 01:00:37 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 11 = ∑11/20, waiting for 11 jobs
2025-11-02 01:00:41 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 11 = ∑11/20, new result: VAL_ACC: 68.210000
2025-11-02 01:00:48 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 10 = ∑10/20, waiting for 11 jobs, finished 1 job
2025-11-02 01:00:48 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 10 = ∑10/20, waiting for 10 jobs
2025-11-02 01:00:49 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 10 = ∑10/20, new result: VAL_ACC: 69.540000
2025-11-02 01:00:49 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 10 = ∑10/20, new result: VAL_ACC: 68.990000
2025-11-02 01:00:49 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 10 = ∑10/20, new result: VAL_ACC: 68.680000
2025-11-02 01:01:03 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 7 = ∑7/20, waiting for 10 jobs, finished 3 jobs
2025-11-02 01:01:03 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 7 = ∑7/20, waiting for 7 jobs
2025-11-02 01:01:04 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 7 = ∑7/20, new result: VAL_ACC: 68.790000
2025-11-02 01:01:04 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 7 = ∑7/20, new result: VAL_ACC: 68.550000
2025-11-02 01:01:13 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 5 = ∑5/20, waiting for 7 jobs, finished 2 jobs
2025-11-02 01:01:13 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 5 = ∑5/20, waiting for 5 jobs
2025-11-02 01:01:15 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 5 = ∑5/20, new result: VAL_ACC: 69.200000
2025-11-02 01:01:15 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 5 = ∑5/20, new result: VAL_ACC: 68.280000
2025-11-02 01:01:15 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 5 = ∑5/20, new result: VAL_ACC: 68.630000
2025-11-02 01:01:29 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 2 = ∑2/20, waiting for 5 jobs, finished 3 jobs
2025-11-02 01:01:29 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 2 = ∑2/20, waiting for 2 jobs
2025-11-02 01:01:30 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 2 = ∑2/20, new result: VAL_ACC: 68.700000
2025-11-02 01:01:37 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 1 = ∑1/20, waiting for 2 jobs, finished 1 job
2025-11-02 01:01:37 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 1 = ∑1/20, waiting for 1 job
2025-11-02 01:01:40 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 1 = ∑1/20, new result: VAL_ACC: 69.060000
2025-11-02 01:01:47 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, waiting for 1 job, finished 1 job
2025-11-02 01:02:41 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, getting new HP set #1/20
2025-11-02 01:02:41 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, getting new HP set #2/20
2025-11-02 01:02:41 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, getting new HP set #3/20
2025-11-02 01:02:41 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, getting new HP set #4/20
2025-11-02 01:02:41 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, getting new HP set #5/20
2025-11-02 01:02:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, getting new HP set #6/20
2025-11-02 01:02:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, getting new HP set #7/20
2025-11-02 01:02:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, getting new HP set #8/20
2025-11-02 01:02:43 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, getting new HP set #9/20
2025-11-02 01:02:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, getting new HP set #10/20
2025-11-02 01:02:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, getting new HP set #11/20
2025-11-02 01:02:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, getting new HP set #12/20
2025-11-02 01:02:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, getting new HP set #13/20
2025-11-02 01:02:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, getting new HP set #14/20
2025-11-02 01:02:45 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, getting new HP set #15/20
2025-11-02 01:02:45 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, getting new HP set #16/20
2025-11-02 01:02:45 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, getting new HP set #17/20
2025-11-02 01:02:45 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, getting new HP set #18/20
2025-11-02 01:02:46 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, getting new HP set #19/20
2025-11-02 01:02:46 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, getting new HP set #20/20
2025-11-02 01:02:46 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, requested 20 jobs, got 20, 2.93 s/job
2025-11-02 01:02:47 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, eval #1/20 start
2025-11-02 01:02:47 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, eval #2/20 start
2025-11-02 01:02:48 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, eval #3/20 start
2025-11-02 01:02:49 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, eval #4/20 start
2025-11-02 01:02:49 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, eval #5/20 start
2025-11-02 01:02:50 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, eval #6/20 start
2025-11-02 01:02:53 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, eval #7/20 start
2025-11-02 01:02:53 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, eval #8/20 start
2025-11-02 01:02:55 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, eval #9/20 start
2025-11-02 01:02:56 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, eval #10/20 start
2025-11-02 01:02:56 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, eval #11/20 start
2025-11-02 01:02:58 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, eval #12/20 start
2025-11-02 01:02:59 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, eval #13/20 start
2025-11-02 01:03:00 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, eval #14/20 start
2025-11-02 01:03:02 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, eval #15/20 start
2025-11-02 01:03:02 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, eval #16/20 start
2025-11-02 01:03:03 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, eval #17/20 start
2025-11-02 01:03:04 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, eval #18/20 start
2025-11-02 01:03:04 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, eval #19/20 start
2025-11-02 01:03:06 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, eval #20/20 start
2025-11-02 01:03:11 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, starting new job
2025-11-02 01:03:13 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, pending/unknown 2/1 = ∑3/20, started new job
2025-11-02 01:03:14 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, pending/unknown 2/1 = ∑3/20, starting new job
2025-11-02 01:03:23 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running/unknown 3/2 = ∑5/20, started new job
2025-11-02 01:03:23 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running/unknown 3/2 = ∑5/20, starting new job
2025-11-02 01:03:27 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running/pending/unknown 3/2/1 = ∑6/20, started new job
2025-11-02 01:03:37 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running/unknown 6/1 = ∑7/20, started new job
2025-11-02 01:03:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running/pending/unknown 6/1/1 = ∑8/20, started new job
2025-11-02 01:03:48 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running/pending/unknown 6/2/2 = ∑10/20, started new job
2025-11-02 01:03:53 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running/unknown 10/2 = ∑12/20, started new job
2025-11-02 01:03:57 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running/pending/unknown 10/2/1 = ∑13/20, started new job
2025-11-02 01:04:03 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running/pending/unknown 10/3/2 = ∑15/20, started new job
2025-11-02 01:04:08 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running/pending/unknown 10/5/2 = ∑17/20, started new job
2025-11-02 01:04:12 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running/pending 17/1 = ∑18/20, started new job
2025-11-02 01:04:17 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running/pending 17/2 = ∑19/20, started new job
2025-11-02 01:04:22 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running/pending 19/1 = ∑20/20, started new job
2025-11-02 01:04:24 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running/pending 19/1 = ∑20/20, waiting for 20 jobs
2025-11-02 01:04:37 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 20 = ∑20/20, waiting for 20 jobs
2025-11-02 03:07:46 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 20 = ∑20/20, new result: VAL_ACC: 70.220000
2025-11-02 03:07:54 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 19 = ∑19/20, waiting for 20 jobs, finished 1 job
2025-11-02 03:07:55 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 19 = ∑19/20, waiting for 19 jobs
2025-11-02 03:07:55 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.62, running 19 = ∑19/20, new result: VAL_ACC: 70.900000
2025-11-02 03:08:03 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 18 = ∑18/20, waiting for 19 jobs, finished 1 job
2025-11-02 03:08:03 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 18 = ∑18/20, waiting for 18 jobs
2025-11-02 03:08:04 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 18 = ∑18/20, new result: VAL_ACC: 70.180000
2025-11-02 03:08:11 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 17 = ∑17/20, waiting for 18 jobs, finished 1 job
2025-11-02 03:08:12 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 17 = ∑17/20, waiting for 17 jobs
2025-11-02 03:08:45 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 17 = ∑17/20, new result: VAL_ACC: 70.550000
2025-11-02 03:08:53 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 16 = ∑16/20, waiting for 17 jobs, finished 1 job
2025-11-02 03:08:53 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 16 = ∑16/20, waiting for 16 jobs
2025-11-02 03:08:54 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 16 = ∑16/20, new result: VAL_ACC: 70.800000
2025-11-02 03:09:02 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 15 = ∑15/20, waiting for 16 jobs, finished 1 job
2025-11-02 03:09:02 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 15 = ∑15/20, waiting for 15 jobs
2025-11-02 03:09:03 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 15 = ∑15/20, new result: VAL_ACC: 69.860000
2025-11-02 03:09:10 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 14 = ∑14/20, waiting for 15 jobs, finished 1 job
2025-11-02 03:09:10 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 14 = ∑14/20, waiting for 14 jobs
2025-11-02 03:09:18 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 14 = ∑14/20, new result: VAL_ACC: 70.320000
2025-11-02 03:09:26 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 13 = ∑13/20, waiting for 14 jobs, finished 1 job
2025-11-02 03:09:26 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 13 = ∑13/20, waiting for 13 jobs
2025-11-02 03:09:28 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 13 = ∑13/20, new result: VAL_ACC: 70.520000
2025-11-02 03:09:28 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 13 = ∑13/20, new result: VAL_ACC: 70.110000
2025-11-02 03:09:39 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 11 = ∑11/20, waiting for 13 jobs, finished 2 jobs
2025-11-02 03:09:39 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 11 = ∑11/20, waiting for 11 jobs
2025-11-02 03:09:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 11 = ∑11/20, new result: VAL_ACC: 70.260000
2025-11-02 03:09:50 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 10 = ∑10/20, waiting for 11 jobs, finished 1 job
2025-11-02 03:09:50 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 10 = ∑10/20, waiting for 10 jobs
2025-11-02 03:09:53 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 10 = ∑10/20, new result: VAL_ACC: 70.340000
2025-11-02 03:10:00 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 9 = ∑9/20, waiting for 10 jobs, finished 1 job
2025-11-02 03:10:00 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 9 = ∑9/20, waiting for 9 jobs
2025-11-02 03:10:01 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 9 = ∑9/20, new result: VAL_ACC: 70.230000
2025-11-02 03:10:01 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 9 = ∑9/20, new result: VAL_ACC: 70.340000
2025-11-02 03:10:13 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 7 = ∑7/20, waiting for 9 jobs, finished 2 jobs
2025-11-02 03:10:14 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 7 = ∑7/20, waiting for 7 jobs
2025-11-02 03:10:43 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 7 = ∑7/20, new result: VAL_ACC: 70.490000
2025-11-02 03:10:50 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 6 = ∑6/20, waiting for 7 jobs, finished 1 job
2025-11-02 03:10:50 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 6 = ∑6/20, waiting for 6 jobs
2025-11-02 03:10:51 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 6 = ∑6/20, new result: VAL_ACC: 70.370000
2025-11-02 03:10:58 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 5 = ∑5/20, waiting for 6 jobs, finished 1 job
2025-11-02 03:10:59 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 5 = ∑5/20, waiting for 5 jobs
2025-11-02 03:11:35 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 5 = ∑5/20, new result: VAL_ACC: 70.390000
2025-11-02 03:11:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 4 = ∑4/20, waiting for 5 jobs, finished 1 job
2025-11-02 03:11:43 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 4 = ∑4/20, waiting for 4 jobs
2025-11-02 03:11:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 4 = ∑4/20, new result: VAL_ACC: 69.900000
2025-11-02 03:11:51 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 3 = ∑3/20, waiting for 4 jobs, finished 1 job
2025-11-02 03:11:52 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 3 = ∑3/20, waiting for 3 jobs
2025-11-02 03:14:36 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 3 = ∑3/20, new result: VAL_ACC: 70.530000
2025-11-02 03:14:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 2 = ∑2/20, waiting for 3 jobs, finished 1 job
2025-11-02 03:14:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 2 = ∑2/20, waiting for 2 jobs
2025-11-02 03:20:08 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 2 = ∑2/20, new result: VAL_ACC: 70.480000
2025-11-02 03:20:16 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 1 = ∑1/20, waiting for 2 jobs, finished 1 job
2025-11-02 03:20:17 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 1 = ∑1/20, waiting for 1 job
2025-11-02 03:20:30 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 1 = ∑1/20, new result: VAL_ACC: 70.590000
2025-11-02 03:20:38 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, waiting for 1 job, finished 1 job
2025-11-02 03:21:51 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, getting new HP set #1/20
2025-11-02 03:21:52 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, getting new HP set #2/20
2025-11-02 03:21:52 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, getting new HP set #3/20
2025-11-02 03:21:52 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, getting new HP set #4/20
2025-11-02 03:21:53 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, getting new HP set #5/20
2025-11-02 03:21:53 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, getting new HP set #6/20
2025-11-02 03:21:53 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, getting new HP set #7/20
2025-11-02 03:21:53 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, getting new HP set #8/20
2025-11-02 03:21:54 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, getting new HP set #9/20
2025-11-02 03:21:54 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, getting new HP set #10/20
2025-11-02 03:21:54 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, getting new HP set #11/20
2025-11-02 03:21:54 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, getting new HP set #12/20
2025-11-02 03:21:55 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, getting new HP set #13/20
2025-11-02 03:21:55 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, getting new HP set #14/20
2025-11-02 03:21:55 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, getting new HP set #15/20
2025-11-02 03:21:55 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, getting new HP set #16/20
2025-11-02 03:21:56 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, getting new HP set #17/20
2025-11-02 03:21:56 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, getting new HP set #18/20
2025-11-02 03:21:56 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, getting new HP set #19/20
2025-11-02 03:21:56 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, getting new HP set #20/20
2025-11-02 03:21:57 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, requested 20 jobs, got 20, 3.90 s/job
2025-11-02 03:21:58 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, eval #1/20 start
2025-11-02 03:21:59 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, eval #2/20 start
2025-11-02 03:21:59 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, eval #3/20 start
2025-11-02 03:22:00 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, eval #4/20 start
2025-11-02 03:22:01 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, eval #5/20 start
2025-11-02 03:22:03 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, eval #6/20 start
2025-11-02 03:22:03 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, eval #7/20 start
2025-11-02 03:22:04 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, eval #8/20 start
2025-11-02 03:22:05 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, eval #9/20 start
2025-11-02 03:22:05 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, eval #10/20 start
2025-11-02 03:22:06 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, eval #11/20 start
2025-11-02 03:22:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, eval #12/20 start
2025-11-02 03:22:08 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, eval #13/20 start
2025-11-02 03:22:08 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, eval #14/20 start
2025-11-02 03:22:09 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, eval #15/20 start
2025-11-02 03:22:10 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, eval #16/20 start
2025-11-02 03:22:12 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, eval #17/20 start
2025-11-02 03:22:12 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, eval #18/20 start
2025-11-02 03:22:13 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, eval #19/20 start
2025-11-02 03:22:14 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, eval #20/20 start
2025-11-02 03:22:20 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, starting new job
2025-11-02 03:22:22 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, pending 3 = ∑3/20, started new job
2025-11-02 03:22:24 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, pending 3 = ∑3/20, starting new job
2025-11-02 03:22:27 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running/unknown 3/1 = ∑4/20, started new job
2025-11-02 03:22:27 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running/unknown 3/1 = ∑4/20, starting new job
2025-11-02 03:22:37 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running/unknown 4/2 = ∑6/20, started new job
2025-11-02 03:22:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running/pending 6/2 = ∑8/20, started new job
2025-11-02 03:22:47 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running/unknown 8/1 = ∑9/20, started new job
2025-11-02 03:22:53 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running/pending/unknown 8/1/3 = ∑12/20, started new job
2025-11-02 03:22:58 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running/pending/unknown 8/4/3 = ∑15/20, started new job
2025-11-02 03:23:03 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running/pending 15/3 = ∑18/20, started new job
2025-11-02 03:23:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running/unknown 18/2 = ∑20/20, started new job
2025-11-02 03:23:09 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running/unknown 18/2 = ∑20/20, waiting for 20 jobs
2025-11-02 03:23:12 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running/pending 18/2 = ∑20/20, waiting for 20 jobs
2025-11-02 03:23:32 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 20 = ∑20/20, waiting for 20 jobs
2025-11-02 05:31:33 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 20 = ∑20/20, new result: VAL_ACC: 70.610000
2025-11-02 05:31:43 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 19 = ∑19/20, waiting for 20 jobs, finished 1 job
2025-11-02 05:31:43 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 19 = ∑19/20, waiting for 19 jobs
2025-11-02 05:31:55 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 19 = ∑19/20, new result: VAL_ACC: 70.380000
2025-11-02 05:32:04 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 18 = ∑18/20, waiting for 19 jobs, finished 1 job
2025-11-02 05:32:04 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 18 = ∑18/20, waiting for 18 jobs
2025-11-02 05:32:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 18 = ∑18/20, new result: VAL_ACC: 70.750000
2025-11-02 05:32:16 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 17 = ∑17/20, waiting for 18 jobs, finished 1 job
2025-11-02 05:32:16 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 17 = ∑17/20, waiting for 17 jobs
2025-11-02 05:32:53 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 70.9, running 17 = ∑17/20, new result: VAL_ACC: 71.220000
2025-11-02 05:33:03 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.22, running 16 = ∑16/20, waiting for 17 jobs, finished 1 job
2025-11-02 05:33:03 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.22, running 16 = ∑16/20, waiting for 16 jobs
2025-11-02 05:33:28 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.22, running 16 = ∑16/20, new result: VAL_ACC: 71.480000
2025-11-02 05:33:28 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.22, running 16 = ∑16/20, new result: VAL_ACC: 70.480000
2025-11-02 05:33:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 14 = ∑14/20, waiting for 16 jobs, finished 2 jobs
2025-11-02 05:33:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 14 = ∑14/20, waiting for 14 jobs
2025-11-02 05:33:43 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 14 = ∑14/20, new result: VAL_ACC: 70.880000
2025-11-02 05:33:52 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 13 = ∑13/20, waiting for 14 jobs, finished 1 job
2025-11-02 05:33:53 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 13 = ∑13/20, waiting for 13 jobs
2025-11-02 05:33:54 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 13 = ∑13/20, new result: VAL_ACC: 70.960000
2025-11-02 05:33:54 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 13 = ∑13/20, new result: VAL_ACC: 70.500000
2025-11-02 05:34:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 11 = ∑11/20, waiting for 13 jobs, finished 2 jobs
2025-11-02 05:34:08 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 11 = ∑11/20, waiting for 11 jobs
2025-11-02 05:34:09 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 11 = ∑11/20, new result: VAL_ACC: 70.440000
2025-11-02 05:34:18 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 10 = ∑10/20, waiting for 11 jobs, finished 1 job
2025-11-02 05:34:18 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 10 = ∑10/20, waiting for 10 jobs
2025-11-02 05:34:19 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 10 = ∑10/20, new result: VAL_ACC: 71.020000
2025-11-02 05:34:29 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 9 = ∑9/20, waiting for 10 jobs, finished 1 job
2025-11-02 05:34:30 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 9 = ∑9/20, waiting for 9 jobs
2025-11-02 05:34:31 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 9 = ∑9/20, new result: VAL_ACC: 71.400000
2025-11-02 05:34:40 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 8 = ∑8/20, waiting for 9 jobs, finished 1 job
2025-11-02 05:34:40 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 8 = ∑8/20, waiting for 8 jobs
2025-11-02 05:34:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 8 = ∑8/20, new result: VAL_ACC: 71.070000
2025-11-02 05:34:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 8 = ∑8/20, new result: VAL_ACC: 70.850000
2025-11-02 05:34:56 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 6 = ∑6/20, waiting for 8 jobs, finished 2 jobs
2025-11-02 05:34:57 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 6 = ∑6/20, waiting for 6 jobs
2025-11-02 05:35:02 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 6 = ∑6/20, new result: VAL_ACC: 71.170000
2025-11-02 05:35:11 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 5 = ∑5/20, waiting for 6 jobs, finished 1 job
2025-11-02 05:35:11 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 5 = ∑5/20, waiting for 5 jobs
2025-11-02 05:35:12 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 5 = ∑5/20, new result: VAL_ACC: 70.590000
2025-11-02 05:35:21 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 4 = ∑4/20, waiting for 5 jobs, finished 1 job
2025-11-02 05:35:22 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 4 = ∑4/20, waiting for 4 jobs
2025-11-02 05:36:08 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 4 = ∑4/20, new result: VAL_ACC: 70.770000
2025-11-02 05:36:18 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 3 = ∑3/20, waiting for 4 jobs, finished 1 job
2025-11-02 05:36:18 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 3 = ∑3/20, waiting for 3 jobs
2025-11-02 05:41:05 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 3 = ∑3/20, new result: VAL_ACC: 71.140000
2025-11-02 05:41:16 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 2 = ∑2/20, waiting for 3 jobs, finished 1 job
2025-11-02 05:41:16 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 2 = ∑2/20, waiting for 2 jobs
2025-11-02 05:45:35 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 2 = ∑2/20, new result: VAL_ACC: 70.990000
2025-11-02 05:45:45 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 1 = ∑1/20, waiting for 2 jobs, finished 1 job
2025-11-02 05:45:45 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 1 = ∑1/20, waiting for 1 job
2025-11-02 05:46:47 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 1 = ∑1/20, new result: VAL_ACC: 70.870000
2025-11-02 05:46:57 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, waiting for 1 job, finished 1 job
2025-11-02 05:48:11 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #1/20
2025-11-02 05:48:11 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #2/20
2025-11-02 05:48:12 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #3/20
2025-11-02 05:48:12 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #4/20
2025-11-02 05:48:12 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #5/20
2025-11-02 05:48:13 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #6/20
2025-11-02 05:48:14 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #7/20
2025-11-02 05:48:14 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #8/20
2025-11-02 05:48:14 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #9/20
2025-11-02 05:48:15 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #10/20
2025-11-02 05:48:15 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #11/20
2025-11-02 05:48:15 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #12/20
2025-11-02 05:48:16 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #13/20
2025-11-02 05:48:16 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #14/20
2025-11-02 05:48:16 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #15/20
2025-11-02 05:48:17 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #16/20
2025-11-02 05:48:17 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #17/20
2025-11-02 05:48:17 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #18/20
2025-11-02 05:48:17 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #19/20
2025-11-02 05:48:18 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #20/20
2025-11-02 05:48:18 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, requested 20 jobs, got 20, 4.03 s/job
2025-11-02 05:48:19 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #1/20 start
2025-11-02 05:48:20 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #2/20 start
2025-11-02 05:48:21 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #3/20 start
2025-11-02 05:48:22 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #4/20 start
2025-11-02 05:48:23 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #5/20 start
2025-11-02 05:48:23 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #6/20 start
2025-11-02 05:48:24 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #7/20 start
2025-11-02 05:48:25 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #8/20 start
2025-11-02 05:48:26 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #9/20 start
2025-11-02 05:48:28 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #10/20 start
2025-11-02 05:48:29 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #11/20 start
2025-11-02 05:48:30 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #12/20 start
2025-11-02 05:48:31 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #13/20 start
2025-11-02 05:48:31 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #14/20 start
2025-11-02 05:48:32 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #15/20 start
2025-11-02 05:48:33 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #16/20 start
2025-11-02 05:48:34 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #17/20 start
2025-11-02 05:48:35 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #18/20 start
2025-11-02 05:48:36 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #19/20 start
2025-11-02 05:48:37 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #20/20 start
2025-11-02 05:48:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, starting new job
2025-11-02 05:48:46 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, pending 1 = ∑1/20, started new job
2025-11-02 05:48:46 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, pending 1 = ∑1/20, starting new job
2025-11-02 05:48:50 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running/unknown 1/1 = ∑2/20, started new job
2025-11-02 05:48:51 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running/unknown 1/1 = ∑2/20, starting new job
2025-11-02 05:48:56 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running/pending/unknown 1/1/2 = ∑4/20, started new job
2025-11-02 05:48:57 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running/pending/unknown 1/1/2 = ∑4/20, starting new job
2025-11-02 05:49:01 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running/pending/unknown 1/3/3 = ∑7/20, started new job
2025-11-02 05:49:05 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running/unknown 7/1 = ∑8/20, started new job
2025-11-02 05:49:10 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running/pending/unknown 7/1/1 = ∑9/20, started new job
2025-11-02 05:49:15 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running/pending/unknown 7/2/1 = ∑10/20, started new job
2025-11-02 05:49:20 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running/pending/unknown 7/3/1 = ∑11/20, started new job
2025-11-02 05:49:31 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running/unknown 11/1 = ∑12/20, started new job
2025-11-02 05:49:40 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running/unknown 12/1 = ∑13/20, started new job
2025-11-02 05:49:45 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running/unknown 13/1 = ∑14/20, started new job
2025-11-02 05:49:51 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running/pending/unknown 13/1/3 = ∑17/20, started new job
2025-11-02 05:49:56 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running/pending/unknown 13/4/2 = ∑19/20, started new job
2025-11-02 05:49:56 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running/pending/unknown 13/4/3 = ∑20/20, started new job
2025-11-02 05:49:58 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running/pending 13/7 = ∑20/20, waiting for 20 jobs
2025-11-02 05:50:09 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 20 = ∑20/20, waiting for 20 jobs
2025-11-02 06:22:51 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 20 = ∑20/20, new result: VAL_ACC: 68.560000
2025-11-02 06:23:01 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 19 = ∑19/20, waiting for 20 jobs, finished 1 job
2025-11-02 06:23:02 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 19 = ∑19/20, waiting for 19 jobs
2025-11-02 06:31:00 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 19 = ∑19/20, new result: VAL_ACC: 69.750000
2025-11-02 06:31:15 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 18 = ∑18/20, waiting for 19 jobs, finished 1 job
2025-11-02 06:31:15 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 18 = ∑18/20, waiting for 18 jobs
2025-11-02 07:09:40 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 18 = ∑18/20, new result: VAL_ACC: 69.350000
2025-11-02 07:09:51 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 17 = ∑17/20, waiting for 18 jobs, finished 1 job
2025-11-02 07:09:51 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 17 = ∑17/20, waiting for 17 jobs
2025-11-02 07:17:57 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 17 = ∑17/20, new result: VAL_ACC: 68.710000
2025-11-02 07:18:09 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 16 = ∑16/20, waiting for 17 jobs, finished 1 job
2025-11-02 07:18:09 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 16 = ∑16/20, waiting for 16 jobs
2025-11-02 07:21:22 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 16 = ∑16/20, new result: VAL_ACC: 69.290000
2025-11-02 07:21:33 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 15 = ∑15/20, waiting for 16 jobs, finished 1 job
2025-11-02 07:21:33 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 15 = ∑15/20, waiting for 15 jobs
2025-11-02 07:41:29 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 15 = ∑15/20, new result: VAL_ACC: 69.180000
2025-11-02 07:41:41 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 14 = ∑14/20, waiting for 15 jobs, finished 1 job
2025-11-02 07:41:41 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 14 = ∑14/20, waiting for 14 jobs
2025-11-02 07:52:20 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 14 = ∑14/20, new result: VAL_ACC: 69.400000
2025-11-02 07:52:32 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 13 = ∑13/20, waiting for 14 jobs, finished 1 job
2025-11-02 07:52:32 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 13 = ∑13/20, waiting for 13 jobs
2025-11-02 07:53:55 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 13 = ∑13/20, new result: VAL_ACC: 69.910000
2025-11-02 07:54:06 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 12 = ∑12/20, waiting for 13 jobs, finished 1 job
2025-11-02 07:54:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 12 = ∑12/20, waiting for 12 jobs
2025-11-02 07:54:20 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 12 = ∑12/20, new result: VAL_ACC: 69.900000
2025-11-02 07:54:31 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 11 = ∑11/20, waiting for 12 jobs, finished 1 job
2025-11-02 07:54:31 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 11 = ∑11/20, waiting for 11 jobs
2025-11-02 07:54:33 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 11 = ∑11/20, new result: VAL_ACC: 70.420000
2025-11-02 07:54:45 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 10 = ∑10/20, waiting for 11 jobs, finished 1 job
2025-11-02 07:54:45 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 10 = ∑10/20, waiting for 10 jobs
2025-11-02 07:54:46 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 10 = ∑10/20, new result: VAL_ACC: 69.350000
2025-11-02 07:54:57 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 9 = ∑9/20, waiting for 10 jobs, finished 1 job
2025-11-02 07:54:57 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 9 = ∑9/20, waiting for 9 jobs
2025-11-02 07:55:09 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 9 = ∑9/20, new result: VAL_ACC: 69.070000
2025-11-02 07:55:20 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 8 = ∑8/20, waiting for 9 jobs, finished 1 job
2025-11-02 07:55:20 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 8 = ∑8/20, waiting for 8 jobs
2025-11-02 07:55:28 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 8 = ∑8/20, new result: VAL_ACC: 70.050000
2025-11-02 07:55:40 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 7 = ∑7/20, waiting for 8 jobs, finished 1 job
2025-11-02 07:55:40 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 7 = ∑7/20, waiting for 7 jobs
2025-11-02 07:56:04 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 7 = ∑7/20, new result: VAL_ACC: 70.310000
2025-11-02 07:56:15 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 6 = ∑6/20, waiting for 7 jobs, finished 1 job
2025-11-02 07:56:16 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 6 = ∑6/20, waiting for 6 jobs
2025-11-02 07:56:35 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 6 = ∑6/20, new result: VAL_ACC: 69.370000
2025-11-02 07:56:47 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 5 = ∑5/20, waiting for 6 jobs, finished 1 job
2025-11-02 07:56:47 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 5 = ∑5/20, waiting for 5 jobs
2025-11-02 07:58:57 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 5 = ∑5/20, new result: VAL_ACC: 69.790000
2025-11-02 07:59:08 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 4 = ∑4/20, waiting for 5 jobs, finished 1 job
2025-11-02 07:59:08 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 4 = ∑4/20, waiting for 4 jobs
2025-11-02 07:59:09 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 4 = ∑4/20, new result: VAL_ACC: 69.960000
2025-11-02 07:59:20 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 3 = ∑3/20, waiting for 4 jobs, finished 1 job
2025-11-02 07:59:20 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 3 = ∑3/20, waiting for 3 jobs
2025-11-02 08:06:48 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 3 = ∑3/20, new result: VAL_ACC: 70.200000
2025-11-02 08:07:00 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 2 = ∑2/20, waiting for 3 jobs, finished 1 job
2025-11-02 08:07:00 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 2 = ∑2/20, waiting for 2 jobs
2025-11-02 08:09:28 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 2 = ∑2/20, new result: VAL_ACC: 68.950000
2025-11-02 08:09:40 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 1 = ∑1/20, waiting for 2 jobs, finished 1 job
2025-11-02 08:09:40 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 1 = ∑1/20, waiting for 1 job
2025-11-02 08:13:13 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 1 = ∑1/20, new result: VAL_ACC: 70.830000
2025-11-02 08:13:25 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, waiting for 1 job, finished 1 job
2025-11-02 08:14:57 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #1/20
2025-11-02 08:14:57 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #2/20
2025-11-02 08:16:39 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, requested 20 jobs, got 1, 192.57 s/job
2025-11-02 08:16:40 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #1/1 start
2025-11-02 08:16:41 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, starting new job
2025-11-02 08:16:41 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, unknown 1 = ∑1/20, started new job
2025-11-02 08:16:43 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, unknown 1 = ∑1/20, waiting for 1 job
2025-11-02 08:16:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, pending 1 = ∑1/20, waiting for 1 job
2025-11-02 08:16:47 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 1 = ∑1/20, waiting for 1 job
2025-11-02 10:36:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 1 = ∑1/20, new result: VAL_ACC: 69.220000
2025-11-02 10:37:02 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, waiting for 1 job, finished 1 job
2025-11-02 10:39:14 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #1/20
2025-11-02 10:39:14 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #2/20
2025-11-02 10:39:14 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #3/20
2025-11-02 10:39:15 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #4/20
2025-11-02 10:39:15 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #5/20
2025-11-02 10:39:15 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #6/20
2025-11-02 10:39:16 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #7/20
2025-11-02 10:39:16 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #8/20
2025-11-02 10:39:17 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #9/20
2025-11-02 10:39:17 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #10/20
2025-11-02 10:39:17 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #11/20
2025-11-02 10:39:18 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #12/20
2025-11-02 10:39:18 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #13/20
2025-11-02 10:39:18 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #14/20
2025-11-02 10:39:19 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #15/20
2025-11-02 10:39:19 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #16/20
2025-11-02 10:39:19 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #17/20
2025-11-02 10:39:52 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #18/20
2025-11-02 10:39:52 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #19/20
2025-11-02 10:39:52 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #20/20
2025-11-02 10:39:53 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, requested 20 jobs, got 20, 8.50 s/job
2025-11-02 10:39:55 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #1/20 start
2025-11-02 10:39:56 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #2/20 start
2025-11-02 10:39:57 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #3/20 start
2025-11-02 10:39:58 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #4/20 start
2025-11-02 10:39:59 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #5/20 start
2025-11-02 10:40:01 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #6/20 start
2025-11-02 10:40:02 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #7/20 start
2025-11-02 10:40:03 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #8/20 start
2025-11-02 10:40:04 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #9/20 start
2025-11-02 10:40:05 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #10/20 start
2025-11-02 10:40:06 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #11/20 start
2025-11-02 10:40:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #12/20 start
2025-11-02 10:40:08 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #13/20 start
2025-11-02 10:40:09 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #14/20 start
2025-11-02 10:40:10 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #15/20 start
2025-11-02 10:40:11 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #16/20 start
2025-11-02 10:40:12 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #17/20 start
2025-11-02 10:40:13 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #18/20 start
2025-11-02 10:40:14 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #19/20 start
2025-11-02 10:40:15 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #20/20 start
2025-11-02 10:40:25 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, starting new job
2025-11-02 10:40:27 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, pending 1 = ∑1/20, started new job
2025-11-02 10:40:28 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, pending 1 = ∑1/20, starting new job
2025-11-02 10:40:31 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running/unknown 1/1 = ∑2/20, started new job
2025-11-02 10:40:32 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running/unknown 1/1 = ∑2/20, starting new job
2025-11-02 10:40:36 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running/pending/unknown 1/1/1 = ∑3/20, started new job
2025-11-02 10:40:37 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running/pending/unknown 1/1/1 = ∑3/20, starting new job
2025-11-02 10:40:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running/pending/unknown 1/3/2 = ∑6/20, started new job
2025-11-02 10:40:43 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running/pending/unknown 1/3/2 = ∑6/20, starting new job
2025-11-02 10:40:46 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running/unknown 6/1 = ∑7/20, started new job
2025-11-02 10:40:56 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running/unknown 7/1 = ∑8/20, started new job
2025-11-02 10:41:01 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running/pending/unknown 7/1/1 = ∑9/20, started new job
2025-11-02 10:41:11 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running/unknown 9/1 = ∑10/20, started new job
2025-11-02 10:41:18 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running/pending/unknown 9/1/3 = ∑13/20, started new job
2025-11-02 10:41:22 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running/unknown 13/2 = ∑15/20, started new job
2025-11-02 10:41:26 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running/unknown 15/1 = ∑16/20, started new job
2025-11-02 10:41:37 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running/pending/unknown 15/1/2 = ∑18/20, started new job
2025-11-02 10:41:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running/pending/unknown 15/3/2 = ∑20/20, started new job
2025-11-02 10:41:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running/pending 15/5 = ∑20/20, waiting for 20 jobs
2025-11-02 10:41:47 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 20 = ∑20/20, waiting for 20 jobs
2025-11-02 11:24:58 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 20 = ∑20/20, new result: VAL_ACC: 66.320000
2025-11-02 11:25:11 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 19 = ∑19/20, waiting for 20 jobs, finished 1 job
2025-11-02 11:25:12 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 19 = ∑19/20, waiting for 19 jobs
2025-11-02 11:36:09 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running/completed 18/1 = ∑19/20, new result: VAL_ACC: 65.630000
2025-11-02 11:36:26 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 18 = ∑18/20, waiting for 19 jobs, finished 1 job
2025-11-02 11:36:26 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 18 = ∑18/20, waiting for 18 jobs
2025-11-02 12:40:22 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 18 = ∑18/20, new result: VAL_ACC: 66.330000
2025-11-02 12:40:35 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 17 = ∑17/20, waiting for 18 jobs, finished 1 job
2025-11-02 12:40:35 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 17 = ∑17/20, waiting for 17 jobs
2025-11-02 12:46:24 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 17 = ∑17/20, new result: VAL_ACC: 70.010000
2025-11-02 12:46:37 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 16 = ∑16/20, waiting for 17 jobs, finished 1 job
2025-11-02 12:46:38 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 16 = ∑16/20, waiting for 16 jobs
2025-11-02 12:47:08 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 16 = ∑16/20, new result: VAL_ACC: 69.770000
2025-11-02 12:47:21 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 15 = ∑15/20, waiting for 16 jobs, finished 1 job
2025-11-02 12:47:22 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 15 = ∑15/20, waiting for 15 jobs
2025-11-02 12:47:33 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 15 = ∑15/20, new result: VAL_ACC: 69.460000
2025-11-02 12:47:46 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 14 = ∑14/20, waiting for 15 jobs, finished 1 job
2025-11-02 12:47:46 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 14 = ∑14/20, waiting for 14 jobs
2025-11-02 12:48:11 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 14 = ∑14/20, new result: VAL_ACC: 66.200000
2025-11-02 12:48:25 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 13 = ∑13/20, waiting for 14 jobs, finished 1 job
2025-11-02 12:48:25 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 13 = ∑13/20, waiting for 13 jobs
2025-11-02 12:49:12 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 13 = ∑13/20, new result: VAL_ACC: 63.890000
2025-11-02 12:49:26 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 12 = ∑12/20, waiting for 13 jobs, finished 1 job
2025-11-02 12:49:26 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 12 = ∑12/20, waiting for 12 jobs
2025-11-02 12:49:29 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 12 = ∑12/20, new result: VAL_ACC: 62.540000
2025-11-02 12:49:43 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 11 = ∑11/20, waiting for 12 jobs, finished 1 job
2025-11-02 12:49:43 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 11 = ∑11/20, waiting for 11 jobs
2025-11-02 12:49:45 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 11 = ∑11/20, new result: VAL_ACC: 64.720000
2025-11-02 12:49:58 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 10 = ∑10/20, waiting for 11 jobs, finished 1 job
2025-11-02 12:49:58 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 10 = ∑10/20, waiting for 10 jobs
2025-11-02 12:51:37 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 10 = ∑10/20, new result: VAL_ACC: 71.420000
2025-11-02 12:51:50 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 9 = ∑9/20, waiting for 10 jobs, finished 1 job
2025-11-02 12:51:50 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 9 = ∑9/20, waiting for 9 jobs
2025-11-02 12:52:10 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 9 = ∑9/20, new result: VAL_ACC: 70.870000
2025-11-02 12:52:23 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 8 = ∑8/20, waiting for 9 jobs, finished 1 job
2025-11-02 12:52:23 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 8 = ∑8/20, waiting for 8 jobs
2025-11-02 12:52:25 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 8 = ∑8/20, new result: VAL_ACC: 70.980000
2025-11-02 12:52:25 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 8 = ∑8/20, new result: VAL_ACC: 70.950000
2025-11-02 12:52:45 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 6 = ∑6/20, waiting for 8 jobs, finished 2 jobs
2025-11-02 12:52:46 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 6 = ∑6/20, waiting for 6 jobs
2025-11-02 12:52:47 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 6 = ∑6/20, new result: VAL_ACC: 70.800000
2025-11-02 12:53:00 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 5 = ∑5/20, waiting for 6 jobs, finished 1 job
2025-11-02 12:53:01 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 5 = ∑5/20, waiting for 5 jobs
2025-11-02 12:53:02 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 5 = ∑5/20, new result: VAL_ACC: 70.920000
2025-11-02 12:53:15 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 4 = ∑4/20, waiting for 5 jobs, finished 1 job
2025-11-02 12:53:16 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 4 = ∑4/20, waiting for 4 jobs
2025-11-02 12:53:50 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 4 = ∑4/20, new result: VAL_ACC: 71.160000
2025-11-02 12:54:04 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 3 = ∑3/20, waiting for 4 jobs, finished 1 job
2025-11-02 12:54:05 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 3 = ∑3/20, waiting for 3 jobs
2025-11-02 12:54:24 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 3 = ∑3/20, new result: VAL_ACC: 70.970000
2025-11-02 12:54:45 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 2 = ∑2/20, waiting for 3 jobs, finished 1 job
2025-11-02 12:54:45 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 2 = ∑2/20, waiting for 2 jobs
2025-11-02 13:03:58 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 2 = ∑2/20, new result: VAL_ACC: 71.250000
2025-11-02 13:04:11 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 1 = ∑1/20, waiting for 2 jobs, finished 1 job
2025-11-02 13:04:12 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 1 = ∑1/20, waiting for 1 job
2025-11-02 13:05:02 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 1 = ∑1/20, new result: VAL_ACC: 71.170000
2025-11-02 13:05:17 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, waiting for 1 job, finished 1 job
2025-11-02 13:07:36 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #1/20
2025-11-02 13:07:36 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #2/20
2025-11-02 13:07:37 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #3/20
2025-11-02 13:07:38 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #4/20
2025-11-02 13:07:39 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #5/20
2025-11-02 13:07:39 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #6/20
2025-11-02 13:07:40 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #7/20
2025-11-02 13:07:40 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #8/20
2025-11-02 13:07:40 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #9/20
2025-11-02 13:07:41 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #10/20
2025-11-02 13:07:41 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #11/20
2025-11-02 13:07:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #12/20
2025-11-02 13:07:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #13/20
2025-11-02 13:07:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #14/20
2025-11-02 13:07:43 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #15/20
2025-11-02 13:07:43 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #16/20
2025-11-02 13:07:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #17/20
2025-11-02 13:07:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #18/20
2025-11-02 13:07:45 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #19/20
2025-11-02 13:07:45 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, getting new HP set #20/20
2025-11-02 13:07:45 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, requested 20 jobs, got 20, 7.37 s/job
2025-11-02 13:07:48 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #1/20 start
2025-11-02 13:07:50 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #2/20 start
2025-11-02 13:07:51 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #3/20 start
2025-11-02 13:07:52 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #4/20 start
2025-11-02 13:07:55 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #5/20 start
2025-11-02 13:07:57 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #6/20 start
2025-11-02 13:07:58 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #7/20 start
2025-11-02 13:08:00 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #8/20 start
2025-11-02 13:08:02 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #9/20 start
2025-11-02 13:08:04 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #10/20 start
2025-11-02 13:08:05 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #11/20 start
2025-11-02 13:08:06 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #12/20 start
2025-11-02 13:08:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #13/20 start
2025-11-02 13:08:08 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #14/20 start
2025-11-02 13:08:10 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #15/20 start
2025-11-02 13:08:12 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #16/20 start
2025-11-02 13:08:13 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #17/20 start
2025-11-02 13:08:15 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #18/20 start
2025-11-02 13:08:16 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #19/20 start
2025-11-02 13:08:18 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, eval #20/20 start
2025-11-02 13:08:28 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, starting new job
2025-11-02 13:08:32 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, pending/unknown 2/1 = ∑3/20, started new job
2025-11-02 13:08:34 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 3 = ∑3/20, starting new job
2025-11-02 13:08:35 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running/unknown 3/1 = ∑4/20, started new job
2025-11-02 13:08:36 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running/unknown 3/1 = ∑4/20, starting new job
2025-11-02 13:08:46 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running/pending/unknown 3/1/2 = ∑6/20, started new job
2025-11-02 13:08:50 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running/unknown 6/1 = ∑7/20, started new job
2025-11-02 13:08:56 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running/unknown 7/2 = ∑9/20, started new job
2025-11-02 13:09:01 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running/pending/unknown 7/2/2 = ∑11/20, started new job
2025-11-02 13:09:06 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running/pending/unknown 7/4/2 = ∑13/20, started new job
2025-11-02 13:09:12 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running/pending/unknown 7/6/3 = ∑16/20, started new job
2025-11-02 13:09:16 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running/unknown 16/2 = ∑18/20, started new job
2025-11-02 13:09:21 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running/unknown 18/2 = ∑20/20, started new job
2025-11-02 13:09:23 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running/unknown 18/2 = ∑20/20, waiting for 20 jobs
2025-11-02 13:09:26 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running/pending 18/2 = ∑20/20, waiting for 20 jobs
2025-11-02 13:09:34 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 20 = ∑20/20, waiting for 20 jobs
2025-11-02 13:54:20 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 20 = ∑20/20, new result: VAL_ACC: 69.180000
2025-11-02 13:54:35 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 19 = ∑19/20, waiting for 20 jobs, finished 1 job
2025-11-02 13:54:35 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 19 = ∑19/20, waiting for 19 jobs
2025-11-02 13:59:18 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 19 = ∑19/20, new result: VAL_ACC: 69.980000
2025-11-02 13:59:34 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 18 = ∑18/20, waiting for 19 jobs, finished 1 job
2025-11-02 13:59:34 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 18 = ∑18/20, waiting for 18 jobs
2025-11-02 14:16:56 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 18 = ∑18/20, new result: VAL_ACC: 69.540000
2025-11-02 14:17:12 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 17 = ∑17/20, waiting for 18 jobs, finished 1 job
2025-11-02 14:17:12 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 17 = ∑17/20, waiting for 17 jobs
2025-11-02 14:38:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 17 = ∑17/20, new result: VAL_ACC: 69.830000
2025-11-02 14:38:58 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 16 = ∑16/20, waiting for 17 jobs, finished 1 job
2025-11-02 14:38:58 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 16 = ∑16/20, waiting for 16 jobs
2025-11-02 14:41:03 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 16 = ∑16/20, new result: VAL_ACC: 64.350000
2025-11-02 14:41:20 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 15 = ∑15/20, waiting for 16 jobs, finished 1 job
2025-11-02 14:41:20 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 15 = ∑15/20, waiting for 15 jobs
2025-11-02 14:41:23 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 15 = ∑15/20, new result: VAL_ACC: 64.580000
2025-11-02 14:41:47 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 14 = ∑14/20, waiting for 15 jobs, finished 1 job
2025-11-02 14:41:47 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 14 = ∑14/20, waiting for 14 jobs
2025-11-02 14:41:48 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 14 = ∑14/20, new result: VAL_ACC: 63.610000
2025-11-02 14:42:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 13 = ∑13/20, waiting for 14 jobs, finished 1 job
2025-11-02 14:42:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 13 = ∑13/20, waiting for 13 jobs
2025-11-02 14:42:11 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 13 = ∑13/20, new result: VAL_ACC: 63.940000
2025-11-02 14:42:11 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 13 = ∑13/20, new result: VAL_ACC: 64.210000
2025-11-02 14:42:46 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 11 = ∑11/20, waiting for 13 jobs, finished 2 jobs
2025-11-02 14:42:46 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 11 = ∑11/20, waiting for 11 jobs
2025-11-02 14:43:28 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 11 = ∑11/20, new result: VAL_ACC: 64.450000
2025-11-02 14:43:47 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 10 = ∑10/20, waiting for 11 jobs, finished 1 job
2025-11-02 14:43:48 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 10 = ∑10/20, waiting for 10 jobs
2025-11-02 14:45:12 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 10 = ∑10/20, new result: VAL_ACC: 64.570000
2025-11-02 14:45:30 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 9 = ∑9/20, waiting for 10 jobs, finished 1 job
2025-11-02 14:45:31 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 9 = ∑9/20, waiting for 9 jobs
2025-11-02 15:14:54 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 9 = ∑9/20, new result: VAL_ACC: 69.090000
2025-11-02 15:15:17 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 8 = ∑8/20, waiting for 9 jobs, finished 1 job
2025-11-02 15:15:18 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 8 = ∑8/20, waiting for 8 jobs
2025-11-02 15:18:34 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 8 = ∑8/20, new result: VAL_ACC: 69.310000
2025-11-02 15:19:00 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 7 = ∑7/20, waiting for 8 jobs, finished 1 job
2025-11-02 15:19:00 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 7 = ∑7/20, waiting for 7 jobs
2025-11-02 15:19:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 7 = ∑7/20, new result: VAL_ACC: 71.370000
2025-11-02 15:19:32 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 6 = ∑6/20, waiting for 7 jobs, finished 1 job
2025-11-02 15:19:32 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 6 = ∑6/20, waiting for 6 jobs
2025-11-02 15:19:33 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.48, running 6 = ∑6/20, new result: VAL_ACC: 71.490000
2025-11-02 15:19:53 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 5 = ∑5/20, waiting for 6 jobs, finished 1 job
2025-11-02 15:19:54 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 5 = ∑5/20, waiting for 5 jobs
2025-11-02 15:19:55 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 5 = ∑5/20, new result: VAL_ACC: 71.110000
2025-11-02 15:20:15 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 4 = ∑4/20, waiting for 5 jobs, finished 1 job
2025-11-02 15:20:15 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 4 = ∑4/20, waiting for 4 jobs
2025-11-02 15:20:35 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 4 = ∑4/20, new result: VAL_ACC: 70.910000
2025-11-02 15:20:53 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 3 = ∑3/20, waiting for 4 jobs, finished 1 job
2025-11-02 15:20:54 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 3 = ∑3/20, waiting for 3 jobs
2025-11-02 15:20:57 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 3 = ∑3/20, new result: VAL_ACC: 71.260000
2025-11-02 15:21:17 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 2 = ∑2/20, waiting for 3 jobs, finished 1 job
2025-11-02 15:21:17 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 2 = ∑2/20, waiting for 2 jobs
2025-11-02 15:22:21 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 2 = ∑2/20, new result: VAL_ACC: 69.960000
2025-11-02 15:22:45 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 1 = ∑1/20, waiting for 2 jobs, finished 1 job
2025-11-02 15:22:45 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 1 = ∑1/20, waiting for 1 job
2025-11-02 15:23:23 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 1 = ∑1/20, new result: VAL_ACC: 70.910000
2025-11-02 15:23:53 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, waiting for 1 job, finished 1 job
2025-11-02 15:25:43 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, getting new HP set #1/20
2025-11-02 15:25:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, getting new HP set #2/20
2025-11-02 15:25:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, getting new HP set #3/20
2025-11-02 15:25:45 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, getting new HP set #4/20
2025-11-02 15:25:45 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, getting new HP set #5/20
2025-11-02 15:25:46 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, getting new HP set #6/20
2025-11-02 15:25:46 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, getting new HP set #7/20
2025-11-02 15:25:46 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, getting new HP set #8/20
2025-11-02 15:25:47 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, getting new HP set #9/20
2025-11-02 15:25:47 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, getting new HP set #10/20
2025-11-02 15:25:48 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, getting new HP set #11/20
2025-11-02 15:25:48 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, getting new HP set #12/20
2025-11-02 15:25:49 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, getting new HP set #13/20
2025-11-02 15:25:49 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, getting new HP set #14/20
2025-11-02 15:25:49 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, getting new HP set #15/20
2025-11-02 15:25:50 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, getting new HP set #16/20
2025-11-02 15:25:50 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, getting new HP set #17/20
2025-11-02 15:25:51 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, getting new HP set #18/20
2025-11-02 15:25:51 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, getting new HP set #19/20
2025-11-02 15:25:52 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, getting new HP set #20/20
2025-11-02 15:25:52 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, requested 20 jobs, got 20, 5.89 s/job
2025-11-02 15:25:54 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, eval #1/20 start
2025-11-02 15:25:55 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, eval #2/20 start
2025-11-02 15:25:56 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, eval #3/20 start
2025-11-02 15:25:58 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, eval #4/20 start
2025-11-02 15:25:59 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, eval #5/20 start
2025-11-02 15:26:00 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, eval #6/20 start
2025-11-02 15:26:01 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, eval #7/20 start
2025-11-02 15:26:04 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, eval #8/20 start
2025-11-02 15:26:05 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, eval #9/20 start
2025-11-02 15:26:06 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, eval #10/20 start
2025-11-02 15:26:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, eval #11/20 start
2025-11-02 15:26:09 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, eval #12/20 start
2025-11-02 15:26:10 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, eval #13/20 start
2025-11-02 15:26:11 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, eval #14/20 start
2025-11-02 15:26:12 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, eval #15/20 start
2025-11-02 15:26:15 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, eval #16/20 start
2025-11-02 15:26:16 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, eval #17/20 start
2025-11-02 15:26:17 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, eval #18/20 start
2025-11-02 15:26:18 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, eval #19/20 start
2025-11-02 15:26:21 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, eval #20/20 start
2025-11-02 15:26:32 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, starting new job
2025-11-02 15:26:36 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, pending 3 = ∑3/20, started new job
2025-11-02 15:26:38 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 3 = ∑3/20, starting new job
2025-11-02 15:26:40 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running/unknown 3/2 = ∑5/20, started new job
2025-11-02 15:26:41 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running/unknown 3/2 = ∑5/20, starting new job
2025-11-02 15:26:45 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running/pending/unknown 3/2/2 = ∑7/20, started new job
2025-11-02 15:26:49 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running/unknown 7/1 = ∑8/20, started new job
2025-11-02 15:26:54 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running/pending 8/1 = ∑9/20, started new job
2025-11-02 15:26:59 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running/unknown 9/1 = ∑10/20, started new job
2025-11-02 15:27:04 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running/pending/unknown 9/1/1 = ∑11/20, started new job
2025-11-02 15:27:05 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running/pending/unknown 9/1/2 = ∑12/20, started new job
2025-11-02 15:27:11 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running/pending/unknown 9/3/3 = ∑15/20, started new job
2025-11-02 15:27:16 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running/pending 15/3 = ∑18/20, started new job
2025-11-02 15:27:20 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running/unknown 18/2 = ∑20/20, started new job
2025-11-02 15:27:22 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running/pending 18/2 = ∑20/20, waiting for 20 jobs
2025-11-02 15:27:48 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 20 = ∑20/20, waiting for 20 jobs
2025-11-02 15:39:34 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 20 = ∑20/20, new result: VAL_ACC: 65.810000
2025-11-02 15:40:00 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 19 = ∑19/20, waiting for 20 jobs, finished 1 job
2025-11-02 15:40:00 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 19 = ∑19/20, waiting for 19 jobs
2025-11-02 16:02:17 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 19 = ∑19/20, new result: VAL_ACC: 67.140000
2025-11-02 16:02:34 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 18 = ∑18/20, waiting for 19 jobs, finished 1 job
2025-11-02 16:02:34 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 18 = ∑18/20, waiting for 18 jobs
2025-11-02 16:21:01 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 18 = ∑18/20, new result: VAL_ACC: 67.780000
2025-11-02 16:21:20 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 17 = ∑17/20, waiting for 18 jobs, finished 1 job
2025-11-02 16:21:20 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 17 = ∑17/20, waiting for 17 jobs
2025-11-02 16:31:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 17 = ∑17/20, new result: VAL_ACC: 67.000000
2025-11-02 16:32:01 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 16 = ∑16/20, waiting for 17 jobs, finished 1 job
2025-11-02 16:32:01 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 16 = ∑16/20, waiting for 16 jobs
2025-11-02 16:45:38 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 16 = ∑16/20, new result: VAL_ACC: 67.510000
2025-11-02 16:45:57 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 15 = ∑15/20, waiting for 16 jobs, finished 1 job
2025-11-02 16:45:57 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 15 = ∑15/20, waiting for 15 jobs
2025-11-02 16:52:57 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 15 = ∑15/20, new result: VAL_ACC: 67.310000
2025-11-02 16:53:16 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 14 = ∑14/20, waiting for 15 jobs, finished 1 job
2025-11-02 16:53:17 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 14 = ∑14/20, waiting for 14 jobs
2025-11-02 16:56:47 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 14 = ∑14/20, new result: VAL_ACC: 68.500000
2025-11-02 16:57:05 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 13 = ∑13/20, waiting for 14 jobs, finished 1 job
2025-11-02 16:57:06 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 13 = ∑13/20, waiting for 13 jobs
2025-11-02 17:03:54 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 13 = ∑13/20, new result: VAL_ACC: 67.300000
2025-11-02 17:04:11 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 12 = ∑12/20, waiting for 13 jobs, finished 1 job
2025-11-02 17:04:11 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 12 = ∑12/20, waiting for 12 jobs
2025-11-02 17:15:34 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 12 = ∑12/20, new result: VAL_ACC: 67.890000
2025-11-02 17:15:52 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 11 = ∑11/20, waiting for 12 jobs, finished 1 job
2025-11-02 17:15:53 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 11 = ∑11/20, waiting for 11 jobs
2025-11-02 17:20:12 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 11 = ∑11/20, new result: VAL_ACC: 68.020000
2025-11-02 17:20:34 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 10 = ∑10/20, waiting for 11 jobs, finished 1 job
2025-11-02 17:20:35 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 10 = ∑10/20, waiting for 10 jobs
2025-11-02 17:20:36 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 10 = ∑10/20, new result: VAL_ACC: 68.390000
2025-11-02 17:20:55 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 9 = ∑9/20, waiting for 10 jobs, finished 1 job
2025-11-02 17:20:55 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 9 = ∑9/20, waiting for 9 jobs
2025-11-02 17:23:27 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 9 = ∑9/20, new result: VAL_ACC: 68.410000
2025-11-02 17:23:46 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 8 = ∑8/20, waiting for 9 jobs, finished 1 job
2025-11-02 17:23:47 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 8 = ∑8/20, waiting for 8 jobs
2025-11-02 17:27:22 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 8 = ∑8/20, new result: VAL_ACC: 67.740000
2025-11-02 17:27:41 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 7 = ∑7/20, waiting for 8 jobs, finished 1 job
2025-11-02 17:27:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 7 = ∑7/20, waiting for 7 jobs
2025-11-02 17:31:01 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 7 = ∑7/20, new result: VAL_ACC: 67.530000
2025-11-02 17:31:18 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 6 = ∑6/20, waiting for 7 jobs, finished 1 job
2025-11-02 17:31:18 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 6 = ∑6/20, waiting for 6 jobs
2025-11-02 17:31:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 6 = ∑6/20, new result: VAL_ACC: 68.040000
2025-11-02 17:32:06 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 5 = ∑5/20, waiting for 6 jobs, finished 1 job
2025-11-02 17:32:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 5 = ∑5/20, waiting for 5 jobs
2025-11-02 17:38:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 5 = ∑5/20, new result: VAL_ACC: 67.840000
2025-11-02 17:39:01 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 4 = ∑4/20, waiting for 5 jobs, finished 1 job
2025-11-02 17:39:01 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 4 = ∑4/20, waiting for 4 jobs
2025-11-02 17:39:14 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 4 = ∑4/20, new result: VAL_ACC: 67.840000
2025-11-02 17:39:32 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 3 = ∑3/20, waiting for 4 jobs, finished 1 job
2025-11-02 17:39:32 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 3 = ∑3/20, waiting for 3 jobs
2025-11-02 17:39:34 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 3 = ∑3/20, new result: VAL_ACC: 67.220000
2025-11-02 17:39:51 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 2 = ∑2/20, waiting for 3 jobs, finished 1 job
2025-11-02 17:39:52 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 2 = ∑2/20, waiting for 2 jobs
2025-11-02 17:40:38 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 2 = ∑2/20, new result: VAL_ACC: 67.260000
2025-11-02 17:40:56 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 1 = ∑1/20, waiting for 2 jobs, finished 1 job
2025-11-02 17:40:57 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 1 = ∑1/20, waiting for 1 job
2025-11-02 17:42:24 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 1 = ∑1/20, new result: VAL_ACC: 67.310000
2025-11-02 17:42:43 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, waiting for 1 job, finished 1 job
2025-11-02 17:44:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, getting new HP set #1/20
2025-11-02 17:44:45 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, getting new HP set #2/20
2025-11-02 17:44:45 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, getting new HP set #3/20
2025-11-02 17:44:46 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, getting new HP set #4/20
2025-11-02 17:44:46 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, getting new HP set #5/20
2025-11-02 17:44:47 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, getting new HP set #6/20
2025-11-02 17:44:47 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, getting new HP set #7/20
2025-11-02 17:44:48 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, getting new HP set #8/20
2025-11-02 17:44:48 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, getting new HP set #9/20
2025-11-02 17:44:49 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, getting new HP set #10/20
2025-11-02 17:44:50 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, getting new HP set #11/20
2025-11-02 17:44:51 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, getting new HP set #12/20
2025-11-02 17:44:51 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, getting new HP set #13/20
2025-11-02 17:44:52 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, getting new HP set #14/20
2025-11-02 17:44:52 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, getting new HP set #15/20
2025-11-02 17:44:52 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, getting new HP set #16/20
2025-11-02 17:44:53 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, getting new HP set #17/20
2025-11-02 17:44:53 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, getting new HP set #18/20
2025-11-02 17:44:54 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, getting new HP set #19/20
2025-11-02 17:44:54 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, getting new HP set #20/20
2025-11-02 17:44:55 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, requested 20 jobs, got 20, 6.45 s/job
2025-11-02 17:44:58 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, eval #1/20 start
2025-11-02 17:45:00 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, eval #2/20 start
2025-11-02 17:45:01 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, eval #3/20 start
2025-11-02 17:45:05 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, eval #4/20 start
2025-11-02 17:45:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, eval #5/20 start
2025-11-02 17:45:09 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, eval #6/20 start
2025-11-02 17:45:10 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, eval #7/20 start
2025-11-02 17:45:13 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, eval #8/20 start
2025-11-02 17:45:14 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, eval #9/20 start
2025-11-02 17:45:15 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, eval #10/20 start
2025-11-02 17:45:17 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, eval #11/20 start
2025-11-02 17:45:18 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, eval #12/20 start
2025-11-02 17:45:19 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, eval #13/20 start
2025-11-02 17:45:28 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, eval #14/20 start
2025-11-02 17:45:29 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, eval #15/20 start
2025-11-02 17:45:31 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, eval #16/20 start
2025-11-02 17:45:32 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, eval #17/20 start
2025-11-02 17:45:34 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, eval #18/20 start
2025-11-02 17:45:36 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, eval #19/20 start
2025-11-02 17:45:38 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, eval #20/20 start
2025-11-02 17:45:50 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, starting new job
2025-11-02 17:45:55 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 3 = ∑3/20, started new job
2025-11-02 17:45:58 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 3 = ∑3/20, starting new job
2025-11-02 17:45:59 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running/unknown 3/2 = ∑5/20, starting new job
2025-11-02 17:45:59 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running/unknown 3/2 = ∑5/20, started new job
2025-11-02 17:46:00 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running/unknown 3/2 = ∑5/20, starting new job
2025-11-02 17:46:03 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running/pending/unknown 3/2/2 = ∑7/20, started new job
2025-11-02 17:46:08 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running/pending/unknown 3/4/2 = ∑9/20, started new job
2025-11-02 17:46:14 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running/pending 9/3 = ∑12/20, started new job
2025-11-02 17:46:17 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running/pending 12/1 = ∑13/20, started new job
2025-11-02 17:46:24 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running/unknown 13/3 = ∑16/20, started new job
2025-11-02 17:46:28 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running/pending/unknown 13/3/2 = ∑18/20, started new job
2025-11-02 17:46:33 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running/pending 18/2 = ∑20/20, started new job
2025-11-02 17:46:35 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 20 = ∑20/20, waiting for 20 jobs
2025-11-02 18:11:23 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 20 = ∑20/20, new result: VAL_ACC: 63.130000
2025-11-02 18:11:54 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 19 = ∑19/20, waiting for 20 jobs, finished 1 job
2025-11-02 18:11:54 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 19 = ∑19/20, waiting for 19 jobs
2025-11-02 18:39:18 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 19 = ∑19/20, new result: VAL_ACC: 71.080000
2025-11-02 18:39:39 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 18 = ∑18/20, waiting for 19 jobs, finished 1 job
2025-11-02 18:39:39 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 18 = ∑18/20, waiting for 18 jobs
2025-11-02 18:49:26 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 18 = ∑18/20, new result: VAL_ACC: 70.830000
2025-11-02 18:49:46 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 17 = ∑17/20, waiting for 18 jobs, finished 1 job
2025-11-02 18:49:47 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 17 = ∑17/20, waiting for 17 jobs
2025-11-02 18:50:18 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 17 = ∑17/20, new result: VAL_ACC: 70.970000
2025-11-02 18:50:37 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 16 = ∑16/20, waiting for 17 jobs, finished 1 job
2025-11-02 18:50:37 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 16 = ∑16/20, waiting for 16 jobs
2025-11-02 19:14:53 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 16 = ∑16/20, new result: VAL_ACC: 61.470000
2025-11-02 19:15:14 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 15 = ∑15/20, waiting for 16 jobs, finished 1 job
2025-11-02 19:15:15 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 15 = ∑15/20, waiting for 15 jobs
2025-11-02 19:15:16 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 15 = ∑15/20, new result: VAL_ACC: 60.570000
2025-11-02 19:15:38 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 14 = ∑14/20, waiting for 15 jobs, finished 1 job
2025-11-02 19:15:38 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 14 = ∑14/20, waiting for 14 jobs
2025-11-02 19:15:40 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 14 = ∑14/20, new result: VAL_ACC: 63.470000
2025-11-02 19:15:41 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 14 = ∑14/20, new result: VAL_ACC: 62.040000
2025-11-02 19:16:10 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 12 = ∑12/20, waiting for 14 jobs, finished 2 jobs
2025-11-02 19:16:11 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 12 = ∑12/20, waiting for 12 jobs
2025-11-02 19:16:38 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 12 = ∑12/20, new result: VAL_ACC: 61.500000
2025-11-02 19:17:03 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 11 = ∑11/20, waiting for 12 jobs, finished 1 job
2025-11-02 19:17:04 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 11 = ∑11/20, waiting for 11 jobs
2025-11-02 19:17:05 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 11 = ∑11/20, new result: VAL_ACC: 62.380000
2025-11-02 19:17:27 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 10 = ∑10/20, waiting for 11 jobs, finished 1 job
2025-11-02 19:17:27 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 10 = ∑10/20, waiting for 10 jobs
2025-11-02 19:17:32 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 10 = ∑10/20, new result: VAL_ACC: 71.340000
2025-11-02 19:17:54 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 9 = ∑9/20, waiting for 10 jobs, finished 1 job
2025-11-02 19:17:54 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 9 = ∑9/20, waiting for 9 jobs
2025-11-02 19:20:11 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 9 = ∑9/20, new result: VAL_ACC: 70.570000
2025-11-02 19:20:30 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 8 = ∑8/20, waiting for 9 jobs, finished 1 job
2025-11-02 19:20:30 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 8 = ∑8/20, waiting for 8 jobs
2025-11-02 19:55:10 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 8 = ∑8/20, new result: VAL_ACC: 70.850000
2025-11-02 19:55:31 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 7 = ∑7/20, waiting for 8 jobs, finished 1 job
2025-11-02 19:55:32 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 7 = ∑7/20, waiting for 7 jobs
2025-11-02 19:55:37 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 7 = ∑7/20, new result: VAL_ACC: 71.120000
2025-11-02 19:55:57 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 6 = ∑6/20, waiting for 7 jobs, finished 1 job
2025-11-02 19:55:57 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 6 = ∑6/20, waiting for 6 jobs
2025-11-02 19:55:59 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 6 = ∑6/20, new result: VAL_ACC: 70.820000
2025-11-02 19:56:19 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 5 = ∑5/20, waiting for 6 jobs, finished 1 job
2025-11-02 19:56:19 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 5 = ∑5/20, waiting for 5 jobs
2025-11-02 19:56:58 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 5 = ∑5/20, new result: VAL_ACC: 70.790000
2025-11-02 19:57:19 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 4 = ∑4/20, waiting for 5 jobs, finished 1 job
2025-11-02 19:57:19 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 4 = ∑4/20, waiting for 4 jobs
2025-11-02 19:57:21 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 4 = ∑4/20, new result: VAL_ACC: 71.150000
2025-11-02 19:57:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 3 = ∑3/20, waiting for 4 jobs, finished 1 job
2025-11-02 19:57:43 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 3 = ∑3/20, waiting for 3 jobs
2025-11-02 19:57:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 3 = ∑3/20, new result: VAL_ACC: 70.660000
2025-11-02 19:58:06 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 2 = ∑2/20, waiting for 3 jobs, finished 1 job
2025-11-02 19:58:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 2 = ∑2/20, waiting for 2 jobs
2025-11-02 19:58:08 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 2 = ∑2/20, new result: VAL_ACC: 71.210000
2025-11-02 19:58:29 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 1 = ∑1/20, waiting for 2 jobs, finished 1 job
2025-11-02 19:58:30 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, running 1 = ∑1/20, waiting for 1 job
2025-11-02 21:54:20 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, best VAL_ACC: 71.49, timeout 1 = ∑1/20, job_failed
2025-11-02 21:54:23 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, waiting for 1 job, finished 1 job
2025-11-02 21:56:29 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #1/20
2025-11-02 21:56:30 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #2/20
2025-11-02 21:56:30 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #3/20
2025-11-02 21:56:31 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #4/20
2025-11-02 21:56:31 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #5/20
2025-11-02 21:56:32 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #6/20
2025-11-02 21:56:32 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #7/20
2025-11-02 21:56:33 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #8/20
2025-11-02 21:56:34 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #9/20
2025-11-02 21:56:34 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #10/20
2025-11-02 21:56:35 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #11/20
2025-11-02 21:56:35 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #12/20
2025-11-02 21:56:36 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #13/20
2025-11-02 21:56:36 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #14/20
2025-11-02 21:56:37 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #15/20
2025-11-02 21:56:37 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #16/20
2025-11-02 21:56:38 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #17/20
2025-11-02 21:56:38 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #18/20
2025-11-02 21:56:39 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #19/20
2025-11-02 21:56:39 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #20/20
2025-11-02 21:56:40 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, requested 20 jobs, got 20, 6.74 s/job
2025-11-02 21:56:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #1/20 start
2025-11-02 21:56:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #2/20 start
2025-11-02 21:56:45 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #3/20 start
2025-11-02 21:56:47 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #4/20 start
2025-11-02 21:56:48 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #5/20 start
2025-11-02 21:56:50 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #6/20 start
2025-11-02 21:56:51 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #7/20 start
2025-11-02 21:56:53 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #8/20 start
2025-11-02 21:56:54 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #9/20 start
2025-11-02 21:56:56 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #10/20 start
2025-11-02 21:56:57 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #11/20 start
2025-11-02 21:56:59 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #12/20 start
2025-11-02 21:57:00 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #13/20 start
2025-11-02 21:57:02 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #14/20 start
2025-11-02 21:57:03 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #15/20 start
2025-11-02 21:57:05 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #16/20 start
2025-11-02 21:57:06 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #17/20 start
2025-11-02 21:57:08 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #18/20 start
2025-11-02 21:57:11 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #19/20 start
2025-11-02 21:57:12 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #20/20 start
2025-11-02 21:57:26 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, starting new job
2025-11-02 21:57:30 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, unknown 2 = ∑2/20, started new job
2025-11-02 21:57:32 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, pending 2 = ∑2/20, starting new job
2025-11-02 21:57:34 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, pending/unknown 2/1 = ∑3/20, started new job
2025-11-02 21:57:35 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, pending/unknown 2/1 = ∑3/20, starting new job
2025-11-02 21:57:40 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/unknown 3/2 = ∑5/20, started new job
2025-11-02 21:57:40 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/unknown 3/2 = ∑5/20, starting new job
2025-11-02 21:57:45 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/unknown 5/2 = ∑7/20, started new job
2025-11-02 21:57:49 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/pending/unknown 5/2/1 = ∑8/20, started new job
2025-11-02 21:57:55 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/pending/unknown 5/3/2 = ∑10/20, started new job
2025-11-02 21:58:00 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/pending/unknown 5/5/3 = ∑13/20, started new job
2025-11-02 21:58:05 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/unknown 13/1 = ∑14/20, started new job
2025-11-02 21:58:10 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/unknown 14/2 = ∑16/20, started new job
2025-11-02 21:58:14 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/pending/unknown 14/2/1 = ∑17/20, started new job
2025-11-02 21:58:20 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/pending/unknown 14/3/2 = ∑19/20, started new job
2025-11-02 21:58:24 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/unknown 19/1 = ∑20/20, started new job
2025-11-02 21:58:26 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/unknown 19/1 = ∑20/20, waiting for 20 jobs
2025-11-02 21:58:30 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/pending 19/1 = ∑20/20, waiting for 20 jobs
2025-11-02 21:58:37 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 20 = ∑20/20, waiting for 20 jobs
2025-11-02 22:01:51 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 20 = ∑20/20, new result: VAL_ACC: 52.050000
2025-11-02 22:02:28 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/completed 15/4 = ∑19/20, waiting for 20 jobs, finished 1 job
2025-11-02 22:02:29 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/completed 15/4 = ∑19/20, waiting for 19 jobs
2025-11-02 22:02:33 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/completed 15/4 = ∑19/20, new result: VAL_ACC: 53.850000
2025-11-02 22:02:33 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/completed 15/4 = ∑19/20, new result: VAL_ACC: 50.090000
2025-11-02 22:02:33 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/completed 15/4 = ∑19/20, new result: VAL_ACC: 51.030000
2025-11-02 22:02:34 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/completed 15/4 = ∑19/20, new result: VAL_ACC: 51.750000
2025-11-02 22:03:38 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 15 = ∑15/20, waiting for 19 jobs, finished 4 jobs
2025-11-02 22:03:38 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 15 = ∑15/20, waiting for 15 jobs
2025-11-02 23:30:00 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 15 = ∑15/20, new result: VAL_ACC: 59.790000
2025-11-02 23:30:27 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 14 = ∑14/20, waiting for 15 jobs, finished 1 job
2025-11-02 23:30:28 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 14 = ∑14/20, waiting for 14 jobs
2025-11-02 23:30:29 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 14 = ∑14/20, new result: VAL_ACC: 60.240000
2025-11-02 23:30:50 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 13 = ∑13/20, waiting for 14 jobs, finished 1 job
2025-11-02 23:30:51 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 13 = ∑13/20, waiting for 13 jobs
2025-11-02 23:30:52 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 13 = ∑13/20, new result: VAL_ACC: 59.710000
2025-11-02 23:31:14 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 12 = ∑12/20, waiting for 13 jobs, finished 1 job
2025-11-02 23:31:15 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 12 = ∑12/20, waiting for 12 jobs
2025-11-02 23:53:37 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 12 = ∑12/20, new result: VAL_ACC: 66.130000
2025-11-02 23:54:01 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 11 = ∑11/20, waiting for 12 jobs, finished 1 job
2025-11-02 23:54:01 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 11 = ∑11/20, waiting for 11 jobs
2025-11-03 00:00:35 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 11 = ∑11/20, new result: VAL_ACC: 68.760000
2025-11-03 00:00:57 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 10 = ∑10/20, waiting for 11 jobs, finished 1 job
2025-11-03 00:00:57 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 10 = ∑10/20, waiting for 10 jobs
2025-11-03 00:00:59 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 10 = ∑10/20, new result: VAL_ACC: 67.290000
2025-11-03 00:01:20 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 9 = ∑9/20, waiting for 10 jobs, finished 1 job
2025-11-03 00:01:21 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 9 = ∑9/20, waiting for 9 jobs
2025-11-03 00:03:58 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 9 = ∑9/20, new result: VAL_ACC: 66.780000
2025-11-03 00:04:22 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 8 = ∑8/20, waiting for 9 jobs, finished 1 job
2025-11-03 00:04:22 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 8 = ∑8/20, waiting for 8 jobs
2025-11-03 00:04:26 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 8 = ∑8/20, new result: VAL_ACC: 68.060000
2025-11-03 00:04:52 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, completed/running 1/6 = ∑7/20, waiting for 8 jobs, finished 1 job
2025-11-03 00:04:53 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, completed/running 1/6 = ∑7/20, waiting for 7 jobs
2025-11-03 00:04:54 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, completed/running 1/6 = ∑7/20, new result: VAL_ACC: 67.520000
2025-11-03 00:05:20 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 6 = ∑6/20, waiting for 7 jobs, finished 1 job
2025-11-03 00:05:21 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 6 = ∑6/20, waiting for 6 jobs
2025-11-03 00:05:30 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 6 = ∑6/20, new result: VAL_ACC: 66.720000
2025-11-03 00:05:53 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 5 = ∑5/20, waiting for 6 jobs, finished 1 job
2025-11-03 00:05:54 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 5 = ∑5/20, waiting for 5 jobs
2025-11-03 00:06:13 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 5 = ∑5/20, new result: VAL_ACC: 67.500000
2025-11-03 00:06:39 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 4 = ∑4/20, waiting for 5 jobs, finished 1 job
2025-11-03 00:06:39 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 4 = ∑4/20, waiting for 4 jobs
2025-11-03 00:06:41 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 4 = ∑4/20, new result: VAL_ACC: 66.940000
2025-11-03 00:07:04 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 3 = ∑3/20, waiting for 4 jobs, finished 1 job
2025-11-03 00:07:05 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 3 = ∑3/20, waiting for 3 jobs
2025-11-03 00:09:12 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 3 = ∑3/20, new result: VAL_ACC: 69.980000
2025-11-03 00:09:34 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 2 = ∑2/20, waiting for 3 jobs, finished 1 job
2025-11-03 00:09:34 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 2 = ∑2/20, waiting for 2 jobs
2025-11-03 00:09:36 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 2 = ∑2/20, new result: VAL_ACC: 70.270000
2025-11-03 00:09:58 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 1 = ∑1/20, waiting for 2 jobs, finished 1 job
2025-11-03 00:09:58 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 1 = ∑1/20, waiting for 1 job
2025-11-03 00:11:53 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 1 = ∑1/20, new result: VAL_ACC: 70.740000
2025-11-03 00:12:17 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, waiting for 1 job, finished 1 job
2025-11-03 00:14:32 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #1/20
2025-11-03 00:14:33 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #2/20
2025-11-03 00:14:33 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #3/20
2025-11-03 00:14:34 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #4/20
2025-11-03 00:14:35 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #5/20
2025-11-03 00:14:35 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #6/20
2025-11-03 00:14:36 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #7/20
2025-11-03 00:14:36 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #8/20
2025-11-03 00:14:37 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #9/20
2025-11-03 00:14:37 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #10/20
2025-11-03 00:14:39 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #11/20
2025-11-03 00:14:40 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #12/20
2025-11-03 00:14:40 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #13/20
2025-11-03 00:14:41 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #14/20
2025-11-03 00:14:41 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #15/20
2025-11-03 00:14:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #16/20
2025-11-03 00:14:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #17/20
2025-11-03 00:14:43 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #18/20
2025-11-03 00:14:43 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #19/20
2025-11-03 00:14:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #20/20
2025-11-03 00:14:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, requested 20 jobs, got 20, 7.26 s/job
2025-11-03 00:14:48 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #1/20 start
2025-11-03 00:14:50 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #2/20 start
2025-11-03 00:14:51 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #3/20 start
2025-11-03 00:14:54 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #4/20 start
2025-11-03 00:14:56 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #5/20 start
2025-11-03 00:14:59 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #6/20 start
2025-11-03 00:15:01 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #7/20 start
2025-11-03 00:15:02 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #8/20 start
2025-11-03 00:15:04 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #9/20 start
2025-11-03 00:15:06 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #10/20 start
2025-11-03 00:15:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #11/20 start
2025-11-03 00:15:09 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #12/20 start
2025-11-03 00:15:10 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #13/20 start
2025-11-03 00:15:14 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #14/20 start
2025-11-03 00:15:16 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #15/20 start
2025-11-03 00:15:18 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #16/20 start
2025-11-03 00:15:19 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #17/20 start
2025-11-03 00:15:21 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #18/20 start
2025-11-03 00:15:23 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #19/20 start
2025-11-03 00:15:24 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #20/20 start
2025-11-03 00:15:39 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, starting new job
2025-11-03 00:15:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 3 = ∑3/20, started new job
2025-11-03 00:15:48 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 4 = ∑4/20, starting new job
2025-11-03 00:15:48 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 5 = ∑5/20, starting new job
2025-11-03 00:15:49 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 5 = ∑5/20, started new job
2025-11-03 00:15:50 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 5 = ∑5/20, starting new job
2025-11-03 00:15:52 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/unknown 5/1 = ∑6/20, started new job
2025-11-03 00:15:53 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/unknown 5/2 = ∑7/20, started new job
2025-11-03 00:15:57 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/pending/unknown 5/2/2 = ∑9/20, started new job
2025-11-03 00:16:03 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 12 = ∑12/20, started new job
2025-11-03 00:16:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/unknown 12/2 = ∑14/20, started new job
2025-11-03 00:16:12 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/pending/unknown 12/2/2 = ∑16/20, started new job
2025-11-03 00:16:18 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 19 = ∑19/20, started new job
2025-11-03 00:16:22 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/pending 19/1 = ∑20/20, started new job
2025-11-03 00:16:24 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 20 = ∑20/20, waiting for 20 jobs
2025-11-03 00:21:13 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 20 = ∑20/20, new result: VAL_ACC: 61.100000
2025-11-03 00:21:13 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 20 = ∑20/20, new result: VAL_ACC: 62.250000
2025-11-03 00:21:13 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 20 = ∑20/20, new result: VAL_ACC: 62.740000
2025-11-03 00:22:04 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 17 = ∑17/20, waiting for 20 jobs, finished 3 jobs
2025-11-03 00:22:04 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 17 = ∑17/20, waiting for 17 jobs
2025-11-03 00:22:14 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 17 = ∑17/20, new result: VAL_ACC: 61.580000
2025-11-03 00:22:14 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 17 = ∑17/20, new result: VAL_ACC: 62.260000
2025-11-03 00:22:14 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 17 = ∑17/20, new result: VAL_ACC: 61.890000
2025-11-03 00:22:15 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 17 = ∑17/20, new result: VAL_ACC: 59.150000
2025-11-03 00:22:15 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 17 = ∑17/20, new result: VAL_ACC: 57.880000
2025-11-03 00:22:15 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 17 = ∑17/20, new result: VAL_ACC: 61.960000
2025-11-03 00:22:16 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 17 = ∑17/20, new result: VAL_ACC: 61.910000
2025-11-03 00:22:16 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 17 = ∑17/20, new result: VAL_ACC: 61.840000
2025-11-03 00:22:17 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 17 = ∑17/20, new result: VAL_ACC: 61.810000
2025-11-03 00:22:17 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 17 = ∑17/20, new result: VAL_ACC: 59.480000
2025-11-03 00:25:51 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 7 = ∑7/20, waiting for 17 jobs, finished 10 jobs
2025-11-03 00:25:52 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 7 = ∑7/20, waiting for 7 jobs
2025-11-03 00:30:12 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 7 = ∑7/20, new result: VAL_ACC: 69.730000
2025-11-03 00:30:57 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 6 = ∑6/20, waiting for 7 jobs, finished 1 job
2025-11-03 00:30:58 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 6 = ∑6/20, waiting for 6 jobs
2025-11-03 00:35:04 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 6 = ∑6/20, new result: VAL_ACC: 67.950000
2025-11-03 00:35:32 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 5 = ∑5/20, waiting for 6 jobs, finished 1 job
2025-11-03 00:35:32 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 5 = ∑5/20, waiting for 5 jobs
2025-11-03 00:52:40 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 5 = ∑5/20, new result: VAL_ACC: 69.990000
2025-11-03 00:53:06 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 4 = ∑4/20, waiting for 5 jobs, finished 1 job
2025-11-03 00:53:06 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 4 = ∑4/20, waiting for 4 jobs
2025-11-03 00:53:08 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 4 = ∑4/20, new result: VAL_ACC: 70.600000
2025-11-03 00:53:34 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 3 = ∑3/20, waiting for 4 jobs, finished 1 job
2025-11-03 00:53:34 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 3 = ∑3/20, waiting for 3 jobs
2025-11-03 00:57:26 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 3 = ∑3/20, new result: VAL_ACC: 70.360000
2025-11-03 00:57:52 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 2 = ∑2/20, waiting for 3 jobs, finished 1 job
2025-11-03 00:57:52 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 2 = ∑2/20, waiting for 2 jobs
2025-11-03 01:31:19 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 2 = ∑2/20, new result: VAL_ACC: 70.340000
2025-11-03 01:31:49 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 1 = ∑1/20, waiting for 2 jobs, finished 1 job
2025-11-03 01:31:49 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 1 = ∑1/20, waiting for 1 job
2025-11-03 02:24:15 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 1 = ∑1/20, new result: VAL_ACC: 68.140000
2025-11-03 02:24:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, waiting for 1 job, finished 1 job
2025-11-03 02:27:56 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #1/20
2025-11-03 02:27:57 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #2/20
2025-11-03 02:27:58 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #3/20
2025-11-03 02:27:58 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #4/20
2025-11-03 02:27:59 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #5/20
2025-11-03 02:27:59 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #6/20
2025-11-03 02:28:00 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #7/20
2025-11-03 02:28:00 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #8/20
2025-11-03 02:28:01 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #9/20
2025-11-03 02:28:02 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #10/20
2025-11-03 02:28:03 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #11/20
2025-11-03 02:28:04 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #12/20
2025-11-03 02:28:04 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #13/20
2025-11-03 02:28:05 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #14/20
2025-11-03 02:28:05 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #15/20
2025-11-03 02:28:06 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #16/20
2025-11-03 02:28:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #17/20
2025-11-03 02:28:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #18/20
2025-11-03 02:28:08 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #19/20
2025-11-03 02:28:09 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #20/20
2025-11-03 02:28:09 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, requested 20 jobs, got 20, 10.17 s/job
2025-11-03 02:28:12 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #1/20 start
2025-11-03 02:28:14 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #2/20 start
2025-11-03 02:28:16 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #3/20 start
2025-11-03 02:28:17 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #4/20 start
2025-11-03 02:28:20 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #5/20 start
2025-11-03 02:28:22 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #6/20 start
2025-11-03 02:28:24 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #7/20 start
2025-11-03 02:28:26 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #8/20 start
2025-11-03 02:28:28 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #9/20 start
2025-11-03 02:28:30 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #10/20 start
2025-11-03 02:28:31 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #11/20 start
2025-11-03 02:28:33 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #12/20 start
2025-11-03 02:28:35 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #13/20 start
2025-11-03 02:28:37 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #14/20 start
2025-11-03 02:28:38 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #15/20 start
2025-11-03 02:28:41 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #16/20 start
2025-11-03 02:28:43 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #17/20 start
2025-11-03 02:28:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #18/20 start
2025-11-03 02:28:46 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #19/20 start
2025-11-03 02:28:48 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #20/20 start
2025-11-03 02:29:03 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, starting new job
2025-11-03 02:29:08 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, pending 3 = ∑3/20, started new job
2025-11-03 02:29:10 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 3 = ∑3/20, started new job
2025-11-03 02:29:12 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/unknown 3/1 = ∑4/20, starting new job
2025-11-03 02:29:13 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/unknown 3/1 = ∑4/20, started new job
2025-11-03 02:29:13 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/unknown 3/1 = ∑4/20, starting new job
2025-11-03 02:29:15 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/pending/unknown 3/1/1 = ∑5/20, started new job
2025-11-03 02:29:21 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/unknown 5/1 = ∑6/20, started new job
2025-11-03 02:29:22 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/unknown 5/2 = ∑7/20, started new job
2025-11-03 02:29:25 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/pending 7/1 = ∑8/20, started new job
2025-11-03 02:29:31 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/unknown 8/1 = ∑9/20, started new job
2025-11-03 02:29:37 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/pending/unknown 8/2/2 = ∑12/20, started new job
2025-11-03 02:29:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/pending/unknown 8/4/3 = ∑15/20, started new job
2025-11-03 02:29:47 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/pending 15/3 = ∑18/20, started new job
2025-11-03 02:29:51 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/unknown 18/2 = ∑20/20, started new job
2025-11-03 02:29:54 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/pending 18/2 = ∑20/20, waiting for 20 jobs
2025-11-03 02:30:10 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 20 = ∑20/20, waiting for 20 jobs
2025-11-03 02:52:43 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 20 = ∑20/20, new result: VAL_ACC: 69.450000
2025-11-03 02:53:11 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 19 = ∑19/20, waiting for 20 jobs, finished 1 job
2025-11-03 02:53:12 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 19 = ∑19/20, waiting for 19 jobs
2025-11-03 02:53:14 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 19 = ∑19/20, new result: VAL_ACC: 69.620000
2025-11-03 02:53:14 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 19 = ∑19/20, new result: VAL_ACC: 69.170000
2025-11-03 02:53:52 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 17 = ∑17/20, waiting for 19 jobs, finished 2 jobs
2025-11-03 02:53:52 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 17 = ∑17/20, waiting for 17 jobs
2025-11-03 02:54:05 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 17 = ∑17/20, new result: VAL_ACC: 69.360000
2025-11-03 02:54:05 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 17 = ∑17/20, new result: VAL_ACC: 70.420000
2025-11-03 02:54:05 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 17 = ∑17/20, new result: VAL_ACC: 69.690000
2025-11-03 02:54:05 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 17 = ∑17/20, new result: VAL_ACC: 69.240000
2025-11-03 02:54:05 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 17 = ∑17/20, new result: VAL_ACC: 70.110000
2025-11-03 02:54:05 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 17 = ∑17/20, new result: VAL_ACC: 69.580000
2025-11-03 02:54:06 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 17 = ∑17/20, new result: VAL_ACC: 69.810000
2025-11-03 02:54:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 17 = ∑17/20, new result: VAL_ACC: 70.090000
2025-11-03 02:54:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 17 = ∑17/20, new result: VAL_ACC: 70.040000
2025-11-03 02:54:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 17 = ∑17/20, new result: VAL_ACC: 70.390000
2025-11-03 02:54:08 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 17 = ∑17/20, new result: VAL_ACC: 69.350000
2025-11-03 02:54:08 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 17 = ∑17/20, new result: VAL_ACC: 69.500000
2025-11-03 02:59:53 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 5 = ∑5/20, waiting for 17 jobs, finished 12 jobs
2025-11-03 02:59:53 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 5 = ∑5/20, waiting for 5 jobs
2025-11-03 02:59:59 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 5 = ∑5/20, new result: VAL_ACC: 69.190000
2025-11-03 02:59:59 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 5 = ∑5/20, new result: VAL_ACC: 69.590000
2025-11-03 02:59:59 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 5 = ∑5/20, new result: VAL_ACC: 69.750000
2025-11-03 03:00:00 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 5 = ∑5/20, new result: VAL_ACC: 70.160000
2025-11-03 03:00:00 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 5 = ∑5/20, new result: VAL_ACC: 70.100000
2025-11-03 03:01:50 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, waiting for 5 jobs, finished 5 jobs
2025-11-03 03:05:02 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #1/20
2025-11-03 03:05:03 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #2/20
2025-11-03 03:05:03 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #3/20
2025-11-03 03:05:04 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #4/20
2025-11-03 03:05:04 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #5/20
2025-11-03 03:05:05 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #6/20
2025-11-03 03:05:06 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #7/20
2025-11-03 03:05:06 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #8/20
2025-11-03 03:05:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #9/20
2025-11-03 03:05:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #10/20
2025-11-03 03:05:08 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #11/20
2025-11-03 03:05:09 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #12/20
2025-11-03 03:05:09 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #13/20
2025-11-03 03:05:10 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #14/20
2025-11-03 03:05:10 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #15/20
2025-11-03 03:05:11 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #16/20
2025-11-03 03:05:12 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #17/20
2025-11-03 03:05:12 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #18/20
2025-11-03 03:05:13 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #19/20
2025-11-03 03:05:14 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, getting new HP set #20/20
2025-11-03 03:05:15 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, requested 20 jobs, got 20, 10.15 s/job
2025-11-03 03:05:18 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #1/20 start
2025-11-03 03:05:20 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #2/20 start
2025-11-03 03:05:23 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #3/20 start
2025-11-03 03:05:24 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #4/20 start
2025-11-03 03:05:26 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #5/20 start
2025-11-03 03:05:30 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #6/20 start
2025-11-03 03:05:32 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #7/20 start
2025-11-03 03:05:35 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #8/20 start
2025-11-03 03:05:37 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #9/20 start
2025-11-03 03:05:39 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #10/20 start
2025-11-03 03:05:41 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #11/20 start
2025-11-03 03:05:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #12/20 start
2025-11-03 03:05:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #13/20 start
2025-11-03 03:05:46 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #14/20 start
2025-11-03 03:05:47 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #15/20 start
2025-11-03 03:05:49 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #16/20 start
2025-11-03 03:05:52 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #17/20 start
2025-11-03 03:05:54 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #18/20 start
2025-11-03 03:05:56 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #19/20 start
2025-11-03 03:05:59 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, eval #20/20 start
2025-11-03 03:06:15 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, starting new job
2025-11-03 03:06:21 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 3 = ∑3/20, started new job
2025-11-03 03:06:24 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 3 = ∑3/20, starting new job
2025-11-03 03:06:28 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/unknown 3/1 = ∑4/20, started new job
2025-11-03 03:06:29 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/unknown 3/1 = ∑4/20, starting new job
2025-11-03 03:06:33 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/pending/unknown 3/1/1 = ∑5/20, started new job
2025-11-03 03:06:43 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/unknown 5/1 = ∑6/20, started new job
2025-11-03 03:06:50 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/pending 6/3 = ∑9/20, started new job
2025-11-03 03:06:55 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/unknown 9/3 = ∑12/20, started new job
2025-11-03 03:07:03 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/unknown 12/1 = ∑13/20, started new job
2025-11-03 03:07:14 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/pending/unknown 12/1/2 = ∑15/20, started new job
2025-11-03 03:07:18 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/pending 15/1 = ∑16/20, started new job
2025-11-03 03:07:23 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/unknown 16/1 = ∑17/20, started new job
2025-11-03 03:07:28 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/pending/unknown 16/1/1 = ∑18/20, started new job
2025-11-03 03:07:34 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/pending/unknown 16/2/2 = ∑20/20, started new job
2025-11-03 03:07:36 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/pending 16/4 = ∑20/20, waiting for 20 jobs
2025-11-03 03:07:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 20 = ∑20/20, waiting for 20 jobs
2025-11-03 03:27:34 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 20 = ∑20/20, new result: VAL_ACC: 69.920000
2025-11-03 03:28:19 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 19 = ∑19/20, waiting for 20 jobs, finished 1 job
2025-11-03 03:28:19 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 19 = ∑19/20, waiting for 19 jobs
2025-11-03 03:28:22 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 19 = ∑19/20, new result: VAL_ACC: 70.750000
2025-11-03 03:28:22 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 19 = ∑19/20, new result: VAL_ACC: 70.270000
2025-11-03 03:29:01 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/completed 16/1 = ∑17/20, waiting for 19 jobs, finished 2 jobs
2025-11-03 03:29:01 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/completed 16/1 = ∑17/20, waiting for 17 jobs
2025-11-03 03:29:03 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running/completed 16/1 = ∑17/20, new result: VAL_ACC: 70.050000
2025-11-03 03:29:31 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 16 = ∑16/20, waiting for 17 jobs, finished 1 job
2025-11-03 03:29:31 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 16 = ∑16/20, waiting for 16 jobs
2025-11-03 03:29:35 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 16 = ∑16/20, new result: VAL_ACC: 70.700000
2025-11-03 03:29:35 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 16 = ∑16/20, new result: VAL_ACC: 70.810000
2025-11-03 03:29:35 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 16 = ∑16/20, new result: VAL_ACC: 70.680000
2025-11-03 03:30:31 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 13 = ∑13/20, waiting for 16 jobs, finished 3 jobs
2025-11-03 03:30:32 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 13 = ∑13/20, waiting for 13 jobs
2025-11-03 03:30:37 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 13 = ∑13/20, new result: VAL_ACC: 70.900000
2025-11-03 03:30:37 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 13 = ∑13/20, new result: VAL_ACC: 70.670000
2025-11-03 03:30:37 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 13 = ∑13/20, new result: VAL_ACC: 70.690000
2025-11-03 03:30:38 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 13 = ∑13/20, new result: VAL_ACC: 71.230000
2025-11-03 03:30:39 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 13 = ∑13/20, new result: VAL_ACC: 70.630000
2025-11-03 03:32:25 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 8 = ∑8/20, waiting for 13 jobs, finished 5 jobs
2025-11-03 03:32:25 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 8 = ∑8/20, waiting for 8 jobs
2025-11-03 03:32:31 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 8 = ∑8/20, new result: VAL_ACC: 71.070000
2025-11-03 03:32:31 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 8 = ∑8/20, new result: VAL_ACC: 71.420000
2025-11-03 03:32:31 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 8 = ∑8/20, new result: VAL_ACC: 70.970000
2025-11-03 03:32:32 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 8 = ∑8/20, new result: VAL_ACC: 71.550000
2025-11-03 03:32:32 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.49, running 8 = ∑8/20, new result: VAL_ACC: 71.470000
2025-11-03 03:34:22 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 3 = ∑3/20, waiting for 8 jobs, finished 5 jobs
2025-11-03 03:34:23 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 3 = ∑3/20, waiting for 3 jobs
2025-11-03 04:05:09 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 3 = ∑3/20, new result: VAL_ACC: 71.140000
2025-11-03 04:05:53 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 2 = ∑2/20, waiting for 3 jobs, finished 1 job
2025-11-03 04:05:54 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 2 = ∑2/20, waiting for 2 jobs
2025-11-03 04:28:25 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 2 = ∑2/20, new result: VAL_ACC: 70.500000
2025-11-03 04:28:56 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 1 = ∑1/20, waiting for 2 jobs, finished 1 job
2025-11-03 04:28:56 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 1 = ∑1/20, waiting for 1 job
2025-11-03 04:29:23 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 1 = ∑1/20, new result: VAL_ACC: 70.420000
2025-11-03 04:29:57 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, waiting for 1 job, finished 1 job
2025-11-03 04:34:14 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #1/20
2025-11-03 04:34:15 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #2/20
2025-11-03 04:34:15 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #3/20
2025-11-03 04:34:16 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #4/20
2025-11-03 04:34:17 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #5/20
2025-11-03 04:34:17 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #6/20
2025-11-03 04:34:18 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #7/20
2025-11-03 04:34:18 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #8/20
2025-11-03 04:34:19 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #9/20
2025-11-03 04:34:20 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #10/20
2025-11-03 04:34:20 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #11/20
2025-11-03 04:34:21 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #12/20
2025-11-03 04:34:21 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #13/20
2025-11-03 04:34:22 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #14/20
2025-11-03 04:34:23 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #15/20
2025-11-03 04:34:23 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #16/20
2025-11-03 04:34:24 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #17/20
2025-11-03 04:34:24 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #18/20
2025-11-03 04:34:25 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #19/20
2025-11-03 04:34:26 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #20/20
2025-11-03 04:34:26 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, requested 20 jobs, got 20, 13.35 s/job
2025-11-03 04:34:28 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #1/20 start
2025-11-03 04:34:31 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #2/20 start
2025-11-03 04:34:33 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #3/20 start
2025-11-03 04:34:35 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #4/20 start
2025-11-03 04:34:39 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #5/20 start
2025-11-03 04:34:40 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #6/20 start
2025-11-03 04:34:43 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #7/20 start
2025-11-03 04:34:45 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #8/20 start
2025-11-03 04:34:47 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #9/20 start
2025-11-03 04:34:48 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #10/20 start
2025-11-03 04:34:51 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #11/20 start
2025-11-03 04:34:53 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #12/20 start
2025-11-03 04:34:55 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #13/20 start
2025-11-03 04:34:57 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #14/20 start
2025-11-03 04:34:59 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #15/20 start
2025-11-03 04:35:01 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #16/20 start
2025-11-03 04:35:03 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #17/20 start
2025-11-03 04:35:06 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #18/20 start
2025-11-03 04:35:08 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #19/20 start
2025-11-03 04:35:12 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #20/20 start
2025-11-03 04:35:27 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, starting new job
2025-11-03 04:35:33 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 3 = ∑3/20, started new job
2025-11-03 04:35:37 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 3 = ∑3/20, starting new job
2025-11-03 04:35:40 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running/unknown 3/1 = ∑4/20, started new job
2025-11-03 04:35:41 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running/unknown 3/1 = ∑4/20, starting new job
2025-11-03 04:35:45 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running/pending/unknown 3/1/1 = ∑5/20, started new job
2025-11-03 04:35:51 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running/pending 5/2 = ∑7/20, started new job
2025-11-03 04:35:55 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running/pending/unknown 5/2/1 = ∑8/20, started new job
2025-11-03 04:36:01 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running/pending 5/5 = ∑10/20, started new job
2025-11-03 04:36:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running/pending 5/8 = ∑13/20, started new job
2025-11-03 04:36:10 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running/unknown 13/1 = ∑14/20, started new job
2025-11-03 04:36:20 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running/unknown 14/1 = ∑15/20, started new job
2025-11-03 04:36:30 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running/unknown 15/1 = ∑16/20, started new job
2025-11-03 04:36:37 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running/pending 15/4 = ∑19/20, started new job
2025-11-03 04:36:40 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running/pending/unknown 15/4/1 = ∑20/20, started new job
2025-11-03 04:36:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running/pending 15/5 = ∑20/20, waiting for 20 jobs
2025-11-03 04:36:54 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 20 = ∑20/20, waiting for 20 jobs
2025-11-03 04:58:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 20 = ∑20/20, new result: VAL_ACC: 68.900000
2025-11-03 04:59:16 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 19 = ∑19/20, waiting for 20 jobs, finished 1 job
2025-11-03 04:59:16 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 19 = ∑19/20, waiting for 19 jobs
2025-11-03 04:59:21 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 19 = ∑19/20, new result: VAL_ACC: 68.940000
2025-11-03 04:59:21 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 19 = ∑19/20, new result: VAL_ACC: 69.610000
2025-11-03 04:59:21 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 19 = ∑19/20, new result: VAL_ACC: 69.630000
2025-11-03 04:59:22 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 19 = ∑19/20, new result: VAL_ACC: 69.050000
2025-11-03 05:00:51 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 15 = ∑15/20, waiting for 19 jobs, finished 4 jobs
2025-11-03 05:00:51 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 15 = ∑15/20, waiting for 15 jobs
2025-11-03 05:00:56 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 15 = ∑15/20, new result: VAL_ACC: 69.230000
2025-11-03 05:00:56 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 15 = ∑15/20, new result: VAL_ACC: 69.260000
2025-11-03 05:00:57 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 15 = ∑15/20, new result: VAL_ACC: 69.630000
2025-11-03 05:00:57 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 15 = ∑15/20, new result: VAL_ACC: 68.770000
2025-11-03 05:02:32 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 11 = ∑11/20, waiting for 15 jobs, finished 4 jobs
2025-11-03 05:02:33 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 11 = ∑11/20, waiting for 11 jobs
2025-11-03 05:02:36 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 11 = ∑11/20, new result: VAL_ACC: 69.880000
2025-11-03 05:02:36 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 11 = ∑11/20, new result: VAL_ACC: 69.030000
2025-11-03 05:03:30 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 9 = ∑9/20, waiting for 11 jobs, finished 2 jobs
2025-11-03 05:03:30 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 9 = ∑9/20, waiting for 9 jobs
2025-11-03 05:27:29 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 9 = ∑9/20, new result: VAL_ACC: 69.990000
2025-11-03 05:28:02 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 8 = ∑8/20, waiting for 9 jobs, finished 1 job
2025-11-03 05:28:02 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 8 = ∑8/20, waiting for 8 jobs
2025-11-03 05:28:24 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 8 = ∑8/20, new result: VAL_ACC: 70.160000
2025-11-03 05:28:55 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 7 = ∑7/20, waiting for 8 jobs, finished 1 job
2025-11-03 05:28:55 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 7 = ∑7/20, waiting for 7 jobs
2025-11-03 05:28:57 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 7 = ∑7/20, new result: VAL_ACC: 69.820000
2025-11-03 05:29:27 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 6 = ∑6/20, waiting for 7 jobs, finished 1 job
2025-11-03 05:29:27 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 6 = ∑6/20, waiting for 6 jobs
2025-11-03 05:29:52 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 6 = ∑6/20, new result: VAL_ACC: 70.220000
2025-11-03 05:30:23 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 5 = ∑5/20, waiting for 6 jobs, finished 1 job
2025-11-03 05:30:23 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 5 = ∑5/20, waiting for 5 jobs
2025-11-03 05:30:25 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 5 = ∑5/20, new result: VAL_ACC: 69.990000
2025-11-03 05:30:56 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 4 = ∑4/20, waiting for 5 jobs, finished 1 job
2025-11-03 05:30:56 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 4 = ∑4/20, waiting for 4 jobs
2025-11-03 05:32:06 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 4 = ∑4/20, new result: VAL_ACC: 69.980000
2025-11-03 05:32:37 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 3 = ∑3/20, waiting for 4 jobs, finished 1 job
2025-11-03 05:32:38 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 3 = ∑3/20, waiting for 3 jobs
2025-11-03 05:34:26 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 3 = ∑3/20, new result: VAL_ACC: 70.240000
2025-11-03 05:34:58 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 2 = ∑2/20, waiting for 3 jobs, finished 1 job
2025-11-03 05:34:59 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 2 = ∑2/20, waiting for 2 jobs
2025-11-03 06:09:39 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 2 = ∑2/20, new result: VAL_ACC: 69.520000
2025-11-03 06:10:12 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 1 = ∑1/20, waiting for 2 jobs, finished 1 job
2025-11-03 06:10:13 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 1 = ∑1/20, waiting for 1 job
2025-11-03 06:16:15 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 1 = ∑1/20, new result: VAL_ACC: 69.490000
2025-11-03 06:16:48 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, waiting for 1 job, finished 1 job
2025-11-03 06:20:52 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #1/20
2025-11-03 06:20:53 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #2/20
2025-11-03 06:20:54 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #3/20
2025-11-03 06:20:54 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #4/20
2025-11-03 06:20:55 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #5/20
2025-11-03 06:20:55 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #6/20
2025-11-03 06:20:56 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #7/20
2025-11-03 06:20:57 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #8/20
2025-11-03 06:20:57 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #9/20
2025-11-03 06:20:58 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #10/20
2025-11-03 06:20:58 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #11/20
2025-11-03 06:20:59 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #12/20
2025-11-03 06:21:00 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #13/20
2025-11-03 06:21:00 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #14/20
2025-11-03 06:21:01 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #15/20
2025-11-03 06:21:02 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #16/20
2025-11-03 06:21:02 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #17/20
2025-11-03 06:21:03 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #18/20
2025-11-03 06:21:03 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #19/20
2025-11-03 06:21:04 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #20/20
2025-11-03 06:21:05 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, requested 20 jobs, got 20, 12.74 s/job
2025-11-03 06:21:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #1/20 start
2025-11-03 06:21:10 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #2/20 start
2025-11-03 06:21:12 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #3/20 start
2025-11-03 06:21:16 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #4/20 start
2025-11-03 06:21:17 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #5/20 start
2025-11-03 06:21:19 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #6/20 start
2025-11-03 06:21:21 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #7/20 start
2025-11-03 06:21:23 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #8/20 start
2025-11-03 06:21:25 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #9/20 start
2025-11-03 06:21:28 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #10/20 start
2025-11-03 06:21:30 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #11/20 start
2025-11-03 06:21:32 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #12/20 start
2025-11-03 06:21:34 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #13/20 start
2025-11-03 06:21:36 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #14/20 start
2025-11-03 06:21:38 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #15/20 start
2025-11-03 06:21:39 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #16/20 start
2025-11-03 06:21:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #17/20 start
2025-11-03 06:21:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #18/20 start
2025-11-03 06:21:48 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #19/20 start
2025-11-03 06:21:50 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #20/20 start
2025-11-03 06:22:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, starting new job
2025-11-03 06:22:10 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, pending 1 = ∑1/20, started new job
2025-11-03 06:22:11 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, pending 1 = ∑1/20, starting new job
2025-11-03 06:22:16 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running/unknown 1/2 = ∑3/20, started new job
2025-11-03 06:22:18 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 3 = ∑3/20, starting new job
2025-11-03 06:22:21 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running/unknown 3/2 = ∑5/20, started new job
2025-11-03 06:22:22 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running/pending 3/2 = ∑5/20, starting new job
2025-11-03 06:22:24 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running/pending/unknown 3/2/1 = ∑6/20, started new job
2025-11-03 06:22:29 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running/pending 6/1 = ∑7/20, started new job
2025-11-03 06:22:37 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running/unknown 7/3 = ∑10/20, started new job
2025-11-03 06:22:41 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running/pending 7/6 = ∑13/20, started new job
2025-11-03 06:22:47 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running/pending/unknown 7/6/3 = ∑16/20, started new job
2025-11-03 06:22:49 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running/pending 16/1 = ∑17/20, started new job
2025-11-03 06:22:54 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running/unknown 17/1 = ∑18/20, started new job
2025-11-03 06:22:59 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running/pending/unknown 17/1/1 = ∑19/20, started new job
2025-11-03 06:23:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running/pending 17/3 = ∑20/20, started new job
2025-11-03 06:23:09 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 20 = ∑20/20, waiting for 20 jobs
2025-11-03 06:44:40 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 20 = ∑20/20, new result: VAL_ACC: 70.730000
2025-11-03 06:45:16 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 19 = ∑19/20, waiting for 20 jobs, finished 1 job
2025-11-03 06:45:17 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 19 = ∑19/20, waiting for 19 jobs
2025-11-03 06:45:18 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 19 = ∑19/20, new result: VAL_ACC: 70.430000
2025-11-03 06:45:53 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 18 = ∑18/20, waiting for 19 jobs, finished 1 job
2025-11-03 06:45:54 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 18 = ∑18/20, waiting for 18 jobs
2025-11-03 06:45:57 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 18 = ∑18/20, new result: VAL_ACC: 70.370000
2025-11-03 06:45:57 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 18 = ∑18/20, new result: VAL_ACC: 70.250000
2025-11-03 06:46:41 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running/completed 12/4 = ∑16/20, waiting for 18 jobs, finished 2 jobs
2025-11-03 06:46:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running/completed 12/4 = ∑16/20, waiting for 16 jobs
2025-11-03 06:46:47 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running/completed 12/4 = ∑16/20, new result: VAL_ACC: 70.730000
2025-11-03 06:46:47 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running/completed 12/4 = ∑16/20, new result: VAL_ACC: 71.090000
2025-11-03 06:46:47 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running/completed 12/4 = ∑16/20, new result: VAL_ACC: 69.630000
2025-11-03 06:46:48 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running/completed 12/4 = ∑16/20, new result: VAL_ACC: 70.730000
2025-11-03 06:48:20 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 12 = ∑12/20, waiting for 16 jobs, finished 4 jobs
2025-11-03 06:48:21 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 12 = ∑12/20, waiting for 12 jobs
2025-11-03 06:48:27 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 12 = ∑12/20, new result: VAL_ACC: 70.690000
2025-11-03 06:48:27 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 12 = ∑12/20, new result: VAL_ACC: 70.910000
2025-11-03 06:48:27 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 12 = ∑12/20, new result: VAL_ACC: 70.500000
2025-11-03 06:48:27 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 12 = ∑12/20, new result: VAL_ACC: 71.090000
2025-11-03 06:48:28 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 12 = ∑12/20, new result: VAL_ACC: 71.250000
2025-11-03 06:50:25 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 7 = ∑7/20, waiting for 12 jobs, finished 5 jobs
2025-11-03 06:50:25 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 7 = ∑7/20, waiting for 7 jobs
2025-11-03 06:54:38 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 7 = ∑7/20, new result: VAL_ACC: 70.950000
2025-11-03 06:55:24 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 6 = ∑6/20, waiting for 7 jobs, finished 1 job
2025-11-03 06:55:25 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 6 = ∑6/20, waiting for 6 jobs
2025-11-03 07:01:02 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 6 = ∑6/20, new result: VAL_ACC: 70.410000
2025-11-03 07:01:38 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 5 = ∑5/20, waiting for 6 jobs, finished 1 job
2025-11-03 07:01:38 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 5 = ∑5/20, waiting for 5 jobs
2025-11-03 07:07:14 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 5 = ∑5/20, new result: VAL_ACC: 70.890000
2025-11-03 07:07:48 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 4 = ∑4/20, waiting for 5 jobs, finished 1 job
2025-11-03 07:07:48 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 4 = ∑4/20, waiting for 4 jobs
2025-11-03 07:08:55 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 4 = ∑4/20, new result: VAL_ACC: 70.210000
2025-11-03 07:09:28 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 3 = ∑3/20, waiting for 4 jobs, finished 1 job
2025-11-03 07:09:29 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 3 = ∑3/20, waiting for 3 jobs
2025-11-03 07:09:30 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 3 = ∑3/20, new result: VAL_ACC: 70.550000
2025-11-03 07:10:04 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 2 = ∑2/20, waiting for 3 jobs, finished 1 job
2025-11-03 07:10:04 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 2 = ∑2/20, waiting for 2 jobs
2025-11-03 07:10:49 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 2 = ∑2/20, new result: VAL_ACC: 70.590000
2025-11-03 07:11:21 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 1 = ∑1/20, waiting for 2 jobs, finished 1 job
2025-11-03 07:11:22 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 1 = ∑1/20, waiting for 1 job
2025-11-03 07:12:35 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 1 = ∑1/20, new result: VAL_ACC: 70.090000
2025-11-03 07:13:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, waiting for 1 job, finished 1 job
2025-11-03 07:18:17 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #1/20
2025-11-03 07:18:17 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #2/20
2025-11-03 07:18:18 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #3/20
2025-11-03 07:18:20 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #4/20
2025-11-03 07:18:21 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #5/20
2025-11-03 07:18:22 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #6/20
2025-11-03 07:18:23 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #7/20
2025-11-03 07:18:23 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #8/20
2025-11-03 07:18:24 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #9/20
2025-11-03 07:18:26 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #10/20
2025-11-03 07:18:26 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #11/20
2025-11-03 07:18:27 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #12/20
2025-11-03 07:18:27 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #13/20
2025-11-03 07:18:28 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #14/20
2025-11-03 07:18:29 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #15/20
2025-11-03 07:18:29 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #16/20
2025-11-03 07:18:30 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #17/20
2025-11-03 07:18:31 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #18/20
2025-11-03 07:18:31 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #19/20
2025-11-03 07:18:33 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, getting new HP set #20/20
2025-11-03 07:18:33 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, requested 20 jobs, got 20, 16.20 s/job
2025-11-03 07:18:36 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #1/20 start
2025-11-03 07:18:38 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #2/20 start
2025-11-03 07:18:40 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #3/20 start
2025-11-03 07:18:41 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #4/20 start
2025-11-03 07:18:43 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #5/20 start
2025-11-03 07:18:45 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #6/20 start
2025-11-03 07:18:47 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #7/20 start
2025-11-03 07:18:49 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #8/20 start
2025-11-03 07:18:51 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #9/20 start
2025-11-03 07:18:52 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #10/20 start
2025-11-03 07:18:54 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #11/20 start
2025-11-03 07:18:56 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #12/20 start
2025-11-03 07:18:58 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #13/20 start
2025-11-03 07:19:00 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #14/20 start
2025-11-03 07:19:02 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #15/20 start
2025-11-03 07:19:04 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #16/20 start
2025-11-03 07:19:06 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #17/20 start
2025-11-03 07:19:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #18/20 start
2025-11-03 07:19:09 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #19/20 start
2025-11-03 07:19:11 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, eval #20/20 start
2025-11-03 07:19:28 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, starting new job
2025-11-03 07:19:34 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running/pending 1/2 = ∑3/20, started new job
2025-11-03 07:19:38 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running/pending 1/3 = ∑4/20, starting new job
2025-11-03 07:19:39 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running/pending 1/3 = ∑4/20, started new job
2025-11-03 07:19:41 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running/pending 1/3 = ∑4/20, starting new job
2025-11-03 07:19:43 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running/pending 1/6 = ∑7/20, started new job
2025-11-03 07:19:47 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running/pending/unknown 1/6/2 = ∑9/20, started new job
2025-11-03 07:19:52 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running/pending 9/2 = ∑11/20, started new job
2025-11-03 07:19:57 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running/pending/unknown 9/2/2 = ∑13/20, started new job
2025-11-03 07:20:02 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running/pending/unknown 9/4/2 = ∑15/20, started new job
2025-11-03 07:20:06 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running/pending/unknown 9/6/1 = ∑16/20, started new job
2025-11-03 07:20:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running/pending/unknown 9/6/2 = ∑17/20, started new job
2025-11-03 07:20:12 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running/unknown 17/2 = ∑19/20, started new job
2025-11-03 07:20:16 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running/pending/unknown 17/2/1 = ∑20/20, started new job
2025-11-03 07:20:18 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 20 = ∑20/20, waiting for 20 jobs
2025-11-03 07:43:47 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 20 = ∑20/20, new result: VAL_ACC: 71.220000
2025-11-03 07:44:21 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 19 = ∑19/20, waiting for 20 jobs, finished 1 job
2025-11-03 07:44:22 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 19 = ∑19/20, waiting for 19 jobs
2025-11-03 07:49:05 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 19 = ∑19/20, new result: VAL_ACC: 69.310000
2025-11-03 07:49:47 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 18 = ∑18/20, waiting for 19 jobs, finished 1 job
2025-11-03 07:49:47 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 18 = ∑18/20, waiting for 18 jobs
2025-11-03 07:54:11 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 18 = ∑18/20, new result: VAL_ACC: 66.830000
2025-11-03 07:54:52 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 17 = ∑17/20, waiting for 18 jobs, finished 1 job
2025-11-03 07:54:53 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 17 = ∑17/20, waiting for 17 jobs
2025-11-03 08:02:19 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 17 = ∑17/20, new result: VAL_ACC: 67.360000
2025-11-03 08:03:03 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 16 = ∑16/20, waiting for 17 jobs, finished 1 job
2025-11-03 08:03:03 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 16 = ∑16/20, waiting for 16 jobs
2025-11-03 08:41:03 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 16 = ∑16/20, new result: VAL_ACC: 70.240000
2025-11-03 08:41:43 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 15 = ∑15/20, waiting for 16 jobs, finished 1 job
2025-11-03 08:41:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 15 = ∑15/20, waiting for 15 jobs
2025-11-03 08:41:45 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 15 = ∑15/20, new result: VAL_ACC: 69.980000
2025-11-03 08:42:24 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 14 = ∑14/20, waiting for 15 jobs, finished 1 job
2025-11-03 08:42:24 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 14 = ∑14/20, waiting for 14 jobs
2025-11-03 08:42:46 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 14 = ∑14/20, new result: VAL_ACC: 69.770000
2025-11-03 08:43:22 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 13 = ∑13/20, waiting for 14 jobs, finished 1 job
2025-11-03 08:43:23 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 13 = ∑13/20, waiting for 13 jobs
2025-11-03 08:44:43 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 13 = ∑13/20, new result: VAL_ACC: 69.520000
2025-11-03 08:45:18 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 12 = ∑12/20, waiting for 13 jobs, finished 1 job
2025-11-03 08:45:19 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 12 = ∑12/20, waiting for 12 jobs
2025-11-03 08:45:20 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 12 = ∑12/20, new result: VAL_ACC: 69.840000
2025-11-03 08:45:54 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 11 = ∑11/20, waiting for 12 jobs, finished 1 job
2025-11-03 08:45:55 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 11 = ∑11/20, waiting for 11 jobs
2025-11-03 08:45:57 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 11 = ∑11/20, new result: VAL_ACC: 70.200000
2025-11-03 08:46:34 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 10 = ∑10/20, waiting for 11 jobs, finished 1 job
2025-11-03 08:46:35 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 10 = ∑10/20, waiting for 10 jobs
2025-11-03 08:48:17 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 10 = ∑10/20, new result: VAL_ACC: 69.610000
2025-11-03 08:48:56 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 9 = ∑9/20, waiting for 10 jobs, finished 1 job
2025-11-03 08:48:56 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 9 = ∑9/20, waiting for 9 jobs
2025-11-03 08:56:08 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 9 = ∑9/20, new result: VAL_ACC: 70.750000
2025-11-03 08:56:45 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 8 = ∑8/20, waiting for 9 jobs, finished 1 job
2025-11-03 08:56:46 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 8 = ∑8/20, waiting for 8 jobs
2025-11-03 08:57:45 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 8 = ∑8/20, new result: VAL_ACC: 68.040000
2025-11-03 08:58:27 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 7 = ∑7/20, waiting for 8 jobs, finished 1 job
2025-11-03 08:58:27 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 7 = ∑7/20, waiting for 7 jobs
2025-11-03 09:00:38 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 7 = ∑7/20, new result: VAL_ACC: 69.880000
2025-11-03 09:01:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 6 = ∑6/20, waiting for 7 jobs, finished 1 job
2025-11-03 09:01:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 6 = ∑6/20, waiting for 6 jobs
2025-11-03 09:15:24 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 6 = ∑6/20, new result: VAL_ACC: 71.110000
2025-11-03 09:15:37 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 5 = ∑5/20, waiting for 6 jobs, finished 1 job
2025-11-03 09:15:37 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 5 = ∑5/20, waiting for 5 jobs
2025-11-03 09:15:39 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 5 = ∑5/20, new result: VAL_ACC: 71.340000
2025-11-03 09:16:18 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 4 = ∑4/20, waiting for 5 jobs, finished 1 job
2025-11-03 09:16:19 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 4 = ∑4/20, waiting for 4 jobs
2025-11-03 09:17:54 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 4 = ∑4/20, new result: VAL_ACC: 70.710000
2025-11-03 09:18:32 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 3 = ∑3/20, waiting for 4 jobs, finished 1 job
2025-11-03 09:18:33 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 3 = ∑3/20, waiting for 3 jobs
2025-11-03 09:18:35 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 3 = ∑3/20, new result: VAL_ACC: 71.200000
2025-11-03 09:19:12 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 2 = ∑2/20, waiting for 3 jobs, finished 1 job
2025-11-03 09:19:12 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 2 = ∑2/20, waiting for 2 jobs
2025-11-03 09:21:58 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.55, running 2 = ∑2/20, new result: VAL_ACC: 71.610000
2025-11-03 09:22:48 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, running 1 = ∑1/20, waiting for 2 jobs, finished 1 job
2025-11-03 09:22:49 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, running 1 = ∑1/20, waiting for 1 job
2025-11-03 09:27:04 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, running 1 = ∑1/20, new result: VAL_ACC: 70.920000
2025-11-03 09:27:41 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, waiting for 1 job, finished 1 job
2025-11-03 09:33:58 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, getting new HP set #1/20
2025-11-03 09:33:59 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, getting new HP set #2/20
2025-11-03 09:33:59 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, getting new HP set #3/20
2025-11-03 09:34:00 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, getting new HP set #4/20
2025-11-03 09:34:02 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, getting new HP set #5/20
2025-11-03 09:34:02 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, getting new HP set #6/20
2025-11-03 09:34:03 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, getting new HP set #7/20
2025-11-03 09:34:04 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, getting new HP set #8/20
2025-11-03 09:34:04 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, getting new HP set #9/20
2025-11-03 09:34:05 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, getting new HP set #10/20
2025-11-03 09:34:06 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, getting new HP set #11/20
2025-11-03 09:34:06 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, getting new HP set #12/20
2025-11-03 09:34:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, getting new HP set #13/20
2025-11-03 09:34:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, getting new HP set #14/20
2025-11-03 09:34:08 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, getting new HP set #15/20
2025-11-03 09:34:10 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, getting new HP set #16/20
2025-11-03 09:34:10 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, getting new HP set #17/20
2025-11-03 09:34:11 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, getting new HP set #18/20
2025-11-03 09:34:12 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, getting new HP set #19/20
2025-11-03 09:34:12 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, getting new HP set #20/20
2025-11-03 09:34:13 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, requested 20 jobs, got 20, 19.53 s/job
2025-11-03 09:34:16 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, eval #1/20 start
2025-11-03 09:34:17 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, eval #2/20 start
2025-11-03 09:34:19 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, eval #3/20 start
2025-11-03 09:34:26 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, eval #4/20 start
2025-11-03 09:34:28 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, eval #5/20 start
2025-11-03 09:34:30 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, eval #6/20 start
2025-11-03 09:34:33 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, eval #7/20 start
2025-11-03 09:34:36 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, eval #8/20 start
2025-11-03 09:34:38 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, eval #9/20 start
2025-11-03 09:34:40 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, eval #10/20 start
2025-11-03 09:34:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, eval #11/20 start
2025-11-03 09:34:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, eval #12/20 start
2025-11-03 09:34:46 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, eval #13/20 start
2025-11-03 09:34:48 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, eval #14/20 start
2025-11-03 09:34:50 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, eval #15/20 start
2025-11-03 09:34:51 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, eval #16/20 start
2025-11-03 09:34:54 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, eval #17/20 start
2025-11-03 09:34:56 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, eval #18/20 start
2025-11-03 09:34:58 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, eval #19/20 start
2025-11-03 09:35:00 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, eval #20/20 start
2025-11-03 09:35:17 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, starting new job
2025-11-03 09:35:22 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, running 1 = ∑1/20, started new job
2025-11-03 09:35:23 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, running 1 = ∑1/20, starting new job
2025-11-03 09:35:26 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, running/pending 1/1 = ∑2/20, started new job
2025-11-03 09:35:27 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, running/pending 1/1 = ∑2/20, starting new job
2025-11-03 09:35:33 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, running/pending 1/4 = ∑5/20, started new job
2025-11-03 09:35:37 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, running/pending 1/4 = ∑5/20, starting new job
2025-11-03 09:35:38 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, running/pending 1/6 = ∑7/20, started new job
2025-11-03 09:35:46 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, running/pending 7/1 = ∑8/20, started new job
2025-11-03 09:35:56 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, running/pending 8/1 = ∑9/20, started new job
2025-11-03 09:36:08 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, running/pending 9/3 = ∑12/20, started new job
2025-11-03 09:36:13 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, running/pending 9/6 = ∑15/20, started new job
2025-11-03 09:36:18 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, running/pending 9/9 = ∑18/20, started new job
2025-11-03 09:36:21 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, running/pending 18/1 = ∑19/20, started new job
2025-11-03 09:36:31 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, running/pending 18/2 = ∑20/20, started new job
2025-11-03 09:36:33 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, running/pending 18/2 = ∑20/20, waiting for 20 jobs
2025-11-03 09:36:46 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, running 20 = ∑20/20, waiting for 20 jobs
2025-11-03 10:02:32 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, running 20 = ∑20/20, new result: VAL_ACC: 70.390000
2025-11-03 10:03:18 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, running 19 = ∑19/20, waiting for 20 jobs, finished 1 job
2025-11-03 10:03:19 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, running 19 = ∑19/20, waiting for 19 jobs
2025-11-03 10:03:24 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, running 19 = ∑19/20, new result: VAL_ACC: 70.660000
2025-11-03 10:03:24 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, running 19 = ∑19/20, new result: VAL_ACC: 71.610000
2025-11-03 10:03:24 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, running 19 = ∑19/20, new result: VAL_ACC: 70.500000
2025-11-03 10:03:24 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, running 19 = ∑19/20, new result: VAL_ACC: 70.900000
2025-11-03 10:05:08 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, completed/running 2/13 = ∑15/20, waiting for 19 jobs, finished 4 jobs
2025-11-03 10:05:08 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, completed/running 2/13 = ∑15/20, waiting for 15 jobs
2025-11-03 10:05:11 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, completed/running 2/13 = ∑15/20, new result: VAL_ACC: 71.620000
2025-11-03 10:05:12 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.61, completed/running 2/13 = ∑15/20, new result: VAL_ACC: 71.220000
2025-11-03 10:06:21 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 13 = ∑13/20, waiting for 15 jobs, finished 2 jobs
2025-11-03 10:06:22 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 13 = ∑13/20, waiting for 13 jobs
2025-11-03 10:06:23 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 13 = ∑13/20, new result: VAL_ACC: 71.050000
2025-11-03 10:07:10 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 12 = ∑12/20, waiting for 13 jobs, finished 1 job
2025-11-03 10:07:10 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 12 = ∑12/20, waiting for 12 jobs
2025-11-03 10:09:11 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 12 = ∑12/20, new result: VAL_ACC: 70.990000
2025-11-03 10:09:47 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 11 = ∑11/20, waiting for 12 jobs, finished 1 job
2025-11-03 10:09:48 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 11 = ∑11/20, waiting for 11 jobs
2025-11-03 10:27:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 11 = ∑11/20, new result: VAL_ACC: 71.270000
2025-11-03 10:28:22 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 10 = ∑10/20, waiting for 11 jobs, finished 1 job
2025-11-03 10:28:23 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 10 = ∑10/20, waiting for 10 jobs
2025-11-03 10:32:41 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 10 = ∑10/20, new result: VAL_ACC: 70.430000
2025-11-03 10:33:20 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 9 = ∑9/20, waiting for 10 jobs, finished 1 job
2025-11-03 10:33:20 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 9 = ∑9/20, waiting for 9 jobs
2025-11-03 10:51:08 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 9 = ∑9/20, new result: VAL_ACC: 69.640000
2025-11-03 10:51:46 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 8 = ∑8/20, waiting for 9 jobs, finished 1 job
2025-11-03 10:51:46 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 8 = ∑8/20, waiting for 8 jobs
2025-11-03 11:21:47 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 8 = ∑8/20, new result: VAL_ACC: 70.980000
2025-11-03 11:22:26 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 7 = ∑7/20, waiting for 8 jobs, finished 1 job
2025-11-03 11:22:27 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 7 = ∑7/20, waiting for 7 jobs
2025-11-03 11:25:15 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 7 = ∑7/20, new result: VAL_ACC: 71.160000
2025-11-03 11:25:55 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 6 = ∑6/20, waiting for 7 jobs, finished 1 job
2025-11-03 11:25:56 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 6 = ∑6/20, waiting for 6 jobs
2025-11-03 11:36:20 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 6 = ∑6/20, new result: VAL_ACC: 71.370000
2025-11-03 11:37:18 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 5 = ∑5/20, waiting for 6 jobs, finished 1 job
2025-11-03 11:37:18 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 5 = ∑5/20, waiting for 5 jobs
2025-11-03 11:37:20 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 5 = ∑5/20, new result: VAL_ACC: 70.750000
2025-11-03 11:38:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 4 = ∑4/20, waiting for 5 jobs, finished 1 job
2025-11-03 11:38:43 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 4 = ∑4/20, waiting for 4 jobs
2025-11-03 11:38:46 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 4 = ∑4/20, new result: VAL_ACC: 71.150000
2025-11-03 11:38:46 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 4 = ∑4/20, new result: VAL_ACC: 71.070000
2025-11-03 11:39:38 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 2 = ∑2/20, waiting for 4 jobs, finished 2 jobs
2025-11-03 11:39:39 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 2 = ∑2/20, waiting for 2 jobs
2025-11-03 11:39:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 2 = ∑2/20, new result: VAL_ACC: 70.890000
2025-11-03 11:40:27 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 1 = ∑1/20, waiting for 2 jobs, finished 1 job
2025-11-03 11:40:27 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 1 = ∑1/20, waiting for 1 job
2025-11-03 11:53:03 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 1 = ∑1/20, new result: VAL_ACC: 70.690000
2025-11-03 11:53:45 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, waiting for 1 job, finished 1 job
2025-11-03 12:03:20 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #1/20
2025-11-03 12:03:21 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #2/20
2025-11-03 12:03:22 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #3/20
2025-11-03 12:03:22 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #4/20
2025-11-03 12:03:23 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #5/20
2025-11-03 12:03:24 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #6/20
2025-11-03 12:03:24 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #7/20
2025-11-03 12:03:25 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #8/20
2025-11-03 12:03:26 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #9/20
2025-11-03 12:03:26 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #10/20
2025-11-03 12:03:27 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #11/20
2025-11-03 12:03:28 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #12/20
2025-11-03 12:03:28 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #13/20
2025-11-03 12:03:31 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #14/20
2025-11-03 12:03:32 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #15/20
2025-11-03 12:03:32 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #16/20
2025-11-03 12:03:33 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #17/20
2025-11-03 12:03:34 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #18/20
2025-11-03 12:03:35 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #19/20
2025-11-03 12:03:35 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #20/20
2025-11-03 12:03:36 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, requested 20 jobs, got 20, 20.64 s/job
2025-11-03 12:03:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #1/20 start
2025-11-03 12:03:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #2/20 start
2025-11-03 12:03:46 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #3/20 start
2025-11-03 12:03:48 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #4/20 start
2025-11-03 12:03:50 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #5/20 start
2025-11-03 12:03:53 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #6/20 start
2025-11-03 12:03:56 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #7/20 start
2025-11-03 12:03:58 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #8/20 start
2025-11-03 12:04:05 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #9/20 start
2025-11-03 12:04:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #10/20 start
2025-11-03 12:04:09 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #11/20 start
2025-11-03 12:04:11 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #12/20 start
2025-11-03 12:04:13 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #13/20 start
2025-11-03 12:04:15 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #14/20 start
2025-11-03 12:04:17 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #15/20 start
2025-11-03 12:04:19 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #16/20 start
2025-11-03 12:04:21 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #17/20 start
2025-11-03 12:04:23 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #18/20 start
2025-11-03 12:04:25 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #19/20 start
2025-11-03 12:04:27 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #20/20 start
2025-11-03 12:04:45 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, starting new job
2025-11-03 12:04:59 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, unknown 1 = ∑1/20, started new job
2025-11-03 12:05:00 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, unknown 1 = ∑1/20, starting new job
2025-11-03 12:05:10 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running/unknown 1/2 = ∑3/20, started new job
2025-11-03 12:05:12 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running/pending 1/2 = ∑3/20, starting new job
2025-11-03 12:05:14 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running/pending/unknown 1/2/1 = ∑4/20, started new job
2025-11-03 12:05:15 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running/pending/unknown 1/2/1 = ∑4/20, starting new job
2025-11-03 12:05:20 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running/pending/unknown 1/3/1 = ∑5/20, started new job
2025-11-03 12:05:24 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running/unknown 5/1 = ∑6/20, started new job
2025-11-03 12:05:29 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running/pending/unknown 5/1/1 = ∑7/20, started new job
2025-11-03 12:05:34 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running/unknown 7/1 = ∑8/20, started new job
2025-11-03 12:05:39 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running/pending/unknown 7/1/1 = ∑9/20, started new job
2025-11-03 12:05:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running/unknown 9/1 = ∑10/20, started new job
2025-11-03 12:05:49 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running/pending/unknown 9/1/1 = ∑11/20, started new job
2025-11-03 12:05:54 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running/pending/unknown 9/2/1 = ∑12/20, started new job
2025-11-03 12:06:00 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running/pending/unknown 9/3/2 = ∑14/20, started new job
2025-11-03 12:06:04 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running/unknown 14/1 = ∑15/20, started new job
2025-11-03 12:06:09 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running/pending/unknown 14/1/1 = ∑16/20, started new job
2025-11-03 12:06:15 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running/pending/unknown 14/2/2 = ∑18/20, started new job
2025-11-03 12:06:20 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running/pending/unknown 14/4/2 = ∑20/20, started new job
2025-11-03 12:06:22 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 20 = ∑20/20, waiting for 20 jobs
2025-11-03 12:39:54 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 20 = ∑20/20, new result: VAL_ACC: 70.250000
2025-11-03 12:40:40 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 19 = ∑19/20, waiting for 20 jobs, finished 1 job
2025-11-03 12:40:41 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 19 = ∑19/20, waiting for 19 jobs
2025-11-03 12:42:59 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 19 = ∑19/20, new result: VAL_ACC: 70.250000
2025-11-03 12:43:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 18 = ∑18/20, waiting for 19 jobs, finished 1 job
2025-11-03 12:43:43 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 18 = ∑18/20, waiting for 18 jobs
2025-11-03 12:45:38 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 18 = ∑18/20, new result: VAL_ACC: 69.690000
2025-11-03 12:46:16 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 17 = ∑17/20, waiting for 18 jobs, finished 1 job
2025-11-03 12:46:17 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 17 = ∑17/20, waiting for 17 jobs
2025-11-03 12:46:20 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 17 = ∑17/20, new result: VAL_ACC: 70.810000
2025-11-03 12:47:01 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 16 = ∑16/20, waiting for 17 jobs, finished 1 job
2025-11-03 12:47:01 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 16 = ∑16/20, waiting for 16 jobs
2025-11-03 12:47:04 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 16 = ∑16/20, new result: VAL_ACC: 70.200000
2025-11-03 12:47:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 16 = ∑16/20, new result: VAL_ACC: 69.000000
2025-11-03 12:47:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 16 = ∑16/20, new result: VAL_ACC: 69.600000
2025-11-03 12:48:59 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, completed/running 8/5 = ∑13/20, waiting for 16 jobs, finished 3 jobs
2025-11-03 12:49:00 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, completed/running 8/5 = ∑13/20, waiting for 13 jobs
2025-11-03 12:49:10 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, completed/running 8/5 = ∑13/20, new result: VAL_ACC: 70.740000
2025-11-03 12:49:10 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, completed/running 8/5 = ∑13/20, new result: VAL_ACC: 69.430000
2025-11-03 12:49:10 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, completed/running 8/5 = ∑13/20, new result: VAL_ACC: 71.150000
2025-11-03 12:49:10 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, completed/running 8/5 = ∑13/20, new result: VAL_ACC: 70.530000
2025-11-03 12:49:11 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, completed/running 8/5 = ∑13/20, new result: VAL_ACC: 70.840000
2025-11-03 12:49:11 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, completed/running 8/5 = ∑13/20, new result: VAL_ACC: 69.520000
2025-11-03 12:49:11 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, completed/running 8/5 = ∑13/20, new result: VAL_ACC: 70.220000
2025-11-03 12:49:15 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, completed/running 8/5 = ∑13/20, new result: VAL_ACC: 69.780000
2025-11-03 12:54:41 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 5 = ∑5/20, waiting for 13 jobs, finished 8 jobs
2025-11-03 12:54:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 5 = ∑5/20, waiting for 5 jobs
2025-11-03 12:54:47 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 5 = ∑5/20, new result: VAL_ACC: 70.970000
2025-11-03 12:54:47 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 5 = ∑5/20, new result: VAL_ACC: 70.600000
2025-11-03 12:54:47 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 5 = ∑5/20, new result: VAL_ACC: 70.360000
2025-11-03 12:54:48 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 5 = ∑5/20, new result: VAL_ACC: 71.190000
2025-11-03 12:57:25 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 1 = ∑1/20, waiting for 5 jobs, finished 4 jobs
2025-11-03 12:57:26 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 1 = ∑1/20, waiting for 1 job
2025-11-03 13:31:51 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 1 = ∑1/20, new result: VAL_ACC: 69.540000
2025-11-03 13:32:36 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, waiting for 1 job, finished 1 job
2025-11-03 13:39:27 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #1/20
2025-11-03 13:39:28 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #2/20
2025-11-03 13:39:29 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #3/20
2025-11-03 13:39:29 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #4/20
2025-11-03 13:39:30 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #5/20
2025-11-03 13:39:31 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #6/20
2025-11-03 13:39:32 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #7/20
2025-11-03 13:39:32 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #8/20
2025-11-03 13:39:33 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #9/20
2025-11-03 13:39:35 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #10/20
2025-11-03 13:39:35 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #11/20
2025-11-03 13:39:36 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #12/20
2025-11-03 13:39:37 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #13/20
2025-11-03 13:39:38 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #14/20
2025-11-03 13:39:38 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #15/20
2025-11-03 13:39:39 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #16/20
2025-11-03 13:39:40 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #17/20
2025-11-03 13:39:41 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #18/20
2025-11-03 13:39:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #19/20
2025-11-03 13:39:43 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #20/20
2025-11-03 13:39:43 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, requested 20 jobs, got 20, 21.25 s/job
2025-11-03 13:39:47 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #1/20 start
2025-11-03 13:39:49 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #2/20 start
2025-11-03 13:39:51 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #3/20 start
2025-11-03 13:39:53 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #4/20 start
2025-11-03 13:39:55 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #5/20 start
2025-11-03 13:39:57 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #6/20 start
2025-11-03 13:39:59 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #7/20 start
2025-11-03 13:40:02 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #8/20 start
2025-11-03 13:40:04 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #9/20 start
2025-11-03 13:40:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #10/20 start
2025-11-03 13:40:09 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #11/20 start
2025-11-03 13:40:11 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #12/20 start
2025-11-03 13:40:13 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #13/20 start
2025-11-03 13:40:15 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #14/20 start
2025-11-03 13:40:17 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #15/20 start
2025-11-03 13:40:19 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #16/20 start
2025-11-03 13:40:22 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #17/20 start
2025-11-03 13:40:24 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #18/20 start
2025-11-03 13:40:26 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #19/20 start
2025-11-03 13:40:28 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #20/20 start
2025-11-03 13:40:48 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, starting new job
2025-11-03 13:40:51 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, unknown 1 = ∑1/20, started new job
2025-11-03 13:40:53 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, unknown 1 = ∑1/20, starting new job
2025-11-03 13:40:55 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, pending/unknown 1/1 = ∑2/20, started new job
2025-11-03 13:40:56 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, pending/unknown 1/1 = ∑2/20, starting new job
2025-11-03 13:41:00 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, pending/unknown 2/1 = ∑3/20, started new job
2025-11-03 13:41:01 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, pending/unknown 2/1 = ∑3/20, starting new job
2025-11-03 13:41:05 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running/unknown 3/1 = ∑4/20, started new job
2025-11-03 13:41:06 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running/unknown 3/1 = ∑4/20, starting new job
2025-11-03 13:41:10 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running/unknown 4/1 = ∑5/20, started new job
2025-11-03 13:41:15 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running/pending/unknown 4/1/1 = ∑6/20, started new job
2025-11-03 13:41:27 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running/pending/unknown 4/2/3 = ∑9/20, started new job
2025-11-03 13:41:30 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running/unknown 9/1 = ∑10/20, started new job
2025-11-03 13:41:35 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running/unknown 10/1 = ∑11/20, started new job
2025-11-03 13:41:40 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running/pending/unknown 10/1/1 = ∑12/20, started new job
2025-11-03 13:41:45 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running/pending/unknown 10/2/1 = ∑13/20, started new job
2025-11-03 13:41:50 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running/unknown 13/1 = ∑14/20, started new job
2025-11-03 13:41:56 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running/pending/unknown 13/1/1 = ∑15/20, started new job
2025-11-03 13:42:00 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running/pending/unknown 14/1/1 = ∑16/20, started new job
2025-11-03 13:42:10 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running/unknown 16/1 = ∑17/20, started new job
2025-11-03 13:42:15 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running/pending/unknown 16/1/1 = ∑18/20, started new job
2025-11-03 13:42:20 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running/pending/unknown 16/2/1 = ∑19/20, started new job
2025-11-03 13:42:30 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running/pending 19/1 = ∑20/20, started new job
2025-11-03 13:42:32 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running/pending 19/1 = ∑20/20, waiting for 20 jobs
2025-11-03 13:42:37 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 20 = ∑20/20, waiting for 20 jobs
2025-11-03 14:29:43 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 20 = ∑20/20, new result: VAL_ACC: 70.550000
2025-11-03 14:30:32 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 19 = ∑19/20, waiting for 20 jobs, finished 1 job
2025-11-03 14:30:32 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 19 = ∑19/20, waiting for 19 jobs
2025-11-03 14:30:34 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 19 = ∑19/20, new result: VAL_ACC: 69.050000
2025-11-03 14:31:16 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 18 = ∑18/20, waiting for 19 jobs, finished 1 job
2025-11-03 14:31:17 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 18 = ∑18/20, waiting for 18 jobs
2025-11-03 14:31:20 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 18 = ∑18/20, new result: VAL_ACC: 70.290000
2025-11-03 14:31:20 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 18 = ∑18/20, new result: VAL_ACC: 70.230000
2025-11-03 14:32:23 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running/completed 14/2 = ∑16/20, waiting for 18 jobs, finished 2 jobs
2025-11-03 14:32:24 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running/completed 14/2 = ∑16/20, waiting for 16 jobs
2025-11-03 14:32:27 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running/completed 14/2 = ∑16/20, new result: VAL_ACC: 70.740000
2025-11-03 14:32:28 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running/completed 14/2 = ∑16/20, new result: VAL_ACC: 70.320000
2025-11-03 14:33:42 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 14 = ∑14/20, waiting for 16 jobs, finished 2 jobs
2025-11-03 14:33:43 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 14 = ∑14/20, waiting for 14 jobs
2025-11-03 14:33:46 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 14 = ∑14/20, new result: VAL_ACC: 70.410000
2025-11-03 14:33:46 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 14 = ∑14/20, new result: VAL_ACC: 70.690000
2025-11-03 14:34:56 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 12 = ∑12/20, waiting for 14 jobs, finished 2 jobs
2025-11-03 14:34:56 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 12 = ∑12/20, waiting for 12 jobs
2025-11-03 14:35:01 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 12 = ∑12/20, new result: VAL_ACC: 70.780000
2025-11-03 14:35:01 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 12 = ∑12/20, new result: VAL_ACC: 71.280000
2025-11-03 14:35:01 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 12 = ∑12/20, new result: VAL_ACC: 70.730000
2025-11-03 14:36:53 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 9 = ∑9/20, waiting for 12 jobs, finished 3 jobs
2025-11-03 14:36:53 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 9 = ∑9/20, waiting for 9 jobs
2025-11-03 14:36:56 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 9 = ∑9/20, new result: VAL_ACC: 70.280000
2025-11-03 14:36:56 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 9 = ∑9/20, new result: VAL_ACC: 70.460000
2025-11-03 14:38:04 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 7 = ∑7/20, waiting for 9 jobs, finished 2 jobs
2025-11-03 14:38:05 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 7 = ∑7/20, waiting for 7 jobs
2025-11-03 14:53:41 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 7 = ∑7/20, new result: VAL_ACC: 68.070000
2025-11-03 14:54:25 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 6 = ∑6/20, waiting for 7 jobs, finished 1 job
2025-11-03 14:54:26 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 6 = ∑6/20, waiting for 6 jobs
2025-11-03 15:28:52 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 6 = ∑6/20, new result: VAL_ACC: 70.330000
2025-11-03 15:29:38 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 5 = ∑5/20, waiting for 6 jobs, finished 1 job
2025-11-03 15:29:38 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 5 = ∑5/20, waiting for 5 jobs
2025-11-03 15:31:47 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 5 = ∑5/20, new result: VAL_ACC: 70.630000
2025-11-03 15:32:41 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 4 = ∑4/20, waiting for 5 jobs, finished 1 job
2025-11-03 15:32:41 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 4 = ∑4/20, waiting for 4 jobs
2025-11-03 15:33:05 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 4 = ∑4/20, new result: VAL_ACC: 70.770000
2025-11-03 15:33:51 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 3 = ∑3/20, waiting for 4 jobs, finished 1 job
2025-11-03 15:33:52 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 3 = ∑3/20, waiting for 3 jobs
2025-11-03 15:33:55 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 3 = ∑3/20, new result: VAL_ACC: 71.250000
2025-11-03 15:33:55 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 3 = ∑3/20, new result: VAL_ACC: 71.160000
2025-11-03 15:34:56 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 1 = ∑1/20, waiting for 3 jobs, finished 2 jobs
2025-11-03 15:34:57 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 1 = ∑1/20, waiting for 1 job
2025-11-03 15:36:09 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 1 = ∑1/20, new result: VAL_ACC: 70.830000
2025-11-03 15:36:54 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, waiting for 1 job, finished 1 job
2025-11-03 15:45:00 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #1/20
2025-11-03 15:45:01 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #2/20
2025-11-03 15:45:02 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #3/20
2025-11-03 15:45:02 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #4/20
2025-11-03 15:45:03 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #5/20
2025-11-03 15:45:04 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #6/20
2025-11-03 15:45:04 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #7/20
2025-11-03 15:45:05 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #8/20
2025-11-03 15:45:06 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #9/20
2025-11-03 15:45:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #10/20
2025-11-03 15:45:07 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #11/20
2025-11-03 15:45:08 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #12/20
2025-11-03 15:45:09 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #13/20
2025-11-03 15:45:10 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #14/20
2025-11-03 15:45:11 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #15/20
2025-11-03 15:45:13 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #16/20
2025-11-03 15:45:13 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #17/20
2025-11-03 15:45:14 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #18/20
2025-11-03 15:45:15 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #19/20
2025-11-03 15:45:50 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, getting new HP set #20/20
2025-11-03 15:54:56 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, requested 20 jobs, got 19, 56.83 s/job
2025-11-03 15:54:58 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #1/19 start
2025-11-03 15:55:01 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #2/19 start
2025-11-03 15:55:03 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #3/19 start
2025-11-03 15:55:06 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #4/19 start
2025-11-03 15:55:08 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #5/19 start
2025-11-03 15:55:10 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #6/19 start
2025-11-03 15:55:14 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #7/19 start
2025-11-03 15:55:16 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #8/19 start
2025-11-03 15:55:19 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #9/19 start
2025-11-03 15:55:22 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #10/19 start
2025-11-03 15:55:24 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #11/19 start
2025-11-03 15:55:26 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #12/19 start
2025-11-03 15:55:29 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #13/19 start
2025-11-03 15:55:31 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #14/19 start
2025-11-03 15:55:33 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #15/19 start
2025-11-03 15:55:36 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #16/19 start
2025-11-03 15:55:41 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #17/19 start
2025-11-03 15:55:44 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #18/19 start
2025-11-03 15:55:46 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, eval #19/19 start
2025-11-03 15:55:59 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, starting new job
2025-11-03 15:56:01 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, unknown 1 = ∑1/20, started new job
2025-11-03 15:56:03 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, pending 1 = ∑1/20, waiting for 1 job
2025-11-03 15:56:16 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 1 = ∑1/20, waiting for 1 job
2025-11-03 16:42:11 (21991ec7-24fc-46c4-9def-2d379a567e83): BOTORCH_MODULAR, failed: 1, best VAL_ACC: 71.62, running 1 = ∑1/20, new result: VAL_ACC: 71.350000
Arguments Overview
| Key | Value |
|---|
| config_yaml | None |
| config_toml | None |
| config_json | None |
| num_random_steps | 20 |
| max_eval | 1000 |
| run_program | [['cHl0aG9uMyAvZGF0YS9ob3JzZS93cy9zMzgxMTE0MS1vbW5pb3B0X21uaXN0X3Rlc3RfY2FsbC9vbW5pb3B0Ly50ZXN0cy9tbmlzdC90cmFpbiAtLWVwb2NocyAlZXBvY2hzIC0tbGVhcm5pbmdf… |
| experiment_name | mnist_mono |
| mem_gb | 40 |
| parameter | [['epochs', 'range', '20', '500', 'int', 'false'], ['lr', 'range', '0.0001', '0.001', 'float', 'false'], ['batch_size', 'range', '64', '1024', 'int', |
| 'false'], ['hidden_size', 'range', '512', '4096', 'int', 'false'], ['dropout', 'range', '0', '0.5', 'float', 'false'], ['num_dense_layers', 'range', |
| '1', '2', 'int', 'false'], ['filter', 'range', '16', '128', 'int', 'false'], ['num_conv_layers', 'range', '5', '7', 'int', 'false']] |
| continue_previous_job | None |
| experiment_constraints | None |
| run_dir | runs |
| seed | None |
| verbose_tqdm | False |
| model | BOTORCH_MODULAR |
| gridsearch | False |
| occ | False |
| show_sixel_scatter | False |
| show_sixel_general | False |
| show_sixel_trial_index_result | False |
| follow | True |
| send_anonymized_usage_stats | True |
| ui_url | None |
| root_venv_dir | /home/s3811141 |
| exclude | None |
| main_process_gb | 20 |
| max_nr_of_zero_results | 50 |
| abbreviate_job_names | False |
| orchestrator_file | None |
| checkout_to_latest_tested_version | False |
| live_share | True |
| disable_tqdm | False |
| disable_previous_job_constraint | False |
| workdir | |
| occ_type | euclid |
| result_names | ['VAL_ACC=max'] |
| minkowski_p | 2 |
| signed_weighted_euclidean_weights | |
| generation_strategy | None |
| generate_all_jobs_at_once | True |
| revert_to_random_when_seemingly_exhausted | True |
| load_data_from_existing_jobs | [] |
| n_estimators_randomforest | 100 |
| max_attempts_for_generation | 20 |
| external_generator | None |
| username | None |
| max_failed_jobs | 0 |
| num_cpus_main_job | None |
| calculate_pareto_front_of_job | [] |
| show_generate_time_table | False |
| force_choice_for_ranges | False |
| max_abandoned_retrial | 20 |
| share_password | None |
| dryrun | False |
| db_url | None |
| run_program_once | cHl0aG9uMyAvZGF0YS9ob3JzZS93cy9zMzgxMTE0MS1vbW5pb3B0X21uaXN0X3Rlc3RfY2FsbC9vbW5pb3B0Ly50ZXN0cy9tbmlzdC90cmFpbiAtLWluc3RhbGw= |
| worker_generator_path | None |
| save_to_database | False |
| range_max_difference | 1000000 |
| skip_search | False |
| dont_warm_start_refitting | False |
| refit_on_cv | False |
| fit_out_of_design | False |
| fit_abandoned | False |
| dont_jit_compile | False |
| num_restarts | 20 |
| raw_samples | 1024 |
| max_num_of_parallel_sruns | 16 |
| no_transform_inputs | False |
| no_normalize_y | False |
| transforms | [] |
| number_of_generators | 1 |
| num_parallel_jobs | 20 |
| worker_timeout | 240 |
| slurm_use_srun | False |
| time | 2880 |
| partition | alpha |
| reservation | None |
| force_local_execution | False |
| slurm_signal_delay_s | 0 |
| nodes_per_job | 1 |
| cpus_per_task | 1 |
| account | None |
| gpus | 1 |
| dependency | None |
| run_mode | local |
| verbose | False |
| verbose_break_run_search_table | False |
| debug | False |
| flame_graph | False |
| memray | False |
| no_sleep | False |
| tests | False |
| show_worker_percentage_table_at_end | False |
| auto_exclude_defective_hosts | False |
| run_tests_that_fail_on_taurus | False |
| raise_in_eval | False |
| show_ram_every_n_seconds | 0 |
| show_generation_and_submission_sixel | False |
| just_return_defaults | False |
| prettyprint | False |
| runtime_debug | False |
| debug_stack_regex | |
| debug_stack_trace_regex | None |
| show_func_name | False |
| beartype | False |
1762015276.7914,20,0,0
1762015303.5615,20,0,0
1762015304.0129,20,1,5
1762015304.9226,20,1,5
1762015308.8086,20,2,10
1762015308.9241,20,2,10
1762015318.8412,20,5,25
1762015318.9375,20,5,25
1762015328.8306,20,7,35
1762015328.9022,20,7,35
1762015333.8372,20,8,40
1762015333.8989,20,8,40
1762015339.267,20,9,45
1762015343.8935,20,9,45
1762015348.8475,20,11,55
1762015348.9097,20,11,55
1762015353.8511,20,12,60
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1762173699.8344,20,12,60
1762173704.1512,20,13,65
1762173704.8455,20,13,65
1762173709.1569,20,14,70
1762173709.8413,20,14,70
1762173714.1611,20,15,75
1762173715.9011,20,15,75
1762173719.1661,20,16,80
1762173719.8719,20,16,80
1762173729.1748,20,17,85
1762173729.8715,20,17,85
1762173734.1795,20,18,90
1762173734.8674,20,18,90
1762173739.1854,20,19,95
1762173739.8928,20,19,95
1762173749.1926,20,20,100
1762176585.984,20,20,100
1762176629.9727,20,18,90
1762176637.0496,20,18,90
1762176674.5925,20,16,80
1762176685.8193,20,16,80
1762176741.3863,20,14,70
1762176749.8702,20,14,70
1762176751.2375,20,13,65
1762176823.9107,20,13,65
1762176825.1815,20,12,60
1762176831.9599,20,12,60
1762176894.2217,20,9,45
1762176903.0422,20,9,45
1762176906.2602,20,8,40
1762176908.5693,20,8,40
1762176909.6044,20,7,35
1762178021.7113,20,7,35
1762178022.3682,20,6,30
1762180132.6386,20,6,30
1762180134.0636,20,5,25
1762180309.8272,20,5,25
1762180358.8419,20,4,20
1762180386.6043,20,4,20
1762180387.8639,20,3,15
1762180388.51,20,3,15
1762180429.7134,20,1,5
1762180572.4558,20,1,5
1762180611.8586,20,0,0
1762181756.789,20,0,0
1762181759.9821,20,1,5
1762184533.5728,20,1,5
1762184534.3245,20,0,0
This logs the CPU and RAM usage of the main worker process.
timestamp,ram_usage_mb,cpu_usage_percent
1762015276,810.29296875,11.7
1762015339,858.10546875,10.5
1762015399,851.94140625,12
1762015459,878.4453125,11.7
1762015519,889.453125,11.7
1762015579,889.97265625,12
1762015639,895.453125,12
1762015699,895.453125,12.1
1762015759,895.484375,12.2
1762015819,895.46484375,12.7
1762015879,895.48828125,12.5
1762015939,898.11328125,12.1
1762015999,898.140625,12
1762016059,898.1328125,11.9
1762016119,898.28125,12.1
1762016179,898.35546875,10.4
1762016239,898.39453125,10.6
1762016299,898.39453125,10.7
1762016359,898.39453125,10.3
1762016419,898.609375,10.5
1762016479,898.59765625,10.3
1762016540,898.58203125,10.2
1762016600,898.57421875,10.3
1762016660,898.609375,10.4
1762016720,898.6015625,10.2
1762016780,898.59765625,10.3
1762016840,898.9375,10.7
1762016900,898.9296875,10.4
1762016961,899.10546875,10.3
1762017021,899.08203125,10.4
1762017081,899.11328125,10.6
1762017141,899.0859375,10.4
1762017201,899.109375,10.4
1762017261,899.11328125,10.4
1762017321,899.109375,10.2
1762017381,899.109375,10.5
1762017441,899.1015625,10.6
1762017501,899.11328125,10.4
1762017561,899.0859375,10.3
1762017621,899.109375,10.3
1762017681,899.68359375,10.4
1762017741,899.73046875,10.2
1762017801,899.70703125,10.6
1762017861,899.87890625,10.3
1762017921,899.87890625,9.9
1762017981,899.87890625,10.2
1762018041,900.0625,10.3
1762018101,900.0625,10.1
1762018161,900.05859375,9.9
1762018221,900.046875,10.3
1762018281,900.046875,10.1
1762018341,900.05859375,10.1
1762018401,900.046875,10.2
1762018461,900.046875,10.5
1762018521,900.046875,10
1762018581,900.046875,10.1
1762018641,900.0625,10.4
1762018701,900.07421875,10.6
1762018761,900.6484375,8.9
1762018821,900.6484375,9
1762018881,900.6484375,8.8
1762018941,900.6484375,9.1
1762019001,900.6484375,9
1762019061,900.6484375,8.9
1762019121,901.10546875,9.2
1762019181,901.1171875,9
1762019241,901.1171875,8.9
1762019301,901.265625,9
1762019361,901.265625,8.9
1762019421,901.265625,9
1762019481,901.265625,8.9
1762019541,901.265625,9
1762019601,901.265625,9
1762019661,901.265625,8.7
1762019721,901.265625,9.1
1762019781,901.265625,9.1
1762019841,901.765625,9.1
1762019901,901.765625,9
1762019961,901.765625,8.9
1762020021,901.765625,8.9
1762020081,901.765625,8.9
1762020141,901.765625,9.1
1762020201,901.765625,9
1762020261,901.765625,8.8
1762020321,901.765625,9.1
1762020381,901.765625,8.9
1762020441,901.765625,9.1
1762020501,901.765625,9.1
1762020561,901.765625,8.8
1762020621,901.765625,9
1762020681,901.765625,9.2
1762020741,901.765625,9.1
1762020802,901.765625,8.7
1762020862,901.765625,9.3
1762020922,901.765625,9
1762020982,901.765625,9.1
1762021042,902.265625,9
1762021102,919.38671875,9.6
1762021164,929.21484375,10.7
1762021224,929.1640625,12.3
1762021284,929.203125,12.2
1762021344,929.25390625,12.6
1762021404,929.30859375,12
1762021464,929.328125,12.3
1762021524,929.38671875,11.9
1762021584,929.43359375,12.2
1762021644,929.4609375,12.3
1762021704,929.546875,12.3
1762021764,929.54296875,12
1762021824,929.578125,12.2
1762021884,929.61328125,12.3
1762021944,929.65625,12.3
1762022004,929.6875,12.2
1762022064,929.7578125,12
1762022124,929.765625,12.2
1762022184,929.796875,12.3
1762022244,929.859375,12.1
1762022304,929.87109375,12
1762022364,929.94140625,12.2
1762022424,929.94140625,12.3
1762022484,930.0234375,12.2
1762022544,930.03515625,12.4
1762022604,930.078125,12.2
1762022664,930.09375,12.4
1762022724,930.1484375,12.6
1762022784,930.16796875,12.1
1762022844,930.203125,12.2
1762022904,930.26953125,12.1
1762022964,930.27734375,12.2
1762023024,930.34765625,12.2
1762023084,930.37890625,12.4
1762023144,930.390625,12.3
1762023204,930.421875,12.1
1762023264,930.45703125,12.2
1762023324,930.48828125,12.4
1762023384,930.53125,12.3
1762023444,930.5703125,12.2
1762023504,930.60546875,12.4
1762023564,930.640625,12.4
1762023624,930.71875,12.2
1762023684,930.73046875,12.2
1762023744,930.76953125,12.2
1762023804,930.8203125,12.4
1762023864,930.859375,12.1
1762023924,930.90625,12.1
1762023984,930.95703125,12.6
1762024044,931.01953125,12
1762024104,931.046875,11.8
1762024164,931.1171875,11.9
1762024224,931.171875,11.6
1762024284,931.21875,12.2
1762024344,931.2421875,11.8
1762024404,931.27734375,11.7
1762024464,931.31640625,11.5
1762024524,931.36328125,11.9
1762024584,931.4296875,11.8
1762024644,931.47265625,12
1762024704,931.51953125,11.6
1762024764,931.59375,11.6
1762024824,931.6171875,11.9
1762024884,931.66015625,11.9
1762024944,931.6953125,11.9
1762025004,931.75390625,11.8
1762025064,931.796875,11.8
1762025124,931.828125,11.7
1762025184,931.91796875,11.7
1762025244,931.92578125,12
1762025304,931.98046875,12
1762025364,934.08203125,11.8
1762025424,934.09375,11.8
1762025484,940.0078125,11.8
1762025544,940.06640625,11.8
1762025604,943.3359375,10.1
1762025665,945.5,9.4
1762025725,949.5,9.3
1762025789,961.44140625,10.8
1762025849,955.60546875,11.5
1762025909,955.609375,11.6
1762025969,955.60546875,12
1762026029,955.62890625,11.7
1762026089,955.6640625,11.6
1762026149,955.6875,11.4
1762026209,955.72265625,11.5
1762026269,955.7890625,11.4
1762026329,955.80078125,11.4
1762026389,955.86328125,11.4
1762026449,955.8984375,11.3
1762026509,955.9375,11.2
1762026569,955.94140625,11.1
1762026629,955.97265625,11.4
1762026689,956.00390625,11.1
1762026749,956.04296875,11.3
1762026809,956.08984375,11.1
1762026869,956.1015625,11.1
1762026929,956.15234375,11.1
1762026989,956.171875,11.3
1762027050,956.21875,11
1762027110,956.2890625,11.2
1762027170,954.40625,11.3
1762027230,954.4296875,11.3
1762027290,954.4765625,10.9
1762027350,954.546875,11.2
1762027410,954.578125,11
1762027470,954.58203125,11.1
1762027530,954.61328125,11.1
1762027590,954.6484375,10.6
1762027650,954.68359375,10.9
1762027710,954.72265625,10.8
1762027770,954.7578125,10.9
1762027830,954.7890625,10.8
1762027890,954.8203125,11
1762027950,954.859375,11
1762028010,954.89453125,11.1
1762028070,954.9375,10.6
1762028130,954.9609375,10.8
1762028190,955.0078125,10.8
1762028250,955.03125,10.8
1762028310,955.1171875,10.8
1762028370,955.1015625,10.9
1762028430,955.14453125,11.1
1762028490,955.1875,10.9
1762028550,955.23046875,10.8
1762028610,955.2421875,10.8
1762028670,955.328125,11.1
1762028730,955.34375,10.8
1762028790,955.39453125,10.5
1762028850,955.453125,10.8
1762028910,955.48828125,10.7
1762028970,955.53515625,10.6
1762029030,955.56640625,10.5
1762029090,955.62109375,10.8
1762029150,955.63671875,10.9
1762029210,955.69921875,10.8
1762029270,955.734375,11
1762029330,955.7734375,10.8
1762029390,955.82421875,10.7
1762029450,955.8515625,10.7
1762029510,955.8984375,10.6
1762029570,955.9609375,10.8
1762029630,956,10.7
1762029690,956.0390625,11.1
1762029750,956.078125,10.7
1762029810,956.140625,10.7
1762029870,956.1640625,11.2
1762029930,956.23828125,10.9
1762029990,957.65234375,11.4
1762030050,957.6171875,11.4
1762030110,962.37890625,11.5
1762030170,962.37890625,11.6
1762030230,962.37890625,11.5
1762030290,962.38671875,12.3
1762030350,962.3515625,11.8
1762030410,962.33203125,12.2
1762030470,962.3359375,12.2
1762030530,962.33203125,12.3
1762030590,962.3359375,12.2
1762030650,962.34765625,12.2
1762030710,962.34765625,11.9
1762030770,962.34765625,12.2
1762030830,962.3828125,12
1762030890,962.3515625,12.3
1762030950,962.33203125,12.4
1762031010,962.34765625,12.2
1762031070,962.3359375,12.4
1762031130,962.3515625,12.5
1762031190,962.3359375,12.6
1762031250,962.3515625,12.7
1762031310,962.359375,12.2
1762031370,962.359375,12.6
1762031430,962.35546875,12.4
1762031490,962.39453125,12.4
1762031550,962.35546875,12.5
1762031610,962.36328125,12.6
1762031670,962.3671875,12.5
1762031730,962.40625,12.5
1762031790,962.4375,12.6
1762031850,962.4765625,12.3
1762031910,962.5078125,12.5
1762031970,962.5703125,12.4
1762032030,962.5625,12.2
1762032090,962.625,12.3
1762032150,962.625,12.3
1762032210,962.68359375,12.8
1762032270,962.73046875,12.1
1762032330,964.05859375,12.5
1762032392,964.02734375,12.1
1762032452,964.03515625,12.3
1762032512,966.1953125,12.3
1762032572,966.19140625,12.5
1762032632,968.18359375,12.7
1762032692,968.1953125,12.3
1762032752,968.1953125,12.4
1762032812,968.1953125,12.6
1762032872,975.75390625,12.2
1762032932,975.7421875,12.4
1762032992,978.2734375,12.4
1762033052,978.2734375,12.6
1762033112,978.28125,12.2
1762033172,978.2734375,12.4
1762033232,978.30078125,12.3
1762033292,978.26953125,12.5
1762033352,978.28515625,12.7
1762033417,978.27734375,12.1
1762033477,978.27734375,12.2
1762033537,981.7265625,12.5
1762033597,981.73046875,12.5
1762033657,981.74609375,12.3
1762033720,983.8203125,12.9
1762033780,987.78515625,13
1762033842,993.78515625,11.6
1762033902,995.7890625,10.8
1762033963,995.7890625,9.9
1762034023,998.2890625,10.1
1762034086,1009.7265625,10.7
1762034146,1005.53515625,12.4
1762034206,1005.57421875,12.2
1762034266,1005.546875,12.3
1762034326,1005.53125,12.2
1762034386,1005.53125,12.3
1762034446,1005.53125,12.4
1762034506,1005.53125,12.8
1762034566,1005.53515625,12.4
1762034626,1005.56640625,12.2
1762034686,1005.53515625,12.3
1762034746,1005.52734375,12.1
1762034806,1005.56640625,12.5
1762034866,1005.53515625,12.2
1762034926,1005.51953125,12.4
1762034986,1005.53125,12.4
1762035046,1005.53125,12.3
1762035106,1005.53125,12.2
1762035166,1005.53125,12.3
1762035226,1005.53515625,12.4
1762035286,1005.5390625,12.2
1762035346,1005.53125,12.3
1762035406,1005.53125,12.3
1762035466,1005.53515625,12.5
1762035526,1005.53125,12.4
1762035586,1005.53515625,12.1
1762035646,1005.515625,12.3
1762035706,1005.53515625,12.1
1762035766,1005.53125,12.5
1762035826,1005.53515625,12.3
1762035886,1005.51953125,12.2
1762035946,1005.56640625,12.1
1762036006,1005.53125,12.2
1762036066,1005.53515625,12.7
1762036126,1005.53125,12.4
1762036186,1005.53125,12.4
1762036246,1005.515625,12.2
1762036306,1005.51953125,12.3
1762036366,1005.53125,12.4
1762036426,1005.53515625,12.4
1762036486,1005.53515625,12.4
1762036546,1005.53125,12.3
1762036606,1005.53515625,12.4
1762036666,1005.51953125,12.3
1762036726,1005.53125,12.1
1762036786,1005.53515625,12.3
1762036846,1005.53125,12
1762036906,1005.55859375,12.3
1762036966,1005.53125,11.9
1762037026,1009.00390625,11.8
1762037086,1008.9765625,12
1762037146,1008.98828125,11.9
1762037206,1008.9765625,11.7
1762037266,1009.015625,11.9
1762037326,1008.98828125,11.9
1762037386,1009.0078125,11.9
1762037446,1009.0078125,11.8
1762037506,1009.046875,11.8
1762037566,1009.078125,11.8
1762037626,1009.08984375,11.6
1762037686,1009.1328125,12
1762037746,1009.16015625,11.8
1762037806,1009.234375,11.7
1762037866,1009.265625,11.9
1762037926,1009.2890625,11.8
1762037986,1009.328125,12.1
1762038046,1009.30859375,12.1
1762038106,1009.35546875,12
1762038166,1009.37890625,11.6
1762038226,1009.41796875,11.8
1762038286,1009.44921875,11.7
1762038346,1009.484375,11.8
1762038406,1009.515625,11.8
1762038466,1009.58203125,11.9
1762038526,1009.58203125,11.9
1762038586,1009.63671875,12.1
1762038646,1009.62890625,12.1
1762038706,1009.703125,11.8
1762038766,1009.6875,11.9
1762038826,1009.7265625,11.9
1762038886,1009.76953125,12
1762038946,1009.7890625,12
1762039006,1009.82421875,12.1
1762039066,1009.84375,12
1762039126,1009.90625,11.9
1762039186,1009.93359375,11.8
1762039246,1009.953125,12.1
1762039306,1010.0078125,11.9
1762039366,1010.015625,12.1
1762039426,1010.01953125,12
1762039486,1010.09765625,11.9
1762039546,1010.08984375,12.2
1762039606,1010.11328125,12
1762039666,1010.16015625,11.8
1762039726,1010.1875,12
1762039786,1010.203125,12.1
1762039846,1010.25,11.9
1762039906,1010.296875,12
1762039966,1010.33984375,12
1762040026,1010.390625,12
1762040086,1010.4140625,12
1762040146,1010.40234375,11.8
1762040206,1010.43359375,12.1
1762040266,1010.46484375,12
1762040326,1012.4765625,12
1762040386,1012.5234375,12
1762040446,1012.54296875,11.9
1762040506,1012.578125,12.2
1762040566,1012.60546875,11.9
1762040626,1012.64453125,11.9
1762040686,1012.6796875,12
1762040746,1012.7578125,11.8
1762040806,1012.74609375,12.1
1762040866,1012.77734375,11.8
1762040926,1012.80859375,11.8
1762040986,1012.84375,11.9
1762041046,1012.86328125,12
1762041106,1012.96484375,12.1
1762041166,1013.9921875,12
1762041226,1014.5,12.1
1762041286,1015.5546875,12.1
1762041346,1015.5546875,12
1762041406,1015.5625,12.2
1762041466,1015.546875,12.3
1762041526,1015.546875,12
1762041586,1018.64453125,10.6
1762041647,1022.93359375,11.2
1762041707,1027.859375,10.2
1762041767,1029.859375,10
1762041827,1040.16015625,9
1762041887,1035.875,12.4
1762041947,1035.87109375,12.5
1762042007,1035.8671875,12.3
1762042067,1035.8828125,12.4
1762042127,1035.8828125,12.5
1762042187,1035.921875,12.6
1762042247,1035.8984375,12.3
1762042307,1035.9375,12.5
1762042367,1035.87109375,12.5
1762042427,1035.8984375,12.8
1762042487,1035.9140625,12.3
1762042547,1035.8984375,12.3
1762042607,1035.8671875,12.6
1762042667,1035.9140625,12.6
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1762164528,1167.66796875,12.6
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1762167223,1204.63671875,12.7
1762167402,1204.63671875,10.3
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1762168768,1153.109375,13
1762168828,1153.1171875,12.7
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1762169250,1153.265625,13
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1762169550,1153.24609375,12.8
1762169611,1153.2265625,13.2
1762169671,1153.25,13.1
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1762169791,1153.234375,13
1762169851,1153.265625,13
1762169911,1153.26171875,13.2
1762169971,1153.22265625,12.7
1762170039,1157.71484375,12.5
1762170099,1157.63671875,12.9
1762170159,1157.62890625,12.7
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1762170281,1164.83984375,13
1762170341,1164.90625,13.4
1762170419,1172.7109375,12.6
1762170538,1178.53125,12.6
1762170880,1214.72265625,12.6
1762171044,1212.53515625,12.6
1762171105,1212.53515625,12.9
1762171165,1212.53515625,12.9
1762171225,1212.53515625,12.9
1762171285,1212.53515625,12.5
1762171345,1212.53515625,13
1762171405,1212.53515625,13.3
1762171466,1212.53515625,13.1
1762171527,1212.53515625,13
1762171587,1212.53515625,12.8
1762171647,1212.53515625,12.9
1762171707,1212.53515625,13
1762171767,1212.53515625,13.2
1762171827,1212.53515625,13
1762171887,1212.53515625,12.7
1762171947,1212.53515625,12.9
1762172008,1212.53515625,12.9
1762172068,1212.53515625,12.9
1762172128,1212.53515625,12.9
1762172188,1212.53515625,13
1762172248,1212.53515625,12.9
1762172308,1212.53515625,13
1762172368,1212.53515625,13.1
1762172430,1212.53515625,12.4
1762172490,1212.53515625,12.3
1762172561,1212.53515625,12.2
1762172621,1212.53515625,12.6
1762172681,1212.53515625,12.6
1762172741,1212.53515625,12.7
1762172801,1212.53515625,12.9
1762172861,1212.53515625,12.7
1762172922,1212.53515625,12.7
1762172982,1212.53515625,12.5
1762173042,1212.53515625,12.6
1762173102,1212.53515625,12.6
1762173567,1212.87109375,13.2
1762173627,1214.37109375,13.1
1762173687,1163.953125,12.8
1762173749,1158.57421875,11.9
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1762173869,1154.28125,12.4
1762173929,1154.28515625,12.5
1762173989,1154.265625,12.2
1762174049,1154.265625,12.7
1762174110,1154.265625,12.5
1762174170,1159.9765625,12.2
1762174230,1160.01171875,12.4
1762174290,1159.97265625,12.5
1762174358,1160.0078125,11.8
1762174418,1160.0078125,12.4
1762174478,1159.9765625,12.3
1762174539,1160.01171875,12.4
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1762175140,1159.9921875,12.5
1762175200,1159.9765625,12.7
1762175260,1160.00390625,12.5
1762175320,1160,12.3
1762175380,1159.9765625,12.5
1762175441,1166.9765625,12.5
1762175502,1166.98046875,12.5
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1762176045,1188.00390625,12.1
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1762176630,1188.03515625,11.4
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1762177143,1213.984375,11.9
1762177203,1213.984375,12.1
1762177263,1213.984375,11.9
1762177323,1213.984375,12.1
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1762177443,1213.984375,12.2
1762177503,1213.984375,12.3
1762177563,1213.984375,12.1
1762177624,1213.984375,12.4
1762177684,1213.984375,12.2
1762177744,1213.984375,12.3
1762177805,1213.984375,12.5
1762177865,1213.984375,12.1
1762177925,1213.984375,12.4
1762177985,1213.984375,12.3
1762178064,1214.015625,11.9
1762178125,1213.984375,12.3
1762178186,1213.984375,12.4
1762178246,1213.984375,12.4
1762178306,1213.984375,12.7
1762178366,1213.984375,12.6
1762178426,1213.984375,12.4
1762178486,1213.984375,12.4
1762178547,1213.984375,12.9
1762178607,1213.984375,12.7
1762178667,1213.984375,12.7
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1762178787,1213.984375,12.8
1762178847,1213.984375,13
1762178907,1213.984375,13
1762178967,1213.984375,12.8
1762179027,1213.984375,13.2
1762179087,1213.984375,13
1762179147,1213.984375,12.7
1762179207,1213.984375,13.1
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1762179390,1213.984375,12.5
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1762179810,1213.984375,13.2
1762179870,1213.984375,12.9
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1762182180,1251.91796875,13.1
1762182240,1251.91796875,13
1762182300,1251.91796875,13.1
1762182360,1251.91796875,13
1762182420,1251.91796875,13.5
1762182480,1251.91796875,13
1762182540,1251.91796875,13
1762182600,1251.91796875,13.1
1762182660,1251.91796875,13.3
1762182720,1251.91796875,13
1762182780,1251.91796875,13
1762182840,1251.91796875,13
1762182901,1251.91796875,13.3
1762182961,1251.91796875,13.2
1762183021,1251.91796875,13
1762183081,1251.91796875,12.9
1762183142,1251.91796875,13.2
1762183202,1251.91796875,12.9
1762183263,1251.91796875,13
1762183324,1251.91796875,12.9
1762183384,1251.91796875,12.9
1762183444,1251.91796875,13.2
1762183504,1251.91796875,12.7
1762183565,1251.91796875,12.6
1762183625,1251.91796875,12.9
1762183685,1251.91796875,13
1762183746,1251.91796875,12.9
1762183806,1251.91796875,12.6
1762183867,1251.91796875,12.1
1762183927,1251.91796875,12.7
1762183987,1251.91796875,12.5
1762184047,1251.91796875,12.8
1762184107,1251.91796875,12.5
1762184167,1251.91796875,12.6
1762184227,1251.91796875,12.5
1762184287,1251.91796875,12.4
1762184347,1251.91796875,12.7
1762184407,1251.91796875,12.6
1762184467,1251.91796875,12.7
1762184527,1251.91796875,12.7
VAL_ACC (goal: maximize)
Best value: 71.62
Achieved at:
- run_time = 1649
- epochs = 107
- lr = 0.00092662737615436
- batch_size = 64
- hidden_size = 2768
- dropout = 0.5
- num_dense_layers = 1
- filter = 128
- num_conv_layers = 5
Parameter statistics
| Parameter | Min | Max | Mean | Std Dev | Count |
|---|
| run_time | 231 | 8652 | 4793.5036 | 2707.1979 | 421 |
| VAL_ACC | 45.6 | 71.62 | 68.3457 | 4.1271 | 421 |
| epochs | 20 | 500 | 329.4545 | 176.3157 | 440 |
| lr | 0.0001 | 0.001 | 0.0008 | 0.0002 | 440 |
| batch_size | 64 | 1024 | 140.2682 | 217.7528 | 440 |
| hidden_size | 512 | 4096 | 3246.9977 | 1028.4565 | 440 |
| dropout | 0 | 0.5 | 0.3947 | 0.148 | 440 |
| num_dense_layers | 1 | 2 | 1.275 | 0.4465 | 440 |
| filter | 22 | 128 | 121.4432 | 16.4658 | 440 |
| num_conv_layers | 5 | 7 | 5.4659 | 0.6422 | 440 |
Show SLURM-Job-ID (if it exists)
submitit INFO (2025-11-01 17:41:54,551) - Starting with JobEnvironment(job_id=1207670, hostname=c143, local_rank=0(1), node=0(1), global_rank=0(1))
submitit INFO (2025-11-01 17:41:54,553) - Loading pickle: /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/runs/mnist_mono/4/single_runs/1207670/1207670_submitted.pkl
Trial-Index: 5
/data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/.torch_venv_1bdd5e1e8b/lib64/python3.9/site-packages/torch/utils/data/dataloader.py:627: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 1, which is smaller than what this DataLoader is going to create. Please be aware that excessive worker creation might get DataLoader running slow or even freeze, lower the worker number to avoid potential slowness/freeze if necessary.
warnings.warn(
Parameters: {"epochs": 308, "lr": 0.0003280551039613784, "batch_size": 420, "hidden_size": 1235, "dropout": 0.07788012875244021, "num_dense_layers": 1, "filter": 94, "num_conv_layers": 7}
Debug-Infos:
========
DEBUG INFOS START:
Program-Code: python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 308 --learning_rate 0.00032805510396137841 --batch_size 420 --hidden_size 1235 --dropout 0.07788012875244021416 --num_dense_layers 1 --filter 94 --num_conv_layers 7
pwd: /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt
File: /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train
UID: 2105408
GID: 200270
SLURM_JOB_ID: 1207670
Status-Change-Time: 1761910410.0
Size: 19255 Bytes
Permissions: -rwxr-xr-x
Owner: s3811141
Last access: 1762015267.0
Last modification: 1761906808.0
Hostname: c143
========
DEBUG INFOS END
python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 308 --learning_rate 0.00032805510396137841 --batch_size 420 --hidden_size 1235 --dropout 0.07788012875244021416 --num_dense_layers 1 --filter 94 --num_conv_layers 7
stdout:
Hyperparameters
╭──────────────────┬───────────────────────╮
│ Parameter │ Value │
├──────────────────┼───────────────────────┤
│ Epochs │ 308 │
│ Num Dense Layers │ 1 │
│ Batch size │ 420 │
│ Learning rate │ 0.0003280551039613784 │
│ Hidden size │ 1235 │
│ Dropout │ 0.07788012875244021 │
│ Optimizer │ adam │
│ Momentum │ 0.9 │
│ Weight Decay │ 0.0001 │
│ Activation │ relu │
│ Init Method │ kaiming │
│ Seed │ None │
│ Conv Filters │ 94 │
│ Num Conv Layers │ 7 │
│ Conv Kernel │ 3 │
│ Conv Stride │ 1 │
│ Conv Padding │ 1 │
╰──────────────────┴───────────────────────╯
Model Summary
╭─────────────────┬─────────────────┬─────────╮
│ Layer │ Output Shape │ Param # │
├─────────────────┼─────────────────┼─────────┤
│ conv::conv0 │ [1, 94, 32, 32] │ 2632 │
│ conv::bn0 │ [1, 94, 32, 32] │ 188 │
│ conv::act_conv0 │ [1, 94, 32, 32] │ 0 │
│ conv::conv1 │ [1, 94, 32, 32] │ 79618 │
│ conv::bn1 │ [1, 94, 32, 32] │ 188 │
│ conv::act_conv1 │ [1, 94, 32, 32] │ 0 │
│ conv::pool1 │ [1, 94, 16, 16] │ 0 │
│ conv::conv2 │ [1, 94, 16, 16] │ 79618 │
│ conv::bn2 │ [1, 94, 16, 16] │ 188 │
│ conv::act_conv2 │ [1, 94, 16, 16] │ 0 │
│ conv::conv3 │ [1, 94, 16, 16] │ 79618 │
│ conv::bn3 │ [1, 94, 16, 16] │ 188 │
│ conv::act_conv3 │ [1, 94, 16, 16] │ 0 │
│ conv::pool2 │ [1, 94, 8, 8] │ 0 │
│ conv::conv4 │ [1, 94, 8, 8] │ 79618 │
│ conv::bn4 │ [1, 94, 8, 8] │ 188 │
│ conv::act_conv4 │ [1, 94, 8, 8] │ 0 │
│ conv::conv5 │ [1, 94, 8, 8] │ 79618 │
│ conv::bn5 │ [1, 94, 8, 8] │ 188 │
│ conv::act_conv5 │ [1, 94, 8, 8] │ 0 │
│ conv::pool3 │ [1, 94, 4, 4] │ 0 │
│ conv::conv6 │ [1, 94, 4, 4] │ 79618 │
│ conv::bn6 │ [1, 94, 4, 4] │ 188 │
│ conv::act_conv6 │ [1, 94, 4, 4] │ 0 │
│ dense::fc0 │ [1, 1235] │ 1858675 │
│ dense::act0 │ [1, 1235] │ 0 │
│ dense::dropout0 │ [1, 1235] │ 0 │
│ dense::output │ [1, 100] │ 123600 │
│ Total │ - │ 2463931 │
╰─────────────────┴─────────────────┴─────────╯
──────────────────────────── Epoch 1/308 - Training ────────────────────────────
Epoch-Loss: 463.0276
─────────────────────────── Epoch 1/308 - Validation ───────────────────────────
╔══ Epoch 1/308 Summary ══╗
║ Validation Loss: 3.3496 ║
║ Accuracy: 19.70% ║
╚═════════════════════════╝
──────────────────────────── Epoch 2/308 - Training ────────────────────────────
Epoch-Loss: 388.9774
─────────────────────────── Epoch 2/308 - Validation ───────────────────────────
╔══ Epoch 2/308 Summary ══╗
║ Validation Loss: 2.9655 ║
║ Accuracy: 26.62% ║
╚═════════════════════════╝
──────────────────────────── Epoch 3/308 - Training ────────────────────────────
Epoch-Loss: 353.4956
─────────────────────────── Epoch 3/308 - Validation ───────────────────────────
╔══ Epoch 3/308 Summary ══╗
║ Validation Loss: 2.8374 ║
║ Accuracy: 28.86% ║
╚═════════════════════════╝
──────────────────────────── Epoch 4/308 - Training ────────────────────────────
Epoch-Loss: 324.8150
─────────────────────────── Epoch 4/308 - Validation ───────────────────────────
╔══ Epoch 4/308 Summary ══╗
║ Validation Loss: 2.6782 ║
║ Accuracy: 32.27% ║
╚═════════════════════════╝
──────────────────────────── Epoch 5/308 - Training ────────────────────────────
Epoch-Loss: 300.5330
─────────────────────────── Epoch 5/308 - Validation ───────────────────────────
╔══ Epoch 5/308 Summary ══╗
║ Validation Loss: 2.4115 ║
║ Accuracy: 38.04% ║
╚═════════════════════════╝
──────────────────────────── Epoch 6/308 - Training ────────────────────────────
Epoch-Loss: 281.5757
─────────────────────────── Epoch 6/308 - Validation ───────────────────────────
╔══ Epoch 6/308 Summary ══╗
║ Validation Loss: 2.4777 ║
║ Accuracy: 37.02% ║
╚═════════════════════════╝
──────────────────────────── Epoch 7/308 - Training ────────────────────────────
Epoch-Loss: 263.9901
─────────────────────────── Epoch 7/308 - Validation ───────────────────────────
╔══ Epoch 7/308 Summary ══╗
║ Validation Loss: 2.2457 ║
║ Accuracy: 41.41% ║
╚═════════════════════════╝
──────────────────────────── Epoch 8/308 - Training ────────────────────────────
Epoch-Loss: 253.9995
─────────────────────────── Epoch 8/308 - Validation ───────────────────────────
╔══ Epoch 8/308 Summary ══╗
║ Validation Loss: 2.1198 ║
║ Accuracy: 44.29% ║
╚═════════════════════════╝
──────────────────────────── Epoch 9/308 - Training ────────────────────────────
Epoch-Loss: 240.7118
─────────────────────────── Epoch 9/308 - Validation ───────────────────────────
╔══ Epoch 9/308 Summary ══╗
║ Validation Loss: 2.0626 ║
║ Accuracy: 45.43% ║
╚═════════════════════════╝
─────────────────────────── Epoch 10/308 - Training ────────────────────────────
Epoch-Loss: 229.5698
────────────────────────── Epoch 10/308 - Validation ───────────────────────────
╔═ Epoch 10/308 Summary ══╗
║ Validation Loss: 2.0400 ║
║ Accuracy: 46.53% ║
╚═════════════════════════╝
─────────────────────────── Epoch 11/308 - Training ────────────────────────────
Epoch-Loss: 220.3836
────────────────────────── Epoch 11/308 - Validation ───────────────────────────
╔═ Epoch 11/308 Summary ══╗
║ Validation Loss: 2.0049 ║
║ Accuracy: 47.13% ║
╚═════════════════════════╝
─────────────────────────── Epoch 12/308 - Training ────────────────────────────
Epoch-Loss: 211.9424
────────────────────────── Epoch 12/308 - Validation ───────────────────────────
╔═ Epoch 12/308 Summary ══╗
║ Validation Loss: 1.9458 ║
║ Accuracy: 48.68% ║
╚═════════════════════════╝
─────────────────────────── Epoch 13/308 - Training ────────────────────────────
Epoch-Loss: 203.1366
────────────────────────── Epoch 13/308 - Validation ───────────────────────────
╔═ Epoch 13/308 Summary ══╗
║ Validation Loss: 1.8725 ║
║ Accuracy: 49.99% ║
╚═════════════════════════╝
─────────────────────────── Epoch 14/308 - Training ────────────────────────────
Epoch-Loss: 197.0838
────────────────────────── Epoch 14/308 - Validation ───────────────────────────
╔═ Epoch 14/308 Summary ══╗
║ Validation Loss: 1.9167 ║
║ Accuracy: 49.68% ║
╚═════════════════════════╝
─────────────────────────── Epoch 15/308 - Training ────────────────────────────
Epoch-Loss: 190.2073
────────────────────────── Epoch 15/308 - Validation ───────────────────────────
╔═ Epoch 15/308 Summary ══╗
║ Validation Loss: 1.8378 ║
║ Accuracy: 50.48% ║
╚═════════════════════════╝
─────────────────────────── Epoch 16/308 - Training ────────────────────────────
Epoch-Loss: 182.4973
────────────────────────── Epoch 16/308 - Validation ───────────────────────────
╔═ Epoch 16/308 Summary ══╗
║ Validation Loss: 1.8236 ║
║ Accuracy: 51.10% ║
╚═════════════════════════╝
─────────────────────────── Epoch 17/308 - Training ────────────────────────────
Epoch-Loss: 175.7168
────────────────────────── Epoch 17/308 - Validation ───────────────────────────
╔═ Epoch 17/308 Summary ══╗
║ Validation Loss: 1.8210 ║
║ Accuracy: 51.69% ║
╚═════════════════════════╝
─────────────────────────── Epoch 18/308 - Training ────────────────────────────
Epoch-Loss: 171.0432
────────────────────────── Epoch 18/308 - Validation ───────────────────────────
╔═ Epoch 18/308 Summary ══╗
║ Validation Loss: 1.8601 ║
║ Accuracy: 51.44% ║
╚═════════════════════════╝
─────────────────────────── Epoch 19/308 - Training ────────────────────────────
Epoch-Loss: 165.5555
────────────────────────── Epoch 19/308 - Validation ───────────────────────────
╔═ Epoch 19/308 Summary ══╗
║ Validation Loss: 1.8098 ║
║ Accuracy: 52.03% ║
╚═════════════════════════╝
─────────────────────────── Epoch 20/308 - Training ────────────────────────────
Epoch-Loss: 160.7432
────────────────────────── Epoch 20/308 - Validation ───────────────────────────
╔═ Epoch 20/308 Summary ══╗
║ Validation Loss: 1.7799 ║
║ Accuracy: 52.61% ║
╚═════════════════════════╝
─────────────────────────── Epoch 21/308 - Training ────────────────────────────
Epoch-Loss: 154.1643
────────────────────────── Epoch 21/308 - Validation ───────────────────────────
╔═ Epoch 21/308 Summary ══╗
║ Validation Loss: 1.9685 ║
║ Accuracy: 49.42% ║
╚═════════════════════════╝
─────────────────────────── Epoch 22/308 - Training ────────────────────────────
Epoch-Loss: 150.3372
────────────────────────── Epoch 22/308 - Validation ───────────────────────────
╔═ Epoch 22/308 Summary ══╗
║ Validation Loss: 1.7679 ║
║ Accuracy: 52.96% ║
╚═════════════════════════╝
─────────────────────────── Epoch 23/308 - Training ────────────────────────────
Epoch-Loss: 143.6328
────────────────────────── Epoch 23/308 - Validation ───────────────────────────
╔═ Epoch 23/308 Summary ══╗
║ Validation Loss: 1.8269 ║
║ Accuracy: 52.75% ║
╚═════════════════════════╝
─────────────────────────── Epoch 24/308 - Training ────────────────────────────
Epoch-Loss: 139.5550
────────────────────────── Epoch 24/308 - Validation ───────────────────────────
╔═ Epoch 24/308 Summary ══╗
║ Validation Loss: 1.7377 ║
║ Accuracy: 54.55% ║
╚═════════════════════════╝
─────────────────────────── Epoch 25/308 - Training ────────────────────────────
Epoch-Loss: 135.8538
────────────────────────── Epoch 25/308 - Validation ───────────────────────────
╔═ Epoch 25/308 Summary ══╗
║ Validation Loss: 1.7988 ║
║ Accuracy: 53.25% ║
╚═════════════════════════╝
─────────────────────────── Epoch 26/308 - Training ────────────────────────────
Epoch-Loss: 130.7409
────────────────────────── Epoch 26/308 - Validation ───────────────────────────
╔═ Epoch 26/308 Summary ══╗
║ Validation Loss: 1.6927 ║
║ Accuracy: 55.26% ║
╚═════════════════════════╝
─────────────────────────── Epoch 27/308 - Training ────────────────────────────
Epoch-Loss: 126.7416
────────────────────────── Epoch 27/308 - Validation ───────────────────────────
╔═ Epoch 27/308 Summary ══╗
║ Validation Loss: 1.6818 ║
║ Accuracy: 55.92% ║
╚═════════════════════════╝
─────────────────────────── Epoch 28/308 - Training ────────────────────────────
Epoch-Loss: 123.0073
────────────────────────── Epoch 28/308 - Validation ───────────────────────────
╔═ Epoch 28/308 Summary ══╗
║ Validation Loss: 1.6691 ║
║ Accuracy: 56.04% ║
╚═════════════════════════╝
─────────────────────────── Epoch 29/308 - Training ────────────────────────────
Epoch-Loss: 118.2746
────────────────────────── Epoch 29/308 - Validation ───────────────────────────
╔═ Epoch 29/308 Summary ══╗
║ Validation Loss: 1.7504 ║
║ Accuracy: 54.58% ║
╚═════════════════════════╝
─────────────────────────── Epoch 30/308 - Training ────────────────────────────
Epoch-Loss: 116.1983
────────────────────────── Epoch 30/308 - Validation ───────────────────────────
╔═ Epoch 30/308 Summary ══╗
║ Validation Loss: 1.7062 ║
║ Accuracy: 55.76% ║
╚═════════════════════════╝
─────────────────────────── Epoch 31/308 - Training ────────────────────────────
Epoch-Loss: 98.1301
────────────────────────── Epoch 31/308 - Validation ───────────────────────────
╔═ Epoch 31/308 Summary ══╗
║ Validation Loss: 1.5840 ║
║ Accuracy: 58.25% ║
╚═════════════════════════╝
─────────────────────────── Epoch 32/308 - Training ────────────────────────────
Epoch-Loss: 93.1643
────────────────────────── Epoch 32/308 - Validation ───────────────────────────
╔═ Epoch 32/308 Summary ══╗
║ Validation Loss: 1.5790 ║
║ Accuracy: 58.49% ║
╚═════════════════════════╝
─────────────────────────── Epoch 33/308 - Training ────────────────────────────
Epoch-Loss: 91.7161
────────────────────────── Epoch 33/308 - Validation ───────────────────────────
╔═ Epoch 33/308 Summary ══╗
║ Validation Loss: 1.5788 ║
║ Accuracy: 58.58% ║
╚═════════════════════════╝
─────────────────────────── Epoch 34/308 - Training ────────────────────────────
Epoch-Loss: 90.3505
────────────────────────── Epoch 34/308 - Validation ───────────────────────────
╔═ Epoch 34/308 Summary ══╗
║ Validation Loss: 1.5752 ║
║ Accuracy: 58.51% ║
╚═════════════════════════╝
─────────────────────────── Epoch 35/308 - Training ────────────────────────────
Epoch-Loss: 89.4340
────────────────────────── Epoch 35/308 - Validation ───────────────────────────
╔═ Epoch 35/308 Summary ══╗
║ Validation Loss: 1.5836 ║
║ Accuracy: 58.36% ║
╚═════════════════════════╝
─────────────────────────── Epoch 36/308 - Training ────────────────────────────
Epoch-Loss: 88.5352
────────────────────────── Epoch 36/308 - Validation ───────────────────────────
╔═ Epoch 36/308 Summary ══╗
║ Validation Loss: 1.5764 ║
║ Accuracy: 58.56% ║
╚═════════════════════════╝
─────────────────────────── Epoch 37/308 - Training ────────────────────────────
Epoch-Loss: 87.9004
────────────────────────── Epoch 37/308 - Validation ───────────────────────────
╔═ Epoch 37/308 Summary ══╗
║ Validation Loss: 1.5834 ║
║ Accuracy: 58.46% ║
╚═════════════════════════╝
─────────────────────────── Epoch 38/308 - Training ────────────────────────────
Epoch-Loss: 86.9117
────────────────────────── Epoch 38/308 - Validation ───────────────────────────
╔═ Epoch 38/308 Summary ══╗
║ Validation Loss: 1.5872 ║
║ Accuracy: 58.56% ║
╚═════════════════════════╝
─────────────────────────── Epoch 39/308 - Training ────────────────────────────
Epoch-Loss: 86.6180
────────────────────────── Epoch 39/308 - Validation ───────────────────────────
╔═ Epoch 39/308 Summary ══╗
║ Validation Loss: 1.5821 ║
║ Accuracy: 58.43% ║
╚═════════════════════════╝
─────────────────────────── Epoch 40/308 - Training ────────────────────────────
Epoch-Loss: 85.8727
────────────────────────── Epoch 40/308 - Validation ───────────────────────────
╔═ Epoch 40/308 Summary ══╗
║ Validation Loss: 1.5782 ║
║ Accuracy: 58.53% ║
╚═════════════════════════╝
─────────────────────────── Epoch 41/308 - Training ────────────────────────────
Epoch-Loss: 85.7470
────────────────────────── Epoch 41/308 - Validation ───────────────────────────
╔═ Epoch 41/308 Summary ══╗
║ Validation Loss: 1.5837 ║
║ Accuracy: 58.58% ║
╚═════════════════════════╝
─────────────────────────── Epoch 42/308 - Training ────────────────────────────
Epoch-Loss: 85.5456
────────────────────────── Epoch 42/308 - Validation ───────────────────────────
╔═ Epoch 42/308 Summary ══╗
║ Validation Loss: 1.5786 ║
║ Accuracy: 58.84% ║
╚═════════════════════════╝
─────────────────────────── Epoch 43/308 - Training ────────────────────────────
Epoch-Loss: 84.3818
────────────────────────── Epoch 43/308 - Validation ───────────────────────────
╔═ Epoch 43/308 Summary ══╗
║ Validation Loss: 1.5826 ║
║ Accuracy: 58.49% ║
╚═════════════════════════╝
─────────────────────────── Epoch 44/308 - Training ────────────────────────────
Epoch-Loss: 84.5540
────────────────────────── Epoch 44/308 - Validation ───────────────────────────
╔═ Epoch 44/308 Summary ══╗
║ Validation Loss: 1.5763 ║
║ Accuracy: 58.59% ║
╚═════════════════════════╝
─────────────────────────── Epoch 45/308 - Training ────────────────────────────
Epoch-Loss: 83.1562
────────────────────────── Epoch 45/308 - Validation ───────────────────────────
╔═ Epoch 45/308 Summary ══╗
║ Validation Loss: 1.5786 ║
║ Accuracy: 58.63% ║
╚═════════════════════════╝
─────────────────────────── Epoch 46/308 - Training ────────────────────────────
Epoch-Loss: 82.5662
────────────────────────── Epoch 46/308 - Validation ───────────────────────────
╔═ Epoch 46/308 Summary ══╗
║ Validation Loss: 1.5757 ║
║ Accuracy: 58.75% ║
╚═════════════════════════╝
─────────────────────────── Epoch 47/308 - Training ────────────────────────────
Epoch-Loss: 82.2322
────────────────────────── Epoch 47/308 - Validation ───────────────────────────
╔═ Epoch 47/308 Summary ══╗
║ Validation Loss: 1.5883 ║
║ Accuracy: 58.70% ║
╚═════════════════════════╝
─────────────────────────── Epoch 48/308 - Training ────────────────────────────
Epoch-Loss: 81.3654
────────────────────────── Epoch 48/308 - Validation ───────────────────────────
╔═ Epoch 48/308 Summary ══╗
║ Validation Loss: 1.5779 ║
║ Accuracy: 58.85% ║
╚═════════════════════════╝
─────────────────────────── Epoch 49/308 - Training ────────────────────────────
Epoch-Loss: 81.1332
────────────────────────── Epoch 49/308 - Validation ───────────────────────────
╔═ Epoch 49/308 Summary ══╗
║ Validation Loss: 1.5816 ║
║ Accuracy: 58.78% ║
╚═════════════════════════╝
─────────────────────────── Epoch 50/308 - Training ────────────────────────────
Epoch-Loss: 80.6061
────────────────────────── Epoch 50/308 - Validation ───────────────────────────
╔═ Epoch 50/308 Summary ══╗
║ Validation Loss: 1.5832 ║
║ Accuracy: 58.81% ║
╚═════════════════════════╝
─────────────────────────── Epoch 51/308 - Training ────────────────────────────
Epoch-Loss: 79.6579
────────────────────────── Epoch 51/308 - Validation ───────────────────────────
╔═ Epoch 51/308 Summary ══╗
║ Validation Loss: 1.5819 ║
║ Accuracy: 58.79% ║
╚═════════════════════════╝
─────────────────────────── Epoch 52/308 - Training ────────────────────────────
Epoch-Loss: 78.9712
────────────────────────── Epoch 52/308 - Validation ───────────────────────────
╔═ Epoch 52/308 Summary ══╗
║ Validation Loss: 1.5877 ║
║ Accuracy: 58.45% ║
╚═════════════════════════╝
─────────────────────────── Epoch 53/308 - Training ────────────────────────────
Epoch-Loss: 78.3641
────────────────────────── Epoch 53/308 - Validation ───────────────────────────
╔═ Epoch 53/308 Summary ══╗
║ Validation Loss: 1.5783 ║
║ Accuracy: 58.93% ║
╚═════════════════════════╝
─────────────────────────── Epoch 54/308 - Training ────────────────────────────
Epoch-Loss: 78.2880
────────────────────────── Epoch 54/308 - Validation ───────────────────────────
╔═ Epoch 54/308 Summary ══╗
║ Validation Loss: 1.5867 ║
║ Accuracy: 58.82% ║
╚═════════════════════════╝
─────────────────────────── Epoch 55/308 - Training ────────────────────────────
Epoch-Loss: 77.3509
────────────────────────── Epoch 55/308 - Validation ───────────────────────────
╔═ Epoch 55/308 Summary ══╗
║ Validation Loss: 1.5834 ║
║ Accuracy: 58.66% ║
╚═════════════════════════╝
─────────────────────────── Epoch 56/308 - Training ────────────────────────────
Epoch-Loss: 77.4206
────────────────────────── Epoch 56/308 - Validation ───────────────────────────
╔═ Epoch 56/308 Summary ══╗
║ Validation Loss: 1.5869 ║
║ Accuracy: 58.61% ║
╚═════════════════════════╝
─────────────────────────── Epoch 57/308 - Training ────────────────────────────
Epoch-Loss: 76.8680
────────────────────────── Epoch 57/308 - Validation ───────────────────────────
╔═ Epoch 57/308 Summary ══╗
║ Validation Loss: 1.5799 ║
║ Accuracy: 58.90% ║
╚═════════════════════════╝
─────────────────────────── Epoch 58/308 - Training ────────────────────────────
Epoch-Loss: 76.1493
────────────────────────── Epoch 58/308 - Validation ───────────────────────────
╔═ Epoch 58/308 Summary ══╗
║ Validation Loss: 1.5871 ║
║ Accuracy: 58.77% ║
╚═════════════════════════╝
─────────────────────────── Epoch 59/308 - Training ────────────────────────────
Epoch-Loss: 76.7336
────────────────────────── Epoch 59/308 - Validation ───────────────────────────
╔═ Epoch 59/308 Summary ══╗
║ Validation Loss: 1.5841 ║
║ Accuracy: 59.01% ║
╚═════════════════════════╝
─────────────────────────── Epoch 60/308 - Training ────────────────────────────
Epoch-Loss: 75.9661
────────────────────────── Epoch 60/308 - Validation ───────────────────────────
╔═ Epoch 60/308 Summary ══╗
║ Validation Loss: 1.5917 ║
║ Accuracy: 58.52% ║
╚═════════════════════════╝
─────────────────────────── Epoch 61/308 - Training ────────────────────────────
Epoch-Loss: 74.0926
────────────────────────── Epoch 61/308 - Validation ───────────────────────────
╔═ Epoch 61/308 Summary ══╗
║ Validation Loss: 1.5819 ║
║ Accuracy: 58.79% ║
╚═════════════════════════╝
─────────────────────────── Epoch 62/308 - Training ────────────────────────────
Epoch-Loss: 73.9066
────────────────────────── Epoch 62/308 - Validation ───────────────────────────
╔═ Epoch 62/308 Summary ══╗
║ Validation Loss: 1.5791 ║
║ Accuracy: 58.75% ║
╚═════════════════════════╝
─────────────────────────── Epoch 63/308 - Training ────────────────────────────
Epoch-Loss: 73.1209
────────────────────────── Epoch 63/308 - Validation ───────────────────────────
╔═ Epoch 63/308 Summary ══╗
║ Validation Loss: 1.5833 ║
║ Accuracy: 58.91% ║
╚═════════════════════════╝
─────────────────────────── Epoch 64/308 - Training ────────────────────────────
Epoch-Loss: 73.6353
────────────────────────── Epoch 64/308 - Validation ───────────────────────────
╔═ Epoch 64/308 Summary ══╗
║ Validation Loss: 1.5799 ║
║ Accuracy: 58.92% ║
╚═════════════════════════╝
─────────────────────────── Epoch 65/308 - Training ────────────────────────────
Epoch-Loss: 72.5056
────────────────────────── Epoch 65/308 - Validation ───────────────────────────
╔═ Epoch 65/308 Summary ══╗
║ Validation Loss: 1.5780 ║
║ Accuracy: 58.97% ║
╚═════════════════════════╝
─────────────────────────── Epoch 66/308 - Training ────────────────────────────
Epoch-Loss: 72.4456
────────────────────────── Epoch 66/308 - Validation ───────────────────────────
╔═ Epoch 66/308 Summary ══╗
║ Validation Loss: 1.5781 ║
║ Accuracy: 59.00% ║
╚═════════════════════════╝
─────────────────────────── Epoch 67/308 - Training ────────────────────────────
Epoch-Loss: 72.5289
────────────────────────── Epoch 67/308 - Validation ───────────────────────────
╔═ Epoch 67/308 Summary ══╗
║ Validation Loss: 1.5810 ║
║ Accuracy: 58.88% ║
╚═════════════════════════╝
─────────────────────────── Epoch 68/308 - Training ────────────────────────────
Epoch-Loss: 72.8630
────────────────────────── Epoch 68/308 - Validation ───────────────────────────
╔═ Epoch 68/308 Summary ══╗
║ Validation Loss: 1.5776 ║
║ Accuracy: 58.96% ║
╚═════════════════════════╝
─────────────────────────── Epoch 69/308 - Training ────────────────────────────
Epoch-Loss: 73.5634
────────────────────────── Epoch 69/308 - Validation ───────────────────────────
╔═ Epoch 69/308 Summary ══╗
║ Validation Loss: 1.5796 ║
║ Accuracy: 59.02% ║
╚═════════════════════════╝
─────────────────────────── Epoch 70/308 - Training ────────────────────────────
Epoch-Loss: 72.6050
────────────────────────── Epoch 70/308 - Validation ───────────────────────────
╔═ Epoch 70/308 Summary ══╗
║ Validation Loss: 1.5768 ║
║ Accuracy: 59.01% ║
╚═════════════════════════╝
─────────────────────────── Epoch 71/308 - Training ────────────────────────────
Epoch-Loss: 73.0525
────────────────────────── Epoch 71/308 - Validation ───────────────────────────
╔═ Epoch 71/308 Summary ══╗
║ Validation Loss: 1.5802 ║
║ Accuracy: 58.90% ║
╚═════════════════════════╝
─────────────────────────── Epoch 72/308 - Training ────────────────────────────
Epoch-Loss: 72.6052
────────────────────────── Epoch 72/308 - Validation ───────────────────────────
╔═ Epoch 72/308 Summary ══╗
║ Validation Loss: 1.5757 ║
║ Accuracy: 59.09% ║
╚═════════════════════════╝
─────────────────────────── Epoch 73/308 - Training ────────────────────────────
Epoch-Loss: 72.5349
────────────────────────── Epoch 73/308 - Validation ───────────────────────────
╔═ Epoch 73/308 Summary ══╗
║ Validation Loss: 1.5785 ║
║ Accuracy: 59.01% ║
╚═════════════════════════╝
─────────────────────────── Epoch 74/308 - Training ────────────────────────────
Epoch-Loss: 72.4860
────────────────────────── Epoch 74/308 - Validation ───────────────────────────
╔═ Epoch 74/308 Summary ══╗
║ Validation Loss: 1.5803 ║
║ Accuracy: 59.17% ║
╚═════════════════════════╝
─────────────────────────── Epoch 75/308 - Training ────────────────────────────
Epoch-Loss: 72.9411
────────────────────────── Epoch 75/308 - Validation ───────────────────────────
╔═ Epoch 75/308 Summary ══╗
║ Validation Loss: 1.5802 ║
║ Accuracy: 59.01% ║
╚═════════════════════════╝
─────────────────────────── Epoch 76/308 - Training ────────────────────────────
Epoch-Loss: 72.2454
────────────────────────── Epoch 76/308 - Validation ───────────────────────────
╔═ Epoch 76/308 Summary ══╗
║ Validation Loss: 1.5804 ║
║ Accuracy: 58.98% ║
╚═════════════════════════╝
─────────────────────────── Epoch 77/308 - Training ────────────────────────────
Epoch-Loss: 71.9600
────────────────────────── Epoch 77/308 - Validation ───────────────────────────
╔═ Epoch 77/308 Summary ══╗
║ Validation Loss: 1.5755 ║
║ Accuracy: 58.91% ║
╚═════════════════════════╝
─────────────────────────── Epoch 78/308 - Training ────────────────────────────
Epoch-Loss: 72.2912
────────────────────────── Epoch 78/308 - Validation ───────────────────────────
╔═ Epoch 78/308 Summary ══╗
║ Validation Loss: 1.5835 ║
║ Accuracy: 58.94% ║
╚═════════════════════════╝
─────────────────────────── Epoch 79/308 - Training ────────────────────────────
Epoch-Loss: 72.1479
────────────────────────── Epoch 79/308 - Validation ───────────────────────────
╔═ Epoch 79/308 Summary ══╗
║ Validation Loss: 1.5785 ║
║ Accuracy: 59.09% ║
╚═════════════════════════╝
─────────────────────────── Epoch 80/308 - Training ────────────────────────────
Epoch-Loss: 72.0121
────────────────────────── Epoch 80/308 - Validation ───────────────────────────
╔═ Epoch 80/308 Summary ══╗
║ Validation Loss: 1.5820 ║
║ Accuracy: 59.06% ║
╚═════════════════════════╝
─────────────────────────── Epoch 81/308 - Training ────────────────────────────
Epoch-Loss: 72.3634
────────────────────────── Epoch 81/308 - Validation ───────────────────────────
╔═ Epoch 81/308 Summary ══╗
║ Validation Loss: 1.5801 ║
║ Accuracy: 58.98% ║
╚═════════════════════════╝
─────────────────────────── Epoch 82/308 - Training ────────────────────────────
Epoch-Loss: 72.4620
────────────────────────── Epoch 82/308 - Validation ───────────────────────────
╔═ Epoch 82/308 Summary ══╗
║ Validation Loss: 1.5862 ║
║ Accuracy: 59.06% ║
╚═════════════════════════╝
─────────────────────────── Epoch 83/308 - Training ────────────────────────────
Epoch-Loss: 71.9973
────────────────────────── Epoch 83/308 - Validation ───────────────────────────
╔═ Epoch 83/308 Summary ══╗
║ Validation Loss: 1.5803 ║
║ Accuracy: 58.96% ║
╚═════════════════════════╝
─────────────────────────── Epoch 84/308 - Training ────────────────────────────
Epoch-Loss: 71.6196
────────────────────────── Epoch 84/308 - Validation ───────────────────────────
╔═ Epoch 84/308 Summary ══╗
║ Validation Loss: 1.5773 ║
║ Accuracy: 59.03% ║
╚═════════════════════════╝
─────────────────────────── Epoch 85/308 - Training ────────────────────────────
Epoch-Loss: 72.1166
────────────────────────── Epoch 85/308 - Validation ───────────────────────────
╔═ Epoch 85/308 Summary ══╗
║ Validation Loss: 1.5799 ║
║ Accuracy: 59.13% ║
╚═════════════════════════╝
─────────────────────────── Epoch 86/308 - Training ────────────────────────────
Epoch-Loss: 71.6234
────────────────────────── Epoch 86/308 - Validation ───────────────────────────
╔═ Epoch 86/308 Summary ══╗
║ Validation Loss: 1.5796 ║
║ Accuracy: 58.97% ║
╚═════════════════════════╝
─────────────────────────── Epoch 87/308 - Training ────────────────────────────
Epoch-Loss: 72.0615
────────────────────────── Epoch 87/308 - Validation ───────────────────────────
╔═ Epoch 87/308 Summary ══╗
║ Validation Loss: 1.5791 ║
║ Accuracy: 59.10% ║
╚═════════════════════════╝
─────────────────────────── Epoch 88/308 - Training ────────────────────────────
Epoch-Loss: 72.2215
────────────────────────── Epoch 88/308 - Validation ───────────────────────────
╔═ Epoch 88/308 Summary ══╗
║ Validation Loss: 1.5808 ║
║ Accuracy: 58.98% ║
╚═════════════════════════╝
─────────────────────────── Epoch 89/308 - Training ────────────────────────────
Epoch-Loss: 71.9003
────────────────────────── Epoch 89/308 - Validation ───────────────────────────
╔═ Epoch 89/308 Summary ══╗
║ Validation Loss: 1.5802 ║
║ Accuracy: 59.05% ║
╚═════════════════════════╝
─────────────────────────── Epoch 90/308 - Training ────────────────────────────
Epoch-Loss: 71.6802
────────────────────────── Epoch 90/308 - Validation ───────────────────────────
╔═ Epoch 90/308 Summary ══╗
║ Validation Loss: 1.5809 ║
║ Accuracy: 59.02% ║
╚═════════════════════════╝
─────────────────────────── Epoch 91/308 - Training ────────────────────────────
Epoch-Loss: 71.2431
────────────────────────── Epoch 91/308 - Validation ───────────────────────────
╔═ Epoch 91/308 Summary ══╗
║ Validation Loss: 1.5797 ║
║ Accuracy: 59.24% ║
╚═════════════════════════╝
─────────────────────────── Epoch 92/308 - Training ────────────────────────────
Epoch-Loss: 71.1596
────────────────────────── Epoch 92/308 - Validation ───────────────────────────
╔═ Epoch 92/308 Summary ══╗
║ Validation Loss: 1.5804 ║
║ Accuracy: 59.09% ║
╚═════════════════════════╝
─────────────────────────── Epoch 93/308 - Training ────────────────────────────
Epoch-Loss: 71.2589
────────────────────────── Epoch 93/308 - Validation ───────────────────────────
╔═ Epoch 93/308 Summary ══╗
║ Validation Loss: 1.5807 ║
║ Accuracy: 58.93% ║
╚═════════════════════════╝
─────────────────────────── Epoch 94/308 - Training ────────────────────────────
Epoch-Loss: 71.2906
────────────────────────── Epoch 94/308 - Validation ───────────────────────────
╔═ Epoch 94/308 Summary ══╗
║ Validation Loss: 1.5777 ║
║ Accuracy: 59.10% ║
╚═════════════════════════╝
─────────────────────────── Epoch 95/308 - Training ────────────────────────────
Epoch-Loss: 71.6768
────────────────────────── Epoch 95/308 - Validation ───────────────────────────
╔═ Epoch 95/308 Summary ══╗
║ Validation Loss: 1.5783 ║
║ Accuracy: 59.18% ║
╚═════════════════════════╝
─────────────────────────── Epoch 96/308 - Training ────────────────────────────
Epoch-Loss: 71.2297
────────────────────────── Epoch 96/308 - Validation ───────────────────────────
╔═ Epoch 96/308 Summary ══╗
║ Validation Loss: 1.5811 ║
║ Accuracy: 58.98% ║
╚═════════════════════════╝
─────────────────────────── Epoch 97/308 - Training ────────────────────────────
Epoch-Loss: 71.1718
────────────────────────── Epoch 97/308 - Validation ───────────────────────────
╔═ Epoch 97/308 Summary ══╗
║ Validation Loss: 1.5787 ║
║ Accuracy: 59.02% ║
╚═════════════════════════╝
─────────────────────────── Epoch 98/308 - Training ────────────────────────────
Epoch-Loss: 71.3907
────────────────────────── Epoch 98/308 - Validation ───────────────────────────
╔═ Epoch 98/308 Summary ══╗
║ Validation Loss: 1.5781 ║
║ Accuracy: 59.07% ║
╚═════════════════════════╝
─────────────────────────── Epoch 99/308 - Training ────────────────────────────
Epoch-Loss: 71.4150
────────────────────────── Epoch 99/308 - Validation ───────────────────────────
╔═ Epoch 99/308 Summary ══╗
║ Validation Loss: 1.5798 ║
║ Accuracy: 59.05% ║
╚═════════════════════════╝
─────────────────────────── Epoch 100/308 - Training ───────────────────────────
Epoch-Loss: 71.2806
────────────────────────── Epoch 100/308 - Validation ──────────────────────────
╔═ Epoch 100/308 Summary ═╗
║ Validation Loss: 1.5824 ║
║ Accuracy: 59.09% ║
╚═════════════════════════╝
─────────────────────────── Epoch 101/308 - Training ───────────────────────────
Epoch-Loss: 71.5312
────────────────────────── Epoch 101/308 - Validation ──────────────────────────
╔═ Epoch 101/308 Summary ═╗
║ Validation Loss: 1.5815 ║
║ Accuracy: 59.04% ║
╚═════════════════════════╝
─────────────────────────── Epoch 102/308 - Training ───────────────────────────
Epoch-Loss: 71.3711
────────────────────────── Epoch 102/308 - Validation ──────────────────────────
╔═ Epoch 102/308 Summary ═╗
║ Validation Loss: 1.5791 ║
║ Accuracy: 59.01% ║
╚═════════════════════════╝
─────────────────────────── Epoch 103/308 - Training ───────────────────────────
Epoch-Loss: 71.0584
────────────────────────── Epoch 103/308 - Validation ──────────────────────────
╔═ Epoch 103/308 Summary ═╗
║ Validation Loss: 1.5839 ║
║ Accuracy: 58.97% ║
╚═════════════════════════╝
─────────────────────────── Epoch 104/308 - Training ───────────────────────────
Epoch-Loss: 71.5406
────────────────────────── Epoch 104/308 - Validation ──────────────────────────
╔═ Epoch 104/308 Summary ═╗
║ Validation Loss: 1.5797 ║
║ Accuracy: 59.03% ║
╚═════════════════════════╝
─────────────────────────── Epoch 105/308 - Training ───────────────────────────
Epoch-Loss: 71.3281
────────────────────────── Epoch 105/308 - Validation ──────────────────────────
╔═ Epoch 105/308 Summary ═╗
║ Validation Loss: 1.5853 ║
║ Accuracy: 59.06% ║
╚═════════════════════════╝
─────────────────────────── Epoch 106/308 - Training ───────────────────────────
Epoch-Loss: 70.8867
────────────────────────── Epoch 106/308 - Validation ──────────────────────────
╔═ Epoch 106/308 Summary ═╗
║ Validation Loss: 1.5776 ║
║ Accuracy: 58.99% ║
╚═════════════════════════╝
─────────────────────────── Epoch 107/308 - Training ───────────────────────────
Epoch-Loss: 71.0895
────────────────────────── Epoch 107/308 - Validation ──────────────────────────
╔═ Epoch 107/308 Summary ═╗
║ Validation Loss: 1.5794 ║
║ Accuracy: 59.09% ║
╚═════════════════════════╝
─────────────────────────── Epoch 108/308 - Training ───────────────────────────
Epoch-Loss: 70.8935
────────────────────────── Epoch 108/308 - Validation ──────────────────────────
╔═ Epoch 108/308 Summary ═╗
║ Validation Loss: 1.5802 ║
║ Accuracy: 58.97% ║
╚═════════════════════════╝
─────────────────────────── Epoch 109/308 - Training ───────────────────────────
Epoch-Loss: 71.6108
────────────────────────── Epoch 109/308 - Validation ──────────────────────────
╔═ Epoch 109/308 Summary ═╗
║ Validation Loss: 1.5791 ║
║ Accuracy: 59.03% ║
╚═════════════════════════╝
─────────────────────────── Epoch 110/308 - Training ───────────────────────────
Epoch-Loss: 70.9431
────────────────────────── Epoch 110/308 - Validation ──────────────────────────
╔═ Epoch 110/308 Summary ═╗
║ Validation Loss: 1.5814 ║
║ Accuracy: 59.11% ║
╚═════════════════════════╝
─────────────────────────── Epoch 111/308 - Training ───────────────────────────
Epoch-Loss: 71.1434
────────────────────────── Epoch 111/308 - Validation ──────────────────────────
╔═ Epoch 111/308 Summary ═╗
║ Validation Loss: 1.5795 ║
║ Accuracy: 59.15% ║
╚═════════════════════════╝
─────────────────────────── Epoch 112/308 - Training ───────────────────────────
Epoch-Loss: 71.4372
────────────────────────── Epoch 112/308 - Validation ──────────────────────────
╔═ Epoch 112/308 Summary ═╗
║ Validation Loss: 1.5783 ║
║ Accuracy: 59.21% ║
╚═════════════════════════╝
─────────────────────────── Epoch 113/308 - Training ───────────────────────────
Epoch-Loss: 71.3692
────────────────────────── Epoch 113/308 - Validation ──────────────────────────
╔═ Epoch 113/308 Summary ═╗
║ Validation Loss: 1.5830 ║
║ Accuracy: 58.95% ║
╚═════════════════════════╝
─────────────────────────── Epoch 114/308 - Training ───────────────────────────
Epoch-Loss: 71.5503
────────────────────────── Epoch 114/308 - Validation ──────────────────────────
╔═ Epoch 114/308 Summary ═╗
║ Validation Loss: 1.5840 ║
║ Accuracy: 59.08% ║
╚═════════════════════════╝
─────────────────────────── Epoch 115/308 - Training ───────────────────────────
Epoch-Loss: 71.3128
────────────────────────── Epoch 115/308 - Validation ──────────────────────────
╔═ Epoch 115/308 Summary ═╗
║ Validation Loss: 1.5826 ║
║ Accuracy: 58.95% ║
╚═════════════════════════╝
─────────────────────────── Epoch 116/308 - Training ───────────────────────────
Epoch-Loss: 70.8776
────────────────────────── Epoch 116/308 - Validation ──────────────────────────
╔═ Epoch 116/308 Summary ═╗
║ Validation Loss: 1.5821 ║
║ Accuracy: 59.07% ║
╚═════════════════════════╝
─────────────────────────── Epoch 117/308 - Training ───────────────────────────
Epoch-Loss: 70.7717
────────────────────────── Epoch 117/308 - Validation ──────────────────────────
╔═ Epoch 117/308 Summary ═╗
║ Validation Loss: 1.5804 ║
║ Accuracy: 59.17% ║
╚═════════════════════════╝
─────────────────────────── Epoch 118/308 - Training ───────────────────────────
Epoch-Loss: 71.8068
────────────────────────── Epoch 118/308 - Validation ──────────────────────────
╔═ Epoch 118/308 Summary ═╗
║ Validation Loss: 1.5836 ║
║ Accuracy: 59.00% ║
╚═════════════════════════╝
─────────────────────────── Epoch 119/308 - Training ───────────────────────────
Epoch-Loss: 71.7520
────────────────────────── Epoch 119/308 - Validation ──────────────────────────
╔═ Epoch 119/308 Summary ═╗
║ Validation Loss: 1.5828 ║
║ Accuracy: 59.19% ║
╚═════════════════════════╝
─────────────────────────── Epoch 120/308 - Training ───────────────────────────
Epoch-Loss: 71.1333
────────────────────────── Epoch 120/308 - Validation ──────────────────────────
╔═ Epoch 120/308 Summary ═╗
║ Validation Loss: 1.5824 ║
║ Accuracy: 59.04% ║
╚═════════════════════════╝
─────────────────────────── Epoch 121/308 - Training ───────────────────────────
Epoch-Loss: 71.3162
────────────────────────── Epoch 121/308 - Validation ──────────────────────────
╔═ Epoch 121/308 Summary ═╗
║ Validation Loss: 1.5803 ║
║ Accuracy: 59.02% ║
╚═════════════════════════╝
─────────────────────────── Epoch 122/308 - Training ───────────────────────────
Epoch-Loss: 71.3393
────────────────────────── Epoch 122/308 - Validation ──────────────────────────
╔═ Epoch 122/308 Summary ═╗
║ Validation Loss: 1.5782 ║
║ Accuracy: 59.08% ║
╚═════════════════════════╝
─────────────────────────── Epoch 123/308 - Training ───────────────────────────
Epoch-Loss: 71.5875
────────────────────────── Epoch 123/308 - Validation ──────────────────────────
╔═ Epoch 123/308 Summary ═╗
║ Validation Loss: 1.5789 ║
║ Accuracy: 59.12% ║
╚═════════════════════════╝
─────────────────────────── Epoch 124/308 - Training ───────────────────────────
Epoch-Loss: 71.8878
────────────────────────── Epoch 124/308 - Validation ──────────────────────────
╔═ Epoch 124/308 Summary ═╗
║ Validation Loss: 1.5817 ║
║ Accuracy: 59.06% ║
╚═════════════════════════╝
─────────────────────────── Epoch 125/308 - Training ───────────────────────────
Epoch-Loss: 71.1822
────────────────────────── Epoch 125/308 - Validation ──────────────────────────
╔═ Epoch 125/308 Summary ═╗
║ Validation Loss: 1.5787 ║
║ Accuracy: 59.24% ║
╚═════════════════════════╝
─────────────────────────── Epoch 126/308 - Training ───────────────────────────
Epoch-Loss: 71.1995
────────────────────────── Epoch 126/308 - Validation ──────────────────────────
╔═ Epoch 126/308 Summary ═╗
║ Validation Loss: 1.5794 ║
║ Accuracy: 59.04% ║
╚═════════════════════════╝
─────────────────────────── Epoch 127/308 - Training ───────────────────────────
Epoch-Loss: 71.4148
────────────────────────── Epoch 127/308 - Validation ──────────────────────────
╔═ Epoch 127/308 Summary ═╗
║ Validation Loss: 1.5823 ║
║ Accuracy: 59.07% ║
╚═════════════════════════╝
─────────────────────────── Epoch 128/308 - Training ───────────────────────────
Epoch-Loss: 71.9481
────────────────────────── Epoch 128/308 - Validation ──────────────────────────
╔═ Epoch 128/308 Summary ═╗
║ Validation Loss: 1.5818 ║
║ Accuracy: 59.09% ║
╚═════════════════════════╝
─────────────────────────── Epoch 129/308 - Training ───────────────────────────
Epoch-Loss: 71.6453
────────────────────────── Epoch 129/308 - Validation ──────────────────────────
╔═ Epoch 129/308 Summary ═╗
║ Validation Loss: 1.5797 ║
║ Accuracy: 59.04% ║
╚═════════════════════════╝
─────────────────────────── Epoch 130/308 - Training ───────────────────────────
Epoch-Loss: 71.5795
────────────────────────── Epoch 130/308 - Validation ──────────────────────────
╔═ Epoch 130/308 Summary ═╗
║ Validation Loss: 1.5844 ║
║ Accuracy: 59.04% ║
╚═════════════════════════╝
─────────────────────────── Epoch 131/308 - Training ───────────────────────────
Epoch-Loss: 70.5692
────────────────────────── Epoch 131/308 - Validation ──────────────────────────
╔═ Epoch 131/308 Summary ═╗
║ Validation Loss: 1.5795 ║
║ Accuracy: 59.16% ║
╚═════════════════════════╝
─────────────────────────── Epoch 132/308 - Training ───────────────────────────
Epoch-Loss: 70.9931
────────────────────────── Epoch 132/308 - Validation ──────────────────────────
╔═ Epoch 132/308 Summary ═╗
║ Validation Loss: 1.5798 ║
║ Accuracy: 59.08% ║
╚═════════════════════════╝
─────────────────────────── Epoch 133/308 - Training ───────────────────────────
Epoch-Loss: 70.8487
────────────────────────── Epoch 133/308 - Validation ──────────────────────────
╔═ Epoch 133/308 Summary ═╗
║ Validation Loss: 1.5807 ║
║ Accuracy: 59.09% ║
╚═════════════════════════╝
─────────────────────────── Epoch 134/308 - Training ───────────────────────────
Epoch-Loss: 71.0803
────────────────────────── Epoch 134/308 - Validation ──────────────────────────
╔═ Epoch 134/308 Summary ═╗
║ Validation Loss: 1.5790 ║
║ Accuracy: 59.03% ║
╚═════════════════════════╝
─────────────────────────── Epoch 135/308 - Training ───────────────────────────
Epoch-Loss: 71.1399
────────────────────────── Epoch 135/308 - Validation ──────────────────────────
╔═ Epoch 135/308 Summary ═╗
║ Validation Loss: 1.5820 ║
║ Accuracy: 59.05% ║
╚═════════════════════════╝
─────────────────────────── Epoch 136/308 - Training ───────────────────────────
Epoch-Loss: 70.6825
────────────────────────── Epoch 136/308 - Validation ──────────────────────────
╔═ Epoch 136/308 Summary ═╗
║ Validation Loss: 1.5816 ║
║ Accuracy: 59.02% ║
╚═════════════════════════╝
─────────────────────────── Epoch 137/308 - Training ───────────────────────────
Epoch-Loss: 70.9742
────────────────────────── Epoch 137/308 - Validation ──────────────────────────
╔═ Epoch 137/308 Summary ═╗
║ Validation Loss: 1.5838 ║
║ Accuracy: 59.03% ║
╚═════════════════════════╝
─────────────────────────── Epoch 138/308 - Training ───────────────────────────
Epoch-Loss: 72.9357
────────────────────────── Epoch 138/308 - Validation ──────────────────────────
╔═ Epoch 138/308 Summary ═╗
║ Validation Loss: 1.5821 ║
║ Accuracy: 58.82% ║
╚═════════════════════════╝
─────────────────────────── Epoch 139/308 - Training ───────────────────────────
Epoch-Loss: 71.5290
────────────────────────── Epoch 139/308 - Validation ──────────────────────────
╔═ Epoch 139/308 Summary ═╗
║ Validation Loss: 1.5796 ║
║ Accuracy: 59.05% ║
╚═════════════════════════╝
─────────────────────────── Epoch 140/308 - Training ───────────────────────────
Epoch-Loss: 71.3970
────────────────────────── Epoch 140/308 - Validation ──────────────────────────
╔═ Epoch 140/308 Summary ═╗
║ Validation Loss: 1.5797 ║
║ Accuracy: 59.23% ║
╚═════════════════════════╝
─────────────────────────── Epoch 141/308 - Training ───────────────────────────
Epoch-Loss: 71.8504
────────────────────────── Epoch 141/308 - Validation ──────────────────────────
╔═ Epoch 141/308 Summary ═╗
║ Validation Loss: 1.5805 ║
║ Accuracy: 59.27% ║
╚═════════════════════════╝
─────────────────────────── Epoch 142/308 - Training ───────────────────────────
Epoch-Loss: 71.7286
────────────────────────── Epoch 142/308 - Validation ──────────────────────────
╔═ Epoch 142/308 Summary ═╗
║ Validation Loss: 1.5831 ║
║ Accuracy: 58.96% ║
╚═════════════════════════╝
─────────────────────────── Epoch 143/308 - Training ───────────────────────────
Epoch-Loss: 71.6794
────────────────────────── Epoch 143/308 - Validation ──────────────────────────
╔═ Epoch 143/308 Summary ═╗
║ Validation Loss: 1.5812 ║
║ Accuracy: 58.91% ║
╚═════════════════════════╝
─────────────────────────── Epoch 144/308 - Training ───────────────────────────
Epoch-Loss: 71.1171
────────────────────────── Epoch 144/308 - Validation ──────────────────────────
╔═ Epoch 144/308 Summary ═╗
║ Validation Loss: 1.5833 ║
║ Accuracy: 58.93% ║
╚═════════════════════════╝
─────────────────────────── Epoch 145/308 - Training ───────────────────────────
Epoch-Loss: 71.2857
────────────────────────── Epoch 145/308 - Validation ──────────────────────────
╔═ Epoch 145/308 Summary ═╗
║ Validation Loss: 1.5814 ║
║ Accuracy: 59.11% ║
╚═════════════════════════╝
─────────────────────────── Epoch 146/308 - Training ───────────────────────────
Epoch-Loss: 71.7857
────────────────────────── Epoch 146/308 - Validation ──────────────────────────
╔═ Epoch 146/308 Summary ═╗
║ Validation Loss: 1.5844 ║
║ Accuracy: 58.89% ║
╚═════════════════════════╝
─────────────────────────── Epoch 147/308 - Training ───────────────────────────
Epoch-Loss: 70.5619
────────────────────────── Epoch 147/308 - Validation ──────────────────────────
╔═ Epoch 147/308 Summary ═╗
║ Validation Loss: 1.5782 ║
║ Accuracy: 59.11% ║
╚═════════════════════════╝
─────────────────────────── Epoch 148/308 - Training ───────────────────────────
Epoch-Loss: 71.2738
────────────────────────── Epoch 148/308 - Validation ──────────────────────────
╔═ Epoch 148/308 Summary ═╗
║ Validation Loss: 1.5799 ║
║ Accuracy: 59.13% ║
╚═════════════════════════╝
─────────────────────────── Epoch 149/308 - Training ───────────────────────────
Epoch-Loss: 71.8375
────────────────────────── Epoch 149/308 - Validation ──────────────────────────
╔═ Epoch 149/308 Summary ═╗
║ Validation Loss: 1.5813 ║
║ Accuracy: 59.02% ║
╚═════════════════════════╝
─────────────────────────── Epoch 150/308 - Training ───────────────────────────
Epoch-Loss: 71.4459
────────────────────────── Epoch 150/308 - Validation ──────────────────────────
╔═ Epoch 150/308 Summary ═╗
║ Validation Loss: 1.5824 ║
║ Accuracy: 59.09% ║
╚═════════════════════════╝
─────────────────────────── Epoch 151/308 - Training ───────────────────────────
Epoch-Loss: 71.1446
────────────────────────── Epoch 151/308 - Validation ──────────────────────────
╔═ Epoch 151/308 Summary ═╗
║ Validation Loss: 1.5788 ║
║ Accuracy: 59.05% ║
╚═════════════════════════╝
─────────────────────────── Epoch 152/308 - Training ───────────────────────────
Epoch-Loss: 70.7597
────────────────────────── Epoch 152/308 - Validation ──────────────────────────
╔═ Epoch 152/308 Summary ═╗
║ Validation Loss: 1.5789 ║
║ Accuracy: 59.07% ║
╚═════════════════════════╝
─────────────────────────── Epoch 153/308 - Training ───────────────────────────
Epoch-Loss: 71.2239
────────────────────────── Epoch 153/308 - Validation ──────────────────────────
╔═ Epoch 153/308 Summary ═╗
║ Validation Loss: 1.5836 ║
║ Accuracy: 59.08% ║
╚═════════════════════════╝
─────────────────────────── Epoch 154/308 - Training ───────────────────────────
Epoch-Loss: 70.7750
────────────────────────── Epoch 154/308 - Validation ──────────────────────────
╔═ Epoch 154/308 Summary ═╗
║ Validation Loss: 1.5802 ║
║ Accuracy: 59.05% ║
╚═════════════════════════╝
─────────────────────────── Epoch 155/308 - Training ───────────────────────────
Epoch-Loss: 70.9977
────────────────────────── Epoch 155/308 - Validation ──────────────────────────
╔═ Epoch 155/308 Summary ═╗
║ Validation Loss: 1.5793 ║
║ Accuracy: 59.22% ║
╚═════════════════════════╝
─────────────────────────── Epoch 156/308 - Training ───────────────────────────
Epoch-Loss: 70.9716
────────────────────────── Epoch 156/308 - Validation ──────────────────────────
╔═ Epoch 156/308 Summary ═╗
║ Validation Loss: 1.5799 ║
║ Accuracy: 58.97% ║
╚═════════════════════════╝
─────────────────────────── Epoch 157/308 - Training ───────────────────────────
Epoch-Loss: 70.7462
────────────────────────── Epoch 157/308 - Validation ──────────────────────────
╔═ Epoch 157/308 Summary ═╗
║ Validation Loss: 1.5834 ║
║ Accuracy: 58.95% ║
╚═════════════════════════╝
─────────────────────────── Epoch 158/308 - Training ───────────────────────────
Epoch-Loss: 70.7152
────────────────────────── Epoch 158/308 - Validation ──────────────────────────
╔═ Epoch 158/308 Summary ═╗
║ Validation Loss: 1.5840 ║
║ Accuracy: 59.12% ║
╚═════════════════════════╝
─────────────────────────── Epoch 159/308 - Training ───────────────────────────
Epoch-Loss: 71.5763
────────────────────────── Epoch 159/308 - Validation ──────────────────────────
╔═ Epoch 159/308 Summary ═╗
║ Validation Loss: 1.5787 ║
║ Accuracy: 59.09% ║
╚═════════════════════════╝
─────────────────────────── Epoch 160/308 - Training ───────────────────────────
Epoch-Loss: 70.8082
────────────────────────── Epoch 160/308 - Validation ──────────────────────────
╔═ Epoch 160/308 Summary ═╗
║ Validation Loss: 1.5834 ║
║ Accuracy: 59.05% ║
╚═════════════════════════╝
─────────────────────────── Epoch 161/308 - Training ───────────────────────────
Epoch-Loss: 71.2934
────────────────────────── Epoch 161/308 - Validation ──────────────────────────
╔═ Epoch 161/308 Summary ═╗
║ Validation Loss: 1.5782 ║
║ Accuracy: 59.24% ║
╚═════════════════════════╝
─────────────────────────── Epoch 162/308 - Training ───────────────────────────
Epoch-Loss: 71.1485
────────────────────────── Epoch 162/308 - Validation ──────────────────────────
╔═ Epoch 162/308 Summary ═╗
║ Validation Loss: 1.5829 ║
║ Accuracy: 59.12% ║
╚═════════════════════════╝
─────────────────────────── Epoch 163/308 - Training ───────────────────────────
Epoch-Loss: 71.0238
────────────────────────── Epoch 163/308 - Validation ──────────────────────────
╔═ Epoch 163/308 Summary ═╗
║ Validation Loss: 1.5804 ║
║ Accuracy: 59.04% ║
╚═════════════════════════╝
─────────────────────────── Epoch 164/308 - Training ───────────────────────────
Epoch-Loss: 71.7951
────────────────────────── Epoch 164/308 - Validation ──────────────────────────
╔═ Epoch 164/308 Summary ═╗
║ Validation Loss: 1.5808 ║
║ Accuracy: 59.12% ║
╚═════════════════════════╝
─────────────────────────── Epoch 165/308 - Training ───────────────────────────
Epoch-Loss: 72.0283
────────────────────────── Epoch 165/308 - Validation ──────────────────────────
╔═ Epoch 165/308 Summary ═╗
║ Validation Loss: 1.5809 ║
║ Accuracy: 59.06% ║
╚═════════════════════════╝
─────────────────────────── Epoch 166/308 - Training ───────────────────────────
Epoch-Loss: 71.1687
────────────────────────── Epoch 166/308 - Validation ──────────────────────────
╔═ Epoch 166/308 Summary ═╗
║ Validation Loss: 1.5815 ║
║ Accuracy: 59.07% ║
╚═════════════════════════╝
─────────────────────────── Epoch 167/308 - Training ───────────────────────────
Epoch-Loss: 71.5625
────────────────────────── Epoch 167/308 - Validation ──────────────────────────
╔═ Epoch 167/308 Summary ═╗
║ Validation Loss: 1.5819 ║
║ Accuracy: 59.01% ║
╚═════════════════════════╝
─────────────────────────── Epoch 168/308 - Training ───────────────────────────
Epoch-Loss: 70.6515
────────────────────────── Epoch 168/308 - Validation ──────────────────────────
╔═ Epoch 168/308 Summary ═╗
║ Validation Loss: 1.5827 ║
║ Accuracy: 59.16% ║
╚═════════════════════════╝
─────────────────────────── Epoch 169/308 - Training ───────────────────────────
Epoch-Loss: 71.9622
────────────────────────── Epoch 169/308 - Validation ──────────────────────────
╔═ Epoch 169/308 Summary ═╗
║ Validation Loss: 1.5839 ║
║ Accuracy: 59.15% ║
╚═════════════════════════╝
─────────────────────────── Epoch 170/308 - Training ───────────────────────────
Epoch-Loss: 71.3994
────────────────────────── Epoch 170/308 - Validation ──────────────────────────
╔═ Epoch 170/308 Summary ═╗
║ Validation Loss: 1.5800 ║
║ Accuracy: 59.12% ║
╚═════════════════════════╝
─────────────────────────── Epoch 171/308 - Training ───────────────────────────
Epoch-Loss: 70.6581
────────────────────────── Epoch 171/308 - Validation ──────────────────────────
╔═ Epoch 171/308 Summary ═╗
║ Validation Loss: 1.5822 ║
║ Accuracy: 59.05% ║
╚═════════════════════════╝
─────────────────────────── Epoch 172/308 - Training ───────────────────────────
Epoch-Loss: 71.1834
────────────────────────── Epoch 172/308 - Validation ──────────────────────────
╔═ Epoch 172/308 Summary ═╗
║ Validation Loss: 1.5791 ║
║ Accuracy: 59.12% ║
╚═════════════════════════╝
─────────────────────────── Epoch 173/308 - Training ───────────────────────────
Epoch-Loss: 71.3039
────────────────────────── Epoch 173/308 - Validation ──────────────────────────
╔═ Epoch 173/308 Summary ═╗
║ Validation Loss: 1.5787 ║
║ Accuracy: 59.15% ║
╚═════════════════════════╝
─────────────────────────── Epoch 174/308 - Training ───────────────────────────
Epoch-Loss: 70.7330
────────────────────────── Epoch 174/308 - Validation ──────────────────────────
╔═ Epoch 174/308 Summary ═╗
║ Validation Loss: 1.5831 ║
║ Accuracy: 58.92% ║
╚═════════════════════════╝
─────────────────────────── Epoch 175/308 - Training ───────────────────────────
Epoch-Loss: 70.5298
────────────────────────── Epoch 175/308 - Validation ──────────────────────────
╔═ Epoch 175/308 Summary ═╗
║ Validation Loss: 1.5819 ║
║ Accuracy: 59.17% ║
╚═════════════════════════╝
─────────────────────────── Epoch 176/308 - Training ───────────────────────────
Epoch-Loss: 71.5444
────────────────────────── Epoch 176/308 - Validation ──────────────────────────
╔═ Epoch 176/308 Summary ═╗
║ Validation Loss: 1.5839 ║
║ Accuracy: 58.91% ║
╚═════════════════════════╝
─────────────────────────── Epoch 177/308 - Training ───────────────────────────
Epoch-Loss: 71.2301
────────────────────────── Epoch 177/308 - Validation ──────────────────────────
╔═ Epoch 177/308 Summary ═╗
║ Validation Loss: 1.5806 ║
║ Accuracy: 59.03% ║
╚═════════════════════════╝
─────────────────────────── Epoch 178/308 - Training ───────────────────────────
Epoch-Loss: 72.3270
────────────────────────── Epoch 178/308 - Validation ──────────────────────────
╔═ Epoch 178/308 Summary ═╗
║ Validation Loss: 1.5833 ║
║ Accuracy: 59.03% ║
╚═════════════════════════╝
─────────────────────────── Epoch 179/308 - Training ───────────────────────────
Epoch-Loss: 71.6034
────────────────────────── Epoch 179/308 - Validation ──────────────────────────
╔═ Epoch 179/308 Summary ═╗
║ Validation Loss: 1.5782 ║
║ Accuracy: 59.16% ║
╚═════════════════════════╝
─────────────────────────── Epoch 180/308 - Training ───────────────────────────
Epoch-Loss: 71.2440
────────────────────────── Epoch 180/308 - Validation ──────────────────────────
╔═ Epoch 180/308 Summary ═╗
║ Validation Loss: 1.5830 ║
║ Accuracy: 58.98% ║
╚═════════════════════════╝
─────────────────────────── Epoch 181/308 - Training ───────────────────────────
Epoch-Loss: 71.4198
────────────────────────── Epoch 181/308 - Validation ──────────────────────────
╔═ Epoch 181/308 Summary ═╗
║ Validation Loss: 1.5798 ║
║ Accuracy: 59.09% ║
╚═════════════════════════╝
─────────────────────────── Epoch 182/308 - Training ───────────────────────────
Epoch-Loss: 71.4096
────────────────────────── Epoch 182/308 - Validation ──────────────────────────
╔═ Epoch 182/308 Summary ═╗
║ Validation Loss: 1.5820 ║
║ Accuracy: 59.01% ║
╚═════════════════════════╝
─────────────────────────── Epoch 183/308 - Training ───────────────────────────
Epoch-Loss: 71.9954
────────────────────────── Epoch 183/308 - Validation ──────────────────────────
╔═ Epoch 183/308 Summary ═╗
║ Validation Loss: 1.5817 ║
║ Accuracy: 59.05% ║
╚═════════════════════════╝
─────────────────────────── Epoch 184/308 - Training ───────────────────────────
Epoch-Loss: 71.1548
────────────────────────── Epoch 184/308 - Validation ──────────────────────────
╔═ Epoch 184/308 Summary ═╗
║ Validation Loss: 1.5829 ║
║ Accuracy: 59.16% ║
╚═════════════════════════╝
─────────────────────────── Epoch 185/308 - Training ───────────────────────────
Epoch-Loss: 70.8510
────────────────────────── Epoch 185/308 - Validation ──────────────────────────
╔═ Epoch 185/308 Summary ═╗
║ Validation Loss: 1.5809 ║
║ Accuracy: 59.04% ║
╚═════════════════════════╝
─────────────────────────── Epoch 186/308 - Training ───────────────────────────
Epoch-Loss: 70.8247
────────────────────────── Epoch 186/308 - Validation ──────────────────────────
╔═ Epoch 186/308 Summary ═╗
║ Validation Loss: 1.5843 ║
║ Accuracy: 59.09% ║
╚═════════════════════════╝
─────────────────────────── Epoch 187/308 - Training ───────────────────────────
Epoch-Loss: 71.6427
────────────────────────── Epoch 187/308 - Validation ──────────────────────────
╔═ Epoch 187/308 Summary ═╗
║ Validation Loss: 1.5794 ║
║ Accuracy: 59.02% ║
╚═════════════════════════╝
─────────────────────────── Epoch 188/308 - Training ───────────────────────────
Epoch-Loss: 71.1067
────────────────────────── Epoch 188/308 - Validation ──────────────────────────
╔═ Epoch 188/308 Summary ═╗
║ Validation Loss: 1.5828 ║
║ Accuracy: 58.98% ║
╚═════════════════════════╝
─────────────────────────── Epoch 189/308 - Training ───────────────────────────
Epoch-Loss: 71.3846
────────────────────────── Epoch 189/308 - Validation ──────────────────────────
╔═ Epoch 189/308 Summary ═╗
║ Validation Loss: 1.5792 ║
║ Accuracy: 59.00% ║
╚═════════════════════════╝
─────────────────────────── Epoch 190/308 - Training ───────────────────────────
Epoch-Loss: 71.2672
────────────────────────── Epoch 190/308 - Validation ──────────────────────────
╔═ Epoch 190/308 Summary ═╗
║ Validation Loss: 1.5802 ║
║ Accuracy: 58.97% ║
╚═════════════════════════╝
─────────────────────────── Epoch 191/308 - Training ───────────────────────────
Epoch-Loss: 71.1267
────────────────────────── Epoch 191/308 - Validation ──────────────────────────
╔═ Epoch 191/308 Summary ═╗
║ Validation Loss: 1.5801 ║
║ Accuracy: 59.25% ║
╚═════════════════════════╝
─────────────────────────── Epoch 192/308 - Training ───────────────────────────
Epoch-Loss: 70.6988
────────────────────────── Epoch 192/308 - Validation ──────────────────────────
╔═ Epoch 192/308 Summary ═╗
║ Validation Loss: 1.5822 ║
║ Accuracy: 58.95% ║
╚═════════════════════════╝
─────────────────────────── Epoch 193/308 - Training ───────────────────────────
Epoch-Loss: 71.3758
────────────────────────── Epoch 193/308 - Validation ──────────────────────────
╔═ Epoch 193/308 Summary ═╗
║ Validation Loss: 1.5804 ║
║ Accuracy: 59.02% ║
╚═════════════════════════╝
─────────────────────────── Epoch 194/308 - Training ───────────────────────────
Epoch-Loss: 70.9982
────────────────────────── Epoch 194/308 - Validation ──────────────────────────
╔═ Epoch 194/308 Summary ═╗
║ Validation Loss: 1.5826 ║
║ Accuracy: 59.15% ║
╚═════════════════════════╝
─────────────────────────── Epoch 195/308 - Training ───────────────────────────
Epoch-Loss: 71.0917
────────────────────────── Epoch 195/308 - Validation ──────────────────────────
╔═ Epoch 195/308 Summary ═╗
║ Validation Loss: 1.5782 ║
║ Accuracy: 59.06% ║
╚═════════════════════════╝
─────────────────────────── Epoch 196/308 - Training ───────────────────────────
Epoch-Loss: 71.2770
────────────────────────── Epoch 196/308 - Validation ──────────────────────────
╔═ Epoch 196/308 Summary ═╗
║ Validation Loss: 1.5843 ║
║ Accuracy: 59.27% ║
╚═════════════════════════╝
─────────────────────────── Epoch 197/308 - Training ───────────────────────────
Epoch-Loss: 71.5150
────────────────────────── Epoch 197/308 - Validation ──────────────────────────
╔═ Epoch 197/308 Summary ═╗
║ Validation Loss: 1.5813 ║
║ Accuracy: 59.01% ║
╚═════════════════════════╝
─────────────────────────── Epoch 198/308 - Training ───────────────────────────
Epoch-Loss: 71.4625
────────────────────────── Epoch 198/308 - Validation ──────────────────────────
╔═ Epoch 198/308 Summary ═╗
║ Validation Loss: 1.5826 ║
║ Accuracy: 59.16% ║
╚═════════════════════════╝
─────────────────────────── Epoch 199/308 - Training ───────────────────────────
Epoch-Loss: 71.5134
────────────────────────── Epoch 199/308 - Validation ──────────────────────────
╔═ Epoch 199/308 Summary ═╗
║ Validation Loss: 1.5778 ║
║ Accuracy: 59.14% ║
╚═════════════════════════╝
─────────────────────────── Epoch 200/308 - Training ───────────────────────────
Epoch-Loss: 70.6352
────────────────────────── Epoch 200/308 - Validation ──────────────────────────
╔═ Epoch 200/308 Summary ═╗
║ Validation Loss: 1.5803 ║
║ Accuracy: 59.13% ║
╚═════════════════════════╝
─────────────────────────── Epoch 201/308 - Training ───────────────────────────
Epoch-Loss: 71.1393
────────────────────────── Epoch 201/308 - Validation ──────────────────────────
╔═ Epoch 201/308 Summary ═╗
║ Validation Loss: 1.5810 ║
║ Accuracy: 59.23% ║
╚═════════════════════════╝
─────────────────────────── Epoch 202/308 - Training ───────────────────────────
Epoch-Loss: 71.2913
────────────────────────── Epoch 202/308 - Validation ──────────────────────────
╔═ Epoch 202/308 Summary ═╗
║ Validation Loss: 1.5812 ║
║ Accuracy: 59.10% ║
╚═════════════════════════╝
─────────────────────────── Epoch 203/308 - Training ───────────────────────────
Epoch-Loss: 71.1343
────────────────────────── Epoch 203/308 - Validation ──────────────────────────
╔═ Epoch 203/308 Summary ═╗
║ Validation Loss: 1.5785 ║
║ Accuracy: 59.10% ║
╚═════════════════════════╝
─────────────────────────── Epoch 204/308 - Training ───────────────────────────
Epoch-Loss: 70.7685
────────────────────────── Epoch 204/308 - Validation ──────────────────────────
╔═ Epoch 204/308 Summary ═╗
║ Validation Loss: 1.5829 ║
║ Accuracy: 59.03% ║
╚═════════════════════════╝
─────────────────────────── Epoch 205/308 - Training ───────────────────────────
Epoch-Loss: 71.7629
────────────────────────── Epoch 205/308 - Validation ──────────────────────────
╔═ Epoch 205/308 Summary ═╗
║ Validation Loss: 1.5803 ║
║ Accuracy: 59.02% ║
╚═════════════════════════╝
─────────────────────────── Epoch 206/308 - Training ───────────────────────────
Epoch-Loss: 70.9740
────────────────────────── Epoch 206/308 - Validation ──────────────────────────
╔═ Epoch 206/308 Summary ═╗
║ Validation Loss: 1.5804 ║
║ Accuracy: 59.00% ║
╚═════════════════════════╝
─────────────────────────── Epoch 207/308 - Training ───────────────────────────
Epoch-Loss: 71.4037
────────────────────────── Epoch 207/308 - Validation ──────────────────────────
╔═ Epoch 207/308 Summary ═╗
║ Validation Loss: 1.5778 ║
║ Accuracy: 59.00% ║
╚═════════════════════════╝
─────────────────────────── Epoch 208/308 - Training ───────────────────────────
Epoch-Loss: 71.9584
────────────────────────── Epoch 208/308 - Validation ──────────────────────────
╔═ Epoch 208/308 Summary ═╗
║ Validation Loss: 1.5782 ║
║ Accuracy: 59.09% ║
╚═════════════════════════╝
─────────────────────────── Epoch 209/308 - Training ───────────────────────────
Epoch-Loss: 70.9882
────────────────────────── Epoch 209/308 - Validation ──────────────────────────
╔═ Epoch 209/308 Summary ═╗
║ Validation Loss: 1.5829 ║
║ Accuracy: 59.09% ║
╚═════════════════════════╝
─────────────────────────── Epoch 210/308 - Training ───────────────────────────
Epoch-Loss: 71.0275
────────────────────────── Epoch 210/308 - Validation ──────────────────────────
╔═ Epoch 210/308 Summary ═╗
║ Validation Loss: 1.5765 ║
║ Accuracy: 59.18% ║
╚═════════════════════════╝
─────────────────────────── Epoch 211/308 - Training ───────────────────────────
Epoch-Loss: 71.1394
────────────────────────── Epoch 211/308 - Validation ──────────────────────────
╔═ Epoch 211/308 Summary ═╗
║ Validation Loss: 1.5845 ║
║ Accuracy: 59.07% ║
╚═════════════════════════╝
─────────────────────────── Epoch 212/308 - Training ───────────────────────────
Epoch-Loss: 70.8120
────────────────────────── Epoch 212/308 - Validation ──────────────────────────
╔═ Epoch 212/308 Summary ═╗
║ Validation Loss: 1.5784 ║
║ Accuracy: 59.06% ║
╚═════════════════════════╝
─────────────────────────── Epoch 213/308 - Training ───────────────────────────
Epoch-Loss: 71.3817
────────────────────────── Epoch 213/308 - Validation ──────────────────────────
╔═ Epoch 213/308 Summary ═╗
║ Validation Loss: 1.5825 ║
║ Accuracy: 59.02% ║
╚═════════════════════════╝
─────────────────────────── Epoch 214/308 - Training ───────────────────────────
Epoch-Loss: 71.2850
────────────────────────── Epoch 214/308 - Validation ──────────────────────────
╔═ Epoch 214/308 Summary ═╗
║ Validation Loss: 1.5791 ║
║ Accuracy: 59.13% ║
╚═════════════════════════╝
─────────────────────────── Epoch 215/308 - Training ───────────────────────────
Epoch-Loss: 71.6693
────────────────────────── Epoch 215/308 - Validation ──────────────────────────
╔═ Epoch 215/308 Summary ═╗
║ Validation Loss: 1.5821 ║
║ Accuracy: 59.01% ║
╚═════════════════════════╝
─────────────────────────── Epoch 216/308 - Training ───────────────────────────
Epoch-Loss: 70.9891
────────────────────────── Epoch 216/308 - Validation ──────────────────────────
╔═ Epoch 216/308 Summary ═╗
║ Validation Loss: 1.5829 ║
║ Accuracy: 58.88% ║
╚═════════════════════════╝
─────────────────────────── Epoch 217/308 - Training ───────────────────────────
Epoch-Loss: 71.2479
────────────────────────── Epoch 217/308 - Validation ──────────────────────────
╔═ Epoch 217/308 Summary ═╗
║ Validation Loss: 1.5832 ║
║ Accuracy: 59.05% ║
╚═════════════════════════╝
─────────────────────────── Epoch 218/308 - Training ───────────────────────────
Epoch-Loss: 70.8375
────────────────────────── Epoch 218/308 - Validation ──────────────────────────
╔═ Epoch 218/308 Summary ═╗
║ Validation Loss: 1.5833 ║
║ Accuracy: 59.10% ║
╚═════════════════════════╝
─────────────────────────── Epoch 219/308 - Training ───────────────────────────
Epoch-Loss: 71.1271
────────────────────────── Epoch 219/308 - Validation ──────────────────────────
╔═ Epoch 219/308 Summary ═╗
║ Validation Loss: 1.5815 ║
║ Accuracy: 59.15% ║
╚═════════════════════════╝
─────────────────────────── Epoch 220/308 - Training ───────────────────────────
Epoch-Loss: 70.7369
────────────────────────── Epoch 220/308 - Validation ──────────────────────────
╔═ Epoch 220/308 Summary ═╗
║ Validation Loss: 1.5795 ║
║ Accuracy: 58.99% ║
╚═════════════════════════╝
─────────────────────────── Epoch 221/308 - Training ───────────────────────────
Epoch-Loss: 71.4905
────────────────────────── Epoch 221/308 - Validation ──────────────────────────
╔═ Epoch 221/308 Summary ═╗
║ Validation Loss: 1.5794 ║
║ Accuracy: 59.07% ║
╚═════════════════════════╝
─────────────────────────── Epoch 222/308 - Training ───────────────────────────
Epoch-Loss: 71.2938
────────────────────────── Epoch 222/308 - Validation ──────────────────────────
╔═ Epoch 222/308 Summary ═╗
║ Validation Loss: 1.5815 ║
║ Accuracy: 59.02% ║
╚═════════════════════════╝
─────────────────────────── Epoch 223/308 - Training ───────────────────────────
Epoch-Loss: 71.2476
────────────────────────── Epoch 223/308 - Validation ──────────────────────────
╔═ Epoch 223/308 Summary ═╗
║ Validation Loss: 1.5830 ║
║ Accuracy: 59.05% ║
╚═════════════════════════╝
─────────────────────────── Epoch 224/308 - Training ───────────────────────────
Epoch-Loss: 70.5288
────────────────────────── Epoch 224/308 - Validation ──────────────────────────
╔═ Epoch 224/308 Summary ═╗
║ Validation Loss: 1.5785 ║
║ Accuracy: 59.10% ║
╚═════════════════════════╝
─────────────────────────── Epoch 225/308 - Training ───────────────────────────
Epoch-Loss: 71.3628
────────────────────────── Epoch 225/308 - Validation ──────────────────────────
╔═ Epoch 225/308 Summary ═╗
║ Validation Loss: 1.5810 ║
║ Accuracy: 59.01% ║
╚═════════════════════════╝
─────────────────────────── Epoch 226/308 - Training ───────────────────────────
Epoch-Loss: 70.3498
────────────────────────── Epoch 226/308 - Validation ──────────────────────────
╔═ Epoch 226/308 Summary ═╗
║ Validation Loss: 1.5809 ║
║ Accuracy: 59.13% ║
╚═════════════════════════╝
─────────────────────────── Epoch 227/308 - Training ───────────────────────────
Epoch-Loss: 72.0759
────────────────────────── Epoch 227/308 - Validation ──────────────────────────
╔═ Epoch 227/308 Summary ═╗
║ Validation Loss: 1.5813 ║
║ Accuracy: 59.20% ║
╚═════════════════════════╝
─────────────────────────── Epoch 228/308 - Training ───────────────────────────
Epoch-Loss: 71.6727
────────────────────────── Epoch 228/308 - Validation ──────────────────────────
╔═ Epoch 228/308 Summary ═╗
║ Validation Loss: 1.5811 ║
║ Accuracy: 59.06% ║
╚═════════════════════════╝
─────────────────────────── Epoch 229/308 - Training ───────────────────────────
Epoch-Loss: 71.4015
────────────────────────── Epoch 229/308 - Validation ──────────────────────────
╔═ Epoch 229/308 Summary ═╗
║ Validation Loss: 1.5820 ║
║ Accuracy: 58.93% ║
╚═════════════════════════╝
─────────────────────────── Epoch 230/308 - Training ───────────────────────────
Epoch-Loss: 71.4316
────────────────────────── Epoch 230/308 - Validation ──────────────────────────
╔═ Epoch 230/308 Summary ═╗
║ Validation Loss: 1.5809 ║
║ Accuracy: 59.09% ║
╚═════════════════════════╝
─────────────────────────── Epoch 231/308 - Training ───────────────────────────
Epoch-Loss: 71.2613
────────────────────────── Epoch 231/308 - Validation ──────────────────────────
╔═ Epoch 231/308 Summary ═╗
║ Validation Loss: 1.5821 ║
║ Accuracy: 59.10% ║
╚═════════════════════════╝
─────────────────────────── Epoch 232/308 - Training ───────────────────────────
Epoch-Loss: 71.1987
────────────────────────── Epoch 232/308 - Validation ──────────────────────────
╔═ Epoch 232/308 Summary ═╗
║ Validation Loss: 1.5839 ║
║ Accuracy: 58.93% ║
╚═════════════════════════╝
─────────────────────────── Epoch 233/308 - Training ───────────────────────────
Epoch-Loss: 70.4883
────────────────────────── Epoch 233/308 - Validation ──────────────────────────
╔═ Epoch 233/308 Summary ═╗
║ Validation Loss: 1.5810 ║
║ Accuracy: 59.08% ║
╚═════════════════════════╝
─────────────────────────── Epoch 234/308 - Training ───────────────────────────
Epoch-Loss: 71.5017
────────────────────────── Epoch 234/308 - Validation ──────────────────────────
╔═ Epoch 234/308 Summary ═╗
║ Validation Loss: 1.5790 ║
║ Accuracy: 59.00% ║
╚═════════════════════════╝
─────────────────────────── Epoch 235/308 - Training ───────────────────────────
Epoch-Loss: 71.1109
────────────────────────── Epoch 235/308 - Validation ──────────────────────────
╔═ Epoch 235/308 Summary ═╗
║ Validation Loss: 1.5827 ║
║ Accuracy: 58.96% ║
╚═════════════════════════╝
─────────────────────────── Epoch 236/308 - Training ───────────────────────────
Epoch-Loss: 72.1548
────────────────────────── Epoch 236/308 - Validation ──────────────────────────
╔═ Epoch 236/308 Summary ═╗
║ Validation Loss: 1.5842 ║
║ Accuracy: 58.93% ║
╚═════════════════════════╝
─────────────────────────── Epoch 237/308 - Training ───────────────────────────
Epoch-Loss: 70.4235
────────────────────────── Epoch 237/308 - Validation ──────────────────────────
╔═ Epoch 237/308 Summary ═╗
║ Validation Loss: 1.5808 ║
║ Accuracy: 59.08% ║
╚═════════════════════════╝
─────────────────────────── Epoch 238/308 - Training ───────────────────────────
Epoch-Loss: 71.4191
────────────────────────── Epoch 238/308 - Validation ──────────────────────────
╔═ Epoch 238/308 Summary ═╗
║ Validation Loss: 1.5817 ║
║ Accuracy: 59.05% ║
╚═════════════════════════╝
─────────────────────────── Epoch 239/308 - Training ───────────────────────────
Epoch-Loss: 71.2709
────────────────────────── Epoch 239/308 - Validation ──────────────────────────
╔═ Epoch 239/308 Summary ═╗
║ Validation Loss: 1.5795 ║
║ Accuracy: 59.06% ║
╚═════════════════════════╝
─────────────────────────── Epoch 240/308 - Training ───────────────────────────
Epoch-Loss: 71.7386
────────────────────────── Epoch 240/308 - Validation ──────────────────────────
╔═ Epoch 240/308 Summary ═╗
║ Validation Loss: 1.5784 ║
║ Accuracy: 59.01% ║
╚═════════════════════════╝
─────────────────────────── Epoch 241/308 - Training ───────────────────────────
Epoch-Loss: 71.1745
────────────────────────── Epoch 241/308 - Validation ──────────────────────────
╔═ Epoch 241/308 Summary ═╗
║ Validation Loss: 1.5814 ║
║ Accuracy: 59.01% ║
╚═════════════════════════╝
─────────────────────────── Epoch 242/308 - Training ───────────────────────────
Epoch-Loss: 70.8853
────────────────────────── Epoch 242/308 - Validation ──────────────────────────
╔═ Epoch 242/308 Summary ═╗
║ Validation Loss: 1.5819 ║
║ Accuracy: 59.08% ║
╚═════════════════════════╝
─────────────────────────── Epoch 243/308 - Training ───────────────────────────
Epoch-Loss: 71.9092
────────────────────────── Epoch 243/308 - Validation ──────────────────────────
╔═ Epoch 243/308 Summary ═╗
║ Validation Loss: 1.5833 ║
║ Accuracy: 59.10% ║
╚═════════════════════════╝
─────────────────────────── Epoch 244/308 - Training ───────────────────────────
Epoch-Loss: 72.2669
────────────────────────── Epoch 244/308 - Validation ──────────────────────────
╔═ Epoch 244/308 Summary ═╗
║ Validation Loss: 1.5828 ║
║ Accuracy: 59.08% ║
╚═════════════════════════╝
─────────────────────────── Epoch 245/308 - Training ───────────────────────────
Epoch-Loss: 71.1122
────────────────────────── Epoch 245/308 - Validation ──────────────────────────
╔═ Epoch 245/308 Summary ═╗
║ Validation Loss: 1.5820 ║
║ Accuracy: 58.99% ║
╚═════════════════════════╝
─────────────────────────── Epoch 246/308 - Training ───────────────────────────
Epoch-Loss: 70.9912
────────────────────────── Epoch 246/308 - Validation ──────────────────────────
╔═ Epoch 246/308 Summary ═╗
║ Validation Loss: 1.5807 ║
║ Accuracy: 59.01% ║
╚═════════════════════════╝
─────────────────────────── Epoch 247/308 - Training ───────────────────────────
Epoch-Loss: 70.9488
────────────────────────── Epoch 247/308 - Validation ──────────────────────────
╔═ Epoch 247/308 Summary ═╗
║ Validation Loss: 1.5793 ║
║ Accuracy: 59.11% ║
╚═════════════════════════╝
─────────────────────────── Epoch 248/308 - Training ───────────────────────────
Epoch-Loss: 71.2954
────────────────────────── Epoch 248/308 - Validation ──────────────────────────
╔═ Epoch 248/308 Summary ═╗
║ Validation Loss: 1.5806 ║
║ Accuracy: 58.99% ║
╚═════════════════════════╝
─────────────────────────── Epoch 249/308 - Training ───────────────────────────
Epoch-Loss: 71.7514
────────────────────────── Epoch 249/308 - Validation ──────────────────────────
╔═ Epoch 249/308 Summary ═╗
║ Validation Loss: 1.5826 ║
║ Accuracy: 59.05% ║
╚═════════════════════════╝
─────────────────────────── Epoch 250/308 - Training ───────────────────────────
Epoch-Loss: 70.9069
────────────────────────── Epoch 250/308 - Validation ──────────────────────────
╔═ Epoch 250/308 Summary ═╗
║ Validation Loss: 1.5791 ║
║ Accuracy: 59.02% ║
╚═════════════════════════╝
─────────────────────────── Epoch 251/308 - Training ───────────────────────────
Epoch-Loss: 71.6755
────────────────────────── Epoch 251/308 - Validation ──────────────────────────
╔═ Epoch 251/308 Summary ═╗
║ Validation Loss: 1.5812 ║
║ Accuracy: 58.95% ║
╚═════════════════════════╝
─────────────────────────── Epoch 252/308 - Training ───────────────────────────
Epoch-Loss: 71.5097
────────────────────────── Epoch 252/308 - Validation ──────────────────────────
╔═ Epoch 252/308 Summary ═╗
║ Validation Loss: 1.5803 ║
║ Accuracy: 58.93% ║
╚═════════════════════════╝
─────────────────────────── Epoch 253/308 - Training ───────────────────────────
Epoch-Loss: 71.5995
────────────────────────── Epoch 253/308 - Validation ──────────────────────────
╔═ Epoch 253/308 Summary ═╗
║ Validation Loss: 1.5829 ║
║ Accuracy: 59.06% ║
╚═════════════════════════╝
─────────────────────────── Epoch 254/308 - Training ───────────────────────────
Epoch-Loss: 71.6918
────────────────────────── Epoch 254/308 - Validation ──────────────────────────
╔═ Epoch 254/308 Summary ═╗
║ Validation Loss: 1.5785 ║
║ Accuracy: 59.15% ║
╚═════════════════════════╝
─────────────────────────── Epoch 255/308 - Training ───────────────────────────
Epoch-Loss: 71.6113
────────────────────────── Epoch 255/308 - Validation ──────────────────────────
╔═ Epoch 255/308 Summary ═╗
║ Validation Loss: 1.5814 ║
║ Accuracy: 59.17% ║
╚═════════════════════════╝
─────────────────────────── Epoch 256/308 - Training ───────────────────────────
Epoch-Loss: 71.9880
────────────────────────── Epoch 256/308 - Validation ──────────────────────────
╔═ Epoch 256/308 Summary ═╗
║ Validation Loss: 1.5815 ║
║ Accuracy: 59.01% ║
╚═════════════════════════╝
─────────────────────────── Epoch 257/308 - Training ───────────────────────────
Epoch-Loss: 71.1923
────────────────────────── Epoch 257/308 - Validation ──────────────────────────
╔═ Epoch 257/308 Summary ═╗
║ Validation Loss: 1.5788 ║
║ Accuracy: 59.04% ║
╚═════════════════════════╝
─────────────────────────── Epoch 258/308 - Training ───────────────────────────
Epoch-Loss: 71.1786
────────────────────────── Epoch 258/308 - Validation ──────────────────────────
╔═ Epoch 258/308 Summary ═╗
║ Validation Loss: 1.5755 ║
║ Accuracy: 59.21% ║
╚═════════════════════════╝
─────────────────────────── Epoch 259/308 - Training ───────────────────────────
Epoch-Loss: 70.9940
────────────────────────── Epoch 259/308 - Validation ──────────────────────────
╔═ Epoch 259/308 Summary ═╗
║ Validation Loss: 1.5823 ║
║ Accuracy: 59.01% ║
╚═════════════════════════╝
─────────────────────────── Epoch 260/308 - Training ───────────────────────────
Epoch-Loss: 71.3353
────────────────────────── Epoch 260/308 - Validation ──────────────────────────
╔═ Epoch 260/308 Summary ═╗
║ Validation Loss: 1.5842 ║
║ Accuracy: 58.96% ║
╚═════════════════════════╝
─────────────────────────── Epoch 261/308 - Training ───────────────────────────
Epoch-Loss: 70.9807
────────────────────────── Epoch 261/308 - Validation ──────────────────────────
╔═ Epoch 261/308 Summary ═╗
║ Validation Loss: 1.5780 ║
║ Accuracy: 59.01% ║
╚═════════════════════════╝
─────────────────────────── Epoch 262/308 - Training ───────────────────────────
Epoch-Loss: 71.6804
────────────────────────── Epoch 262/308 - Validation ──────────────────────────
╔═ Epoch 262/308 Summary ═╗
║ Validation Loss: 1.5826 ║
║ Accuracy: 58.88% ║
╚═════════════════════════╝
─────────────────────────── Epoch 263/308 - Training ───────────────────────────
Epoch-Loss: 71.1304
────────────────────────── Epoch 263/308 - Validation ──────────────────────────
╔═ Epoch 263/308 Summary ═╗
║ Validation Loss: 1.5833 ║
║ Accuracy: 59.01% ║
╚═════════════════════════╝
─────────────────────────── Epoch 264/308 - Training ───────────────────────────
Epoch-Loss: 71.7555
────────────────────────── Epoch 264/308 - Validation ──────────────────────────
╔═ Epoch 264/308 Summary ═╗
║ Validation Loss: 1.5792 ║
║ Accuracy: 59.22% ║
╚═════════════════════════╝
─────────────────────────── Epoch 265/308 - Training ───────────────────────────
Epoch-Loss: 71.6950
────────────────────────── Epoch 265/308 - Validation ──────────────────────────
╔═ Epoch 265/308 Summary ═╗
║ Validation Loss: 1.5797 ║
║ Accuracy: 59.05% ║
╚═════════════════════════╝
─────────────────────────── Epoch 266/308 - Training ───────────────────────────
Epoch-Loss: 71.4124
────────────────────────── Epoch 266/308 - Validation ──────────────────────────
╔═ Epoch 266/308 Summary ═╗
║ Validation Loss: 1.5787 ║
║ Accuracy: 59.04% ║
╚═════════════════════════╝
─────────────────────────── Epoch 267/308 - Training ───────────────────────────
Epoch-Loss: 71.2861
────────────────────────── Epoch 267/308 - Validation ──────────────────────────
╔═ Epoch 267/308 Summary ═╗
║ Validation Loss: 1.5803 ║
║ Accuracy: 59.00% ║
╚═════════════════════════╝
─────────────────────────── Epoch 268/308 - Training ───────────────────────────
Epoch-Loss: 71.4560
────────────────────────── Epoch 268/308 - Validation ──────────────────────────
╔═ Epoch 268/308 Summary ═╗
║ Validation Loss: 1.5821 ║
║ Accuracy: 58.96% ║
╚═════════════════════════╝
─────────────────────────── Epoch 269/308 - Training ───────────────────────────
Epoch-Loss: 71.1040
────────────────────────── Epoch 269/308 - Validation ──────────────────────────
╔═ Epoch 269/308 Summary ═╗
║ Validation Loss: 1.5805 ║
║ Accuracy: 59.15% ║
╚═════════════════════════╝
─────────────────────────── Epoch 270/308 - Training ───────────────────────────
Epoch-Loss: 71.6364
────────────────────────── Epoch 270/308 - Validation ──────────────────────────
╔═ Epoch 270/308 Summary ═╗
║ Validation Loss: 1.5798 ║
║ Accuracy: 58.96% ║
╚═════════════════════════╝
─────────────────────────── Epoch 271/308 - Training ───────────────────────────
Epoch-Loss: 71.7650
────────────────────────── Epoch 271/308 - Validation ──────────────────────────
╔═ Epoch 271/308 Summary ═╗
║ Validation Loss: 1.5811 ║
║ Accuracy: 59.03% ║
╚═════════════════════════╝
─────────────────────────── Epoch 272/308 - Training ───────────────────────────
Epoch-Loss: 70.8091
────────────────────────── Epoch 272/308 - Validation ──────────────────────────
╔═ Epoch 272/308 Summary ═╗
║ Validation Loss: 1.5800 ║
║ Accuracy: 59.19% ║
╚═════════════════════════╝
─────────────────────────── Epoch 273/308 - Training ───────────────────────────
Epoch-Loss: 70.5630
────────────────────────── Epoch 273/308 - Validation ──────────────────────────
╔═ Epoch 273/308 Summary ═╗
║ Validation Loss: 1.5791 ║
║ Accuracy: 59.17% ║
╚═════════════════════════╝
─────────────────────────── Epoch 274/308 - Training ───────────────────────────
Epoch-Loss: 70.9771
────────────────────────── Epoch 274/308 - Validation ──────────────────────────
╔═ Epoch 274/308 Summary ═╗
║ Validation Loss: 1.5807 ║
║ Accuracy: 59.03% ║
╚═════════════════════════╝
─────────────────────────── Epoch 275/308 - Training ───────────────────────────
Epoch-Loss: 71.0839
────────────────────────── Epoch 275/308 - Validation ──────────────────────────
╔═ Epoch 275/308 Summary ═╗
║ Validation Loss: 1.5803 ║
║ Accuracy: 59.03% ║
╚═════════════════════════╝
─────────────────────────── Epoch 276/308 - Training ───────────────────────────
Epoch-Loss: 71.2285
────────────────────────── Epoch 276/308 - Validation ──────────────────────────
╔═ Epoch 276/308 Summary ═╗
║ Validation Loss: 1.5801 ║
║ Accuracy: 59.11% ║
╚═════════════════════════╝
─────────────────────────── Epoch 277/308 - Training ───────────────────────────
Epoch-Loss: 71.1879
────────────────────────── Epoch 277/308 - Validation ──────────────────────────
╔═ Epoch 277/308 Summary ═╗
║ Validation Loss: 1.5785 ║
║ Accuracy: 59.10% ║
╚═════════════════════════╝
─────────────────────────── Epoch 278/308 - Training ───────────────────────────
Epoch-Loss: 70.9889
────────────────────────── Epoch 278/308 - Validation ──────────────────────────
╔═ Epoch 278/308 Summary ═╗
║ Validation Loss: 1.5785 ║
║ Accuracy: 59.15% ║
╚═════════════════════════╝
─────────────────────────── Epoch 279/308 - Training ───────────────────────────
Epoch-Loss: 70.6312
────────────────────────── Epoch 279/308 - Validation ──────────────────────────
╔═ Epoch 279/308 Summary ═╗
║ Validation Loss: 1.5812 ║
║ Accuracy: 59.08% ║
╚═════════════════════════╝
─────────────────────────── Epoch 280/308 - Training ───────────────────────────
Epoch-Loss: 70.7436
────────────────────────── Epoch 280/308 - Validation ──────────────────────────
╔═ Epoch 280/308 Summary ═╗
║ Validation Loss: 1.5809 ║
║ Accuracy: 59.04% ║
╚═════════════════════════╝
─────────────────────────── Epoch 281/308 - Training ───────────────────────────
Epoch-Loss: 70.9193
────────────────────────── Epoch 281/308 - Validation ──────────────────────────
╔═ Epoch 281/308 Summary ═╗
║ Validation Loss: 1.5813 ║
║ Accuracy: 58.86% ║
╚═════════════════════════╝
─────────────────────────── Epoch 282/308 - Training ───────────────────────────
Epoch-Loss: 71.5285
────────────────────────── Epoch 282/308 - Validation ──────────────────────────
╔═ Epoch 282/308 Summary ═╗
║ Validation Loss: 1.5801 ║
║ Accuracy: 59.14% ║
╚═════════════════════════╝
─────────────────────────── Epoch 283/308 - Training ───────────────────────────
Epoch-Loss: 70.7492
────────────────────────── Epoch 283/308 - Validation ──────────────────────────
╔═ Epoch 283/308 Summary ═╗
║ Validation Loss: 1.5808 ║
║ Accuracy: 59.14% ║
╚═════════════════════════╝
─────────────────────────── Epoch 284/308 - Training ───────────────────────────
Epoch-Loss: 71.3683
────────────────────────── Epoch 284/308 - Validation ──────────────────────────
╔═ Epoch 284/308 Summary ═╗
║ Validation Loss: 1.5793 ║
║ Accuracy: 59.05% ║
╚═════════════════════════╝
─────────────────────────── Epoch 285/308 - Training ───────────────────────────
Epoch-Loss: 72.0213
────────────────────────── Epoch 285/308 - Validation ──────────────────────────
╔═ Epoch 285/308 Summary ═╗
║ Validation Loss: 1.5819 ║
║ Accuracy: 59.12% ║
╚═════════════════════════╝
─────────────────────────── Epoch 286/308 - Training ───────────────────────────
Epoch-Loss: 70.8938
────────────────────────── Epoch 286/308 - Validation ──────────────────────────
╔═ Epoch 286/308 Summary ═╗
║ Validation Loss: 1.5818 ║
║ Accuracy: 58.99% ║
╚═════════════════════════╝
─────────────────────────── Epoch 287/308 - Training ───────────────────────────
Epoch-Loss: 71.1468
────────────────────────── Epoch 287/308 - Validation ──────────────────────────
╔═ Epoch 287/308 Summary ═╗
║ Validation Loss: 1.5771 ║
║ Accuracy: 59.08% ║
╚═════════════════════════╝
─────────────────────────── Epoch 288/308 - Training ───────────────────────────
Epoch-Loss: 70.4069
────────────────────────── Epoch 288/308 - Validation ──────────────────────────
╔═ Epoch 288/308 Summary ═╗
║ Validation Loss: 1.5789 ║
║ Accuracy: 59.14% ║
╚═════════════════════════╝
─────────────────────────── Epoch 289/308 - Training ───────────────────────────
Epoch-Loss: 71.3303
────────────────────────── Epoch 289/308 - Validation ──────────────────────────
╔═ Epoch 289/308 Summary ═╗
║ Validation Loss: 1.5818 ║
║ Accuracy: 59.06% ║
╚═════════════════════════╝
─────────────────────────── Epoch 290/308 - Training ───────────────────────────
Epoch-Loss: 71.0295
────────────────────────── Epoch 290/308 - Validation ──────────────────────────
╔═ Epoch 290/308 Summary ═╗
║ Validation Loss: 1.5802 ║
║ Accuracy: 59.15% ║
╚═════════════════════════╝
─────────────────────────── Epoch 291/308 - Training ───────────────────────────
Epoch-Loss: 71.5645
────────────────────────── Epoch 291/308 - Validation ──────────────────────────
╔═ Epoch 291/308 Summary ═╗
║ Validation Loss: 1.5816 ║
║ Accuracy: 59.07% ║
╚═════════════════════════╝
─────────────────────────── Epoch 292/308 - Training ───────────────────────────
Epoch-Loss: 72.0467
────────────────────────── Epoch 292/308 - Validation ──────────────────────────
╔═ Epoch 292/308 Summary ═╗
║ Validation Loss: 1.5817 ║
║ Accuracy: 59.19% ║
╚═════════════════════════╝
─────────────────────────── Epoch 293/308 - Training ───────────────────────────
Epoch-Loss: 71.8308
────────────────────────── Epoch 293/308 - Validation ──────────────────────────
╔═ Epoch 293/308 Summary ═╗
║ Validation Loss: 1.5822 ║
║ Accuracy: 59.02% ║
╚═════════════════════════╝
─────────────────────────── Epoch 294/308 - Training ───────────────────────────
Epoch-Loss: 70.9338
────────────────────────── Epoch 294/308 - Validation ──────────────────────────
╔═ Epoch 294/308 Summary ═╗
║ Validation Loss: 1.5821 ║
║ Accuracy: 59.09% ║
╚═════════════════════════╝
─────────────────────────── Epoch 295/308 - Training ───────────────────────────
Epoch-Loss: 71.0240
────────────────────────── Epoch 295/308 - Validation ──────────────────────────
╔═ Epoch 295/308 Summary ═╗
║ Validation Loss: 1.5804 ║
║ Accuracy: 58.95% ║
╚═════════════════════════╝
─────────────────────────── Epoch 296/308 - Training ───────────────────────────
Epoch-Loss: 71.0500
────────────────────────── Epoch 296/308 - Validation ──────────────────────────
╔═ Epoch 296/308 Summary ═╗
║ Validation Loss: 1.5791 ║
║ Accuracy: 59.12% ║
╚═════════════════════════╝
─────────────────────────── Epoch 297/308 - Training ───────────────────────────
Epoch-Loss: 70.5282
────────────────────────── Epoch 297/308 - Validation ──────────────────────────
╔═ Epoch 297/308 Summary ═╗
║ Validation Loss: 1.5781 ║
║ Accuracy: 59.11% ║
╚═════════════════════════╝
─────────────────────────── Epoch 298/308 - Training ───────────────────────────
Epoch-Loss: 71.2861
────────────────────────── Epoch 298/308 - Validation ──────────────────────────
╔═ Epoch 298/308 Summary ═╗
║ Validation Loss: 1.5794 ║
║ Accuracy: 59.10% ║
╚═════════════════════════╝
─────────────────────────── Epoch 299/308 - Training ───────────────────────────
Epoch-Loss: 70.5723
────────────────────────── Epoch 299/308 - Validation ──────────────────────────
╔═ Epoch 299/308 Summary ═╗
║ Validation Loss: 1.5796 ║
║ Accuracy: 59.03% ║
╚═════════════════════════╝
─────────────────────────── Epoch 300/308 - Training ───────────────────────────
Epoch-Loss: 70.9577
────────────────────────── Epoch 300/308 - Validation ──────────────────────────
╔═ Epoch 300/308 Summary ═╗
║ Validation Loss: 1.5804 ║
║ Accuracy: 59.02% ║
╚═════════════════════════╝
─────────────────────────── Epoch 301/308 - Training ───────────────────────────
Epoch-Loss: 71.4810
────────────────────────── Epoch 301/308 - Validation ──────────────────────────
╔═ Epoch 301/308 Summary ═╗
║ Validation Loss: 1.5849 ║
║ Accuracy: 58.89% ║
╚═════════════════════════╝
─────────────────────────── Epoch 302/308 - Training ───────────────────────────
Epoch-Loss: 71.0289
────────────────────────── Epoch 302/308 - Validation ──────────────────────────
╔═ Epoch 302/308 Summary ═╗
║ Validation Loss: 1.5796 ║
║ Accuracy: 59.11% ║
╚═════════════════════════╝
─────────────────────────── Epoch 303/308 - Training ───────────────────────────
Epoch-Loss: 71.2466
────────────────────────── Epoch 303/308 - Validation ──────────────────────────
╔═ Epoch 303/308 Summary ═╗
║ Validation Loss: 1.5834 ║
║ Accuracy: 59.12% ║
╚═════════════════════════╝
─────────────────────────── Epoch 304/308 - Training ───────────────────────────
Epoch-Loss: 71.0606
────────────────────────── Epoch 304/308 - Validation ──────────────────────────
╔═ Epoch 304/308 Summary ═╗
║ Validation Loss: 1.5809 ║
║ Accuracy: 58.96% ║
╚═════════════════════════╝
─────────────────────────── Epoch 305/308 - Training ───────────────────────────
Epoch-Loss: 71.0147
────────────────────────── Epoch 305/308 - Validation ──────────────────────────
╔═ Epoch 305/308 Summary ═╗
║ Validation Loss: 1.5805 ║
║ Accuracy: 59.10% ║
╚═════════════════════════╝
─────────────────────────── Epoch 306/308 - Training ───────────────────────────
Epoch-Loss: 71.3946
────────────────────────── Epoch 306/308 - Validation ──────────────────────────
╔═ Epoch 306/308 Summary ═╗
║ Validation Loss: 1.5816 ║
║ Accuracy: 58.97% ║
╚═════════════════════════╝
─────────────────────────── Epoch 307/308 - Training ───────────────────────────
Epoch-Loss: 71.4225
────────────────────────── Epoch 307/308 - Validation ──────────────────────────
╔═ Epoch 307/308 Summary ═╗
║ Validation Loss: 1.5823 ║
║ Accuracy: 59.14% ║
╚═════════════════════════╝
─────────────────────────── Epoch 308/308 - Training ───────────────────────────
Epoch-Loss: 71.1800
────────────────────────── Epoch 308/308 - Validation ──────────────────────────
╔═ Epoch 308/308 Summary ═╗
║ Validation Loss: 1.5834 ║
║ Accuracy: 59.00% ║
╚═════════════════════════╝
VAL_LOSS: 1.5834157168865204
VAL_ACC: 59.0
RUNTIME: 3408.221
NORMALIZED_RUNTIME: 47.336
stderr:
/data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/.torch_venv_1bdd5e1e8b/lib64/python3.9/site-packages/torch/utils/data/dataloader.py:627: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 1, which is smaller than what this DataLoader is going to create. Please be aware that excessive worker creation might get DataLoader running slow or even freeze, lower the worker number to avoid potential slowness/freeze if necessary.
warnings.warn(
Result: {'VAL_ACC': 59.0}
Final-results: {'VAL_ACC': 59.0}
EXIT_CODE: 0
submitit INFO (2025-11-01 18:38:48,572) - Job completed successfully
submitit INFO (2025-11-01 18:38:48,574) - Exiting after successful completion