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 | RUNNING |
|---|
| SOBOL | 20 | 0 | 20 | 0 |
| BOTORCH_MODULAR | 401 | 16 | 366 | 19 |
Experiment parameters
| Name | Type | Lower bound | Upper bound | Type | Log Scale? |
|---|
| epochs | range | 20 | 300 | 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 |
| 0 |
386 |
19 |
421 |
Result names and types
Last progressbar status
2025-11-01 15:00:13 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 13 = ∑13/20, new result: VAL_ACC: 70.920000
Git-Version
Commit: b0be50d275c42846a83038bf3c24241d60ce4e7d (8949-3-gb0be50d27)
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
0,1761919446,1295,127c23cb-d119-4ecc-b801-d8b643248022,1761920741,1761923914,3173,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 263 --learning_rate 0.00047447446584701538 --batch_size 214 --hidden_size 974 --dropout 0.18813806772232055664 --num_dense_layers 2 --filter 127 --num_conv_layers 5,0,,c103,1205109,0_0,COMPLETED,SOBOL,65.89000000000000056843418860808,263,0.000474474465847015379471596219,214,974,0.188138067722320556640625,2,127,5
1,1761919450,1314,127c23cb-d119-4ecc-b801-d8b643248022,1761920764,1761921044,280,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 25 --learning_rate 0.00062518730089068414 --batch_size 557 --hidden_size 3511 --dropout 0.47498733643442392349 --num_dense_layers 1 --filter 32 --num_conv_layers 6,0,,c95,1205115,1_0,COMPLETED,SOBOL,47.909999999999996589394868351519,25,0.000625187300890684143246656124,557,3511,0.474987336434423923492431640625,1,32,6
2,1761919446,4,127c23cb-d119-4ecc-b801-d8b643248022,1761919450,1761920488,1038,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 92 --learning_rate 0.00025182953672483565 --batch_size 447 --hidden_size 1590 --dropout 0.37142576789483428001 --num_dense_layers 1 --filter 93 --num_conv_layers 7,0,,c64,1205102,2_0,COMPLETED,SOBOL,58.549999999999997157829056959599,92,0.000251829536724835654701304399,447,1590,0.371425767894834280014038085938,1,93,7
3,1761919446,68,127c23cb-d119-4ecc-b801-d8b643248022,1761919514,1761921492,1978,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 187 --learning_rate 0.00084807953722774987 --batch_size 834 --hidden_size 3141 --dropout 0.08845279226079583168 --num_dense_layers 2 --filter 62 --num_conv_layers 5,0,,c131,1205103,3_0,COMPLETED,SOBOL,57.840000000000003410605131648481,187,0.00084807953722774987153493198,834,3141,0.088452792260795831680297851562,2,62,5
4,1761919446,725,127c23cb-d119-4ecc-b801-d8b643248022,1761920171,1761922530,2359,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 213 --learning_rate 0.00012108744010329247 --batch_size 739 --hidden_size 2439 --dropout 0.05480971559882164001 --num_dense_layers 2 --filter 81 --num_conv_layers 7,0,,c146,1205105,4_0,COMPLETED,SOBOL,50.82999999999999829469743417576,213,0.000121087440103292474469047491,739,2439,0.0548097155988216400146484375,2,81,7
5,1761919446,9,127c23cb-d119-4ecc-b801-d8b643248022,1761919455,1761921103,1648,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 137 --learning_rate 0.00097925067329779261 --batch_size 156 --hidden_size 2285 --dropout 0.28016804065555334091 --num_dense_layers 1 --filter 49 --num_conv_layers 5,0,,c93,1205101,5_0,COMPLETED,SOBOL,62.92999999999999971578290569596,137,0.000979250673297792605109801656,156,2285,0.280168040655553340911865234375,1,49,5
6,1761919446,1305,127c23cb-d119-4ecc-b801-d8b643248022,1761920751,1761921493,742,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 68 --learning_rate 0.00034021691270172595 --batch_size 1016 --hidden_size 3710 --dropout 0.37970070866867899895 --num_dense_layers 1 --filter 112 --num_conv_layers 6,0,,c99,1205113,6_0,COMPLETED,SOBOL,60.3500000000000014210854715202,68,0.000340216912701725947548031526,1016,3710,0.379700708668678998947143554688,1,112,6
7,1761919447,1317,127c23cb-d119-4ecc-b801-d8b643248022,1761920764,1761923781,3017,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 291 --learning_rate 0.00075987412231042981 --batch_size 388 --hidden_size 782 --dropout 0.15827971743419766426 --num_dense_layers 2 --filter 16 --num_conv_layers 7,0,,c95,1205118,7_0,COMPLETED,SOBOL,43.57000000000000028421709430404,291,0.00075987412231042980592654601,388,782,0.158279717434197664260864257812,2,16,7
8,1761919446,1295,127c23cb-d119-4ecc-b801-d8b643248022,1761920741,1761923714,2973,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 281 --learning_rate 0.000297346952278167 --batch_size 948 --hidden_size 2052 --dropout 0.45920056058093905449 --num_dense_layers 2 --filter 76 --num_conv_layers 7,0,,c103,1205108,8_0,COMPLETED,SOBOL,53.119999999999997442046151263639,281,0.000297346952278167001894326749,948,2052,0.459200560580939054489135742188,2,76,7
9,1761919446,1295,127c23cb-d119-4ecc-b801-d8b643248022,1761920741,1761921594,853,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 77 --learning_rate 0.00080231149606406688 --batch_size 307 --hidden_size 2679 --dropout 0.2353400704450905323 --num_dense_layers 1 --filter 51 --num_conv_layers 5,0,,c103,1205110,9_0,COMPLETED,SOBOL,61.67000000000000170530256582424,77,0.000802311496064066881871157388,307,2679,0.235340070445090532302856445312,1,51,5
10,1761919446,1319,127c23cb-d119-4ecc-b801-d8b643248022,1761920765,1761922352,1587,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 145 --learning_rate 0.00052728364178910854 --batch_size 685 --hidden_size 512 --dropout 0.10428191721439361572 --num_dense_layers 1 --filter 102 --num_conv_layers 6,0,,c95,1205117,10_0,COMPLETED,SOBOL,60.85999999999999943156581139192,145,0.00052728364178910853803106118,685,512,0.10428191721439361572265625,1,102,6
11,1761919446,577,127c23cb-d119-4ecc-b801-d8b643248022,1761920023,1761922594,2571,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 204 --learning_rate 0.0005726218849420549 --batch_size 119 --hidden_size 3973 --dropout 0.32426724117249250412 --num_dense_layers 2 --filter 28 --num_conv_layers 7,0,,c107,1205104,11_0,COMPLETED,SOBOL,53.229999999999996873611962655559,204,0.000572621884942054902231656222,119,3973,0.324267241172492504119873046875,2,28,7
12,1761919446,1318,127c23cb-d119-4ecc-b801-d8b643248022,1761920764,1761922652,1888,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 160 --learning_rate 0.0004070911359041929 --batch_size 485 --hidden_size 3276 --dropout 0.29565384378656744957 --num_dense_layers 2 --filter 114 --num_conv_layers 5,0,,c95,1205116,12_0,COMPLETED,SOBOL,62.92999999999999971578290569596,160,0.000407091135904192897437825494,485,3276,0.295653843786567449569702148438,2,114,5
13,1761919446,1351,127c23cb-d119-4ecc-b801-d8b643248022,1761920797,1761922021,1224,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 119 --learning_rate 0.00069325052471831444 --batch_size 886 --hidden_size 1216 --dropout 0.00828442955389618874 --num_dense_layers 1 --filter 40 --num_conv_layers 6,0,,c69,1205120,13_0,COMPLETED,SOBOL,53.71999999999999886313162278384,119,0.00069325052471831444429739566,886,1216,0.008284429553896188735961914062,1,40,6
14,1761919446,1311,127c23cb-d119-4ecc-b801-d8b643248022,1761920757,1761921355,598,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 51 --learning_rate 0.00018066990375518798 --batch_size 297 --hidden_size 2873 --dropout 0.14288203977048397064 --num_dense_layers 1 --filter 92 --num_conv_layers 7,0,,c99,1205112,14_0,COMPLETED,SOBOL,57.57000000000000028421709430404,51,0.000180669903755187983510760441,297,2873,0.14288203977048397064208984375,1,92,7
15,1761919446,1305,127c23cb-d119-4ecc-b801-d8b643248022,1761920751,1761923311,2560,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 238 --learning_rate 0.00091942445049062371 --batch_size 623 --hidden_size 1851 --dropout 0.42631525266915559769 --num_dense_layers 2 --filter 67 --num_conv_layers 5,0,,c99,1205114,15_0,COMPLETED,SOBOL,61.060000000000002273736754432321,238,0.000919424450490623711672311114,623,1851,0.426315252669155597686767578125,2,67,5
16,1761919446,1295,127c23cb-d119-4ecc-b801-d8b643248022,1761920741,1761923285,2544,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 240 --learning_rate 0.00018742306064814328 --batch_size 358 --hidden_size 3842 --dropout 0.06308140605688095093 --num_dense_layers 1 --filter 35 --num_conv_layers 7,0,,c103,1205107,16_0,COMPLETED,SOBOL,48.07999999999999829469743417576,240,0.000187423060648143284100813899,358,3842,0.063081406056880950927734375,1,35,7
17,1761919446,1048,127c23cb-d119-4ecc-b801-d8b643248022,1761920494,1761920954,460,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 41 --learning_rate 0.00091292546978220346 --batch_size 926 --hidden_size 888 --dropout 0.34996126126497983932 --num_dense_layers 2 --filter 124 --num_conv_layers 5,0,,c64,1205106,17_0,COMPLETED,SOBOL,58.3999999999999985789145284798,41,0.000912925469782203458969649379,926,888,0.349961261264979839324951171875,2,124,5
18,1761919446,1311,127c23cb-d119-4ecc-b801-d8b643248022,1761920757,1761922441,1684,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 113 --learning_rate 0.00041451745349913835 --batch_size 66 --hidden_size 2306 --dropout 0.49649100704118609428 --num_dense_layers 2 --filter 59 --num_conv_layers 5,0,,c99,1205111,18_0,COMPLETED,SOBOL,64.049999999999997157829056959599,113,0.000414517453499138350137692699,66,2306,0.496491007041186094284057617188,2,59,5
19,1761919452,1359,127c23cb-d119-4ecc-b801-d8b643248022,1761920811,1761922768,1957,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 177 --learning_rate 0.0006855837705545128 --batch_size 709 --hidden_size 2179 --dropout 0.2135484856553375721 --num_dense_layers 1 --filter 98 --num_conv_layers 6,0,,c107,1205121,19_0,COMPLETED,SOBOL,63.3500000000000014210854715202,177,0.000685583770554512800590729604,709,2179,0.213548485655337572097778320312,1,98,6
20,1761923998,75,127c23cb-d119-4ecc-b801-d8b643248022,1761924073,1761927318,3245,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 300 --learning_rate 0.0008551374354164394 --batch_size 787 --hidden_size 4096 --dropout 0.33386897191983627708 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c151,1205196,20_0,COMPLETED,BOTORCH_MODULAR,66.5,300,0.000855137435416439403365607141,787,4096,0.333868971919836277084669973192,1,128,6
21,1761923998,149,127c23cb-d119-4ecc-b801-d8b643248022,1761924147,1761927389,3242,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 294 --learning_rate 0.00086661967216995035 --batch_size 772 --hidden_size 4091 --dropout 0.33464408961811814569 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c95,1205197,21_0,COMPLETED,BOTORCH_MODULAR,66.14000000000000056843418860808,294,0.000866619672169950346941880159,772,4091,0.334644089618118145690317533081,1,128,6
22,1761923998,319,127c23cb-d119-4ecc-b801-d8b643248022,1761924317,1761927543,3226,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 293 --learning_rate 0.00086832527939554032 --batch_size 775 --hidden_size 4096 --dropout 0.33397153859108619223 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c23,1205198,22_0,COMPLETED,BOTORCH_MODULAR,66.049999999999997157829056959599,293,0.000868325279395540318601309782,775,4096,0.333971538591086192226953244244,1,128,6
23,1761923998,990,127c23cb-d119-4ecc-b801-d8b643248022,1761924988,1761928443,3455,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 300 --learning_rate 0.00085335421256824107 --batch_size 769 --hidden_size 4096 --dropout 0.33469347332134957718 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c148,1205206,23_0,COMPLETED,BOTORCH_MODULAR,65.189999999999997726263245567679,300,0.000853354212568241073978703159,769,4096,0.334693473321349577176420098112,1,128,6
24,1761923998,827,127c23cb-d119-4ecc-b801-d8b643248022,1761924825,1761928043,3218,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 293 --learning_rate 0.00086790251081000078 --batch_size 772 --hidden_size 4096 --dropout 0.33393083948035084951 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c145,1205204,24_0,COMPLETED,BOTORCH_MODULAR,66.60999999999999943156581139192,293,0.000867902510810000782891238114,772,4096,0.333930839480350849513001776359,1,128,6
25,1761923999,416,127c23cb-d119-4ecc-b801-d8b643248022,1761924415,1761927630,3215,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 294 --learning_rate 0.00086602255642144195 --batch_size 772 --hidden_size 4096 --dropout 0.33412419533635351332 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c152,1205201,25_0,COMPLETED,BOTORCH_MODULAR,66.180000000000006821210263296962,294,0.000866022556421441945355421677,772,4096,0.334124195336353513319238572876,1,128,6
26,1761923998,989,127c23cb-d119-4ecc-b801-d8b643248022,1761924987,1761928289,3302,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 294 --learning_rate 0.00086635333577926609 --batch_size 772 --hidden_size 4096 --dropout 0.33435653659551811678 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c87,1205208,26_0,COMPLETED,BOTORCH_MODULAR,65.939999999999997726263245567679,294,0.000866353335779266090464767469,772,4096,0.334356536595518116783409823256,1,128,6
27,1761923998,468,127c23cb-d119-4ecc-b801-d8b643248022,1761924466,1761927869,3403,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 294 --learning_rate 0.00086668212795450346 --batch_size 772 --hidden_size 4096 --dropout 0.33467914843582324824 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c127,1205202,27_0,COMPLETED,BOTORCH_MODULAR,66.53000000000000113686837721616,294,0.00086668212795450345897751987,772,4096,0.334679148435823248242115823814,1,128,6
28,1761923998,363,127c23cb-d119-4ecc-b801-d8b643248022,1761924361,1761927754,3393,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 294 --learning_rate 0.00086635514730947752 --batch_size 772 --hidden_size 4096 --dropout 0.3343740216789342079 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c125,1205200,28_0,COMPLETED,BOTORCH_MODULAR,65.71999999999999886313162278384,294,0.000866355147309477518179077205,772,4096,0.334374021678934207901789932293,1,128,6
29,1761923998,4111,127c23cb-d119-4ecc-b801-d8b643248022,1761928109,1761931259,3150,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 291 --learning_rate 0.00087429375549759119 --batch_size 813 --hidden_size 4096 --dropout 0.33228958439576461448 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c64,1205213,29_0,COMPLETED,BOTORCH_MODULAR,66.14000000000000056843418860808,291,0.000874293755497591190163630959,813,4096,0.332289584395764614477286613692,1,128,6
30,1761923998,4071,127c23cb-d119-4ecc-b801-d8b643248022,1761928069,1761931234,3165,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 294 --learning_rate 0.00086523076513891244 --batch_size 771 --hidden_size 4096 --dropout 0.33339332770548002483 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c131,1205212,30_0,COMPLETED,BOTORCH_MODULAR,65.959999999999993747223925311118,294,0.000865230765138912442067942177,771,4096,0.3333933277054800248251353878,1,128,6
31,1761923998,4186,127c23cb-d119-4ecc-b801-d8b643248022,1761928184,1761931394,3210,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 294 --learning_rate 0.00086538635427973359 --batch_size 769 --hidden_size 4096 --dropout 0.33378986185575626466 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c107,1205214,31_0,COMPLETED,BOTORCH_MODULAR,64.769999999999996020960679743439,294,0.000865386354279733586124245814,769,4096,0.333789861855756264663597221443,1,128,6
32,1761923998,4004,127c23cb-d119-4ecc-b801-d8b643248022,1761928002,1761931194,3192,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 294 --learning_rate 0.00086629336869645474 --batch_size 772 --hidden_size 4096 --dropout 0.33437182855322766795 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c80,1205210,32_0,COMPLETED,BOTORCH_MODULAR,66.189999999999997726263245567679,294,0.000866293368696454736156697951,772,4096,0.334371828553227667946146084432,1,128,6
33,1761923998,969,127c23cb-d119-4ecc-b801-d8b643248022,1761924967,1761928179,3212,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 294 --learning_rate 0.00086642800884675398 --batch_size 772 --hidden_size 4096 --dropout 0.33453226665627383563 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c107,1205205,33_0,COMPLETED,BOTORCH_MODULAR,66.290000000000006252776074688882,294,0.00086642800884675398327000595,772,4096,0.334532266656273835625512447223,1,128,6
34,1761923998,4052,127c23cb-d119-4ecc-b801-d8b643248022,1761928050,1761931297,3247,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 294 --learning_rate 0.00086604062133805685 --batch_size 772 --hidden_size 4096 --dropout 0.33414432240399516427 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c145,1205211,34_0,COMPLETED,BOTORCH_MODULAR,66.069999999999993178789736703038,294,0.00086604062133805684731840957,772,4096,0.334144322403995164272316742426,1,128,6
35,1761923998,363,127c23cb-d119-4ecc-b801-d8b643248022,1761924361,1761927747,3386,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 300 --learning_rate 0.00085553022652836721 --batch_size 795 --hidden_size 4096 --dropout 0.33365125517683663636 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c125,1205199,35_0,COMPLETED,BOTORCH_MODULAR,65.650000000000005684341886080801,300,0.00085553022652836720716995611,795,4096,0.33365125517683663636248070361,1,128,6
36,1761923999,597,127c23cb-d119-4ecc-b801-d8b643248022,1761924596,1761927805,3209,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 294 --learning_rate 0.00086964212352134236 --batch_size 803 --hidden_size 4096 --dropout 0.33375647588483259298 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c146,1205203,36_0,COMPLETED,BOTORCH_MODULAR,66.069999999999993178789736703038,294,0.000869642123521342357700403269,803,4096,0.33375647588483259298186567321,1,128,6
37,1761923999,988,127c23cb-d119-4ecc-b801-d8b643248022,1761924987,1761928207,3220,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 296 --learning_rate 0.00087355046336602292 --batch_size 774 --hidden_size 3718 --dropout 0.34714284819204199728 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c87,1205207,37_0,COMPLETED,BOTORCH_MODULAR,66.46999999999999886313162278384,296,0.000873550463366022916095188222,774,3718,0.347142848192041997279488896311,1,128,6
38,1761923999,4003,127c23cb-d119-4ecc-b801-d8b643248022,1761928002,1761931319,3317,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 294 --learning_rate 0.00086586484774188726 --batch_size 772 --hidden_size 4096 --dropout 0.33397976808980595065 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c125,1205209,38_0,COMPLETED,BOTORCH_MODULAR,66.189999999999997726263245567679,294,0.000865864847741887257333293082,772,4096,0.333979768089805950648241150702,1,128,6
39,1761924004,4204,127c23cb-d119-4ecc-b801-d8b643248022,1761928208,1761931458,3250,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 295 --learning_rate 0.00086382956127585564 --batch_size 771 --hidden_size 4096 --dropout 0.33407962189818968257 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c130,1205215,39_0,COMPLETED,BOTORCH_MODULAR,66.07999999999999829469743417576,295,0.000863829561275855639657095253,771,4096,0.334079621898189682571711500714,1,128,6
40,1761931634,357,127c23cb-d119-4ecc-b801-d8b643248022,1761931991,1761934658,2667,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 247 --learning_rate 0.00100000000000000002 --batch_size 1024 --hidden_size 1693 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c86,1205911,40_0,COMPLETED,BOTORCH_MODULAR,64.42000000000000170530256582424,247,0.001000000000000000020816681712,1024,1693,0.5,1,128,6
41,1761931635,892,127c23cb-d119-4ecc-b801-d8b643248022,1761932527,1761935231,2704,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 248 --learning_rate 0.00100000000000000002 --batch_size 1024 --hidden_size 1727 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c145,1205923,41_0,COMPLETED,BOTORCH_MODULAR,64.42000000000000170530256582424,248,0.001000000000000000020816681712,1024,1727,0.5,1,128,6
42,1761931635,501,127c23cb-d119-4ecc-b801-d8b643248022,1761932136,1761934815,2679,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 247 --learning_rate 0.00100000000000000002 --batch_size 1024 --hidden_size 1430 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c79,1205914,42_0,COMPLETED,BOTORCH_MODULAR,64.099999999999994315658113919199,247,0.001000000000000000020816681712,1024,1430,0.5,1,128,6
43,1761931634,442,127c23cb-d119-4ecc-b801-d8b643248022,1761932076,1761934757,2681,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 247 --learning_rate 0.00100000000000000002 --batch_size 1024 --hidden_size 1740 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c148,1205912,43_0,COMPLETED,BOTORCH_MODULAR,64.379999999999995452526491135359,247,0.001000000000000000020816681712,1024,1740,0.5,1,128,6
44,1761931635,922,127c23cb-d119-4ecc-b801-d8b643248022,1761932557,1761935280,2723,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 246 --learning_rate 0.00100000000000000002 --batch_size 1024 --hidden_size 1858 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c125,1205924,44_0,COMPLETED,BOTORCH_MODULAR,64.549999999999997157829056959599,246,0.001000000000000000020816681712,1024,1858,0.5,1,128,6
45,1761931640,1098,127c23cb-d119-4ecc-b801-d8b643248022,1761932738,1761935446,2708,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 247 --learning_rate 0.00100000000000000002 --batch_size 1024 --hidden_size 1614 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c95,1205927,45_0,COMPLETED,BOTORCH_MODULAR,63.740000000000001989519660128281,247,0.001000000000000000020816681712,1024,1614,0.5,1,128,6
46,1761931634,351,127c23cb-d119-4ecc-b801-d8b643248022,1761931985,1761934658,2673,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 246 --learning_rate 0.00100000000000000002 --batch_size 1024 --hidden_size 1737 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c149,1205910,46_0,COMPLETED,BOTORCH_MODULAR,64.32999999999999829469743417576,246,0.001000000000000000020816681712,1024,1737,0.5,1,128,6
47,1761931635,741,127c23cb-d119-4ecc-b801-d8b643248022,1761932376,1761935038,2662,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 245 --learning_rate 0.00100000000000000002 --batch_size 1024 --hidden_size 1745 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c103,1205921,47_0,COMPLETED,BOTORCH_MODULAR,64.299999999999997157829056959599,245,0.001000000000000000020816681712,1024,1745,0.5,1,128,6
48,1761931635,471,127c23cb-d119-4ecc-b801-d8b643248022,1761932106,1761934737,2631,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 245 --learning_rate 0.00100000000000000002 --batch_size 1024 --hidden_size 1802 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c95,1205913,48_0,COMPLETED,BOTORCH_MODULAR,64.629999999999995452526491135359,245,0.001000000000000000020816681712,1024,1802,0.5,1,128,6
49,1761931635,742,127c23cb-d119-4ecc-b801-d8b643248022,1761932377,1761935045,2668,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 246 --learning_rate 0.00100000000000000002 --batch_size 1024 --hidden_size 1731 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c131,1205920,49_0,COMPLETED,BOTORCH_MODULAR,63.89000000000000056843418860808,246,0.001000000000000000020816681712,1024,1731,0.5,1,128,6
50,1761931635,591,127c23cb-d119-4ecc-b801-d8b643248022,1761932226,1761935072,2846,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 246 --learning_rate 0.00100000000000000002 --batch_size 1024 --hidden_size 1690 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c127,1205915,50_0,COMPLETED,BOTORCH_MODULAR,64.28000000000000113686837721616,246,0.001000000000000000020816681712,1024,1690,0.5,1,128,6
51,1761931635,952,127c23cb-d119-4ecc-b801-d8b643248022,1761932587,1761935245,2658,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 246 --learning_rate 0.00100000000000000002 --batch_size 1024 --hidden_size 1801 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c107,1205925,51_0,COMPLETED,BOTORCH_MODULAR,64.180000000000006821210263296962,246,0.001000000000000000020816681712,1024,1801,0.5,1,128,6
52,1761931641,1157,127c23cb-d119-4ecc-b801-d8b643248022,1761932798,1761935446,2648,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 246 --learning_rate 0.00100000000000000002 --batch_size 1024 --hidden_size 1729 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c64,1205928,52_0,COMPLETED,BOTORCH_MODULAR,65.099999999999994315658113919199,246,0.001000000000000000020816681712,1024,1729,0.5,1,128,6
53,1761931635,591,127c23cb-d119-4ecc-b801-d8b643248022,1761932226,1761934944,2718,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 247 --learning_rate 0.00100000000000000002 --batch_size 1024 --hidden_size 1655 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c69,1205918,53_0,COMPLETED,BOTORCH_MODULAR,64.260000000000005115907697472721,247,0.001000000000000000020816681712,1024,1655,0.5,1,128,6
54,1761931635,591,127c23cb-d119-4ecc-b801-d8b643248022,1761932226,1761934915,2689,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 247 --learning_rate 0.00100000000000000002 --batch_size 1024 --hidden_size 1678 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c79,1205917,54_0,COMPLETED,BOTORCH_MODULAR,63.939999999999997726263245567679,247,0.001000000000000000020816681712,1024,1678,0.5,1,128,6
55,1761931635,591,127c23cb-d119-4ecc-b801-d8b643248022,1761932226,1761934938,2712,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 246 --learning_rate 0.00100000000000000002 --batch_size 1024 --hidden_size 1866 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c99,1205916,55_0,COMPLETED,BOTORCH_MODULAR,64.78000000000000113686837721616,246,0.001000000000000000020816681712,1024,1866,0.5,1,128,6
56,1761931636,621,127c23cb-d119-4ecc-b801-d8b643248022,1761932257,1761935464,3207,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 247 --learning_rate 0.00100000000000000002 --batch_size 1024 --hidden_size 1621 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c85,1205919,56_0,COMPLETED,BOTORCH_MODULAR,64.28000000000000113686837721616,247,0.001000000000000000020816681712,1024,1621,0.5,1,128,6
57,1761931636,891,127c23cb-d119-4ecc-b801-d8b643248022,1761932527,1761935164,2637,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 246 --learning_rate 0.00100000000000000002 --batch_size 1024 --hidden_size 1732 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c152,1205922,57_0,COMPLETED,BOTORCH_MODULAR,64.28000000000000113686837721616,246,0.001000000000000000020816681712,1024,1732,0.5,1,128,6
58,1761931637,980,127c23cb-d119-4ecc-b801-d8b643248022,1761932617,1761935272,2655,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 248 --learning_rate 0.00100000000000000002 --batch_size 1024 --hidden_size 1684 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c152,1205926,58_0,COMPLETED,BOTORCH_MODULAR,64.75,248,0.001000000000000000020816681712,1024,1684,0.5,1,128,6
59,1761931641,1217,127c23cb-d119-4ecc-b801-d8b643248022,1761932858,1761935483,2625,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 246 --learning_rate 0.00100000000000000002 --batch_size 1024 --hidden_size 1911 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c85,1205929,59_0,COMPLETED,BOTORCH_MODULAR,64,246,0.001000000000000000020816681712,1024,1911,0.5,1,128,6
60,1761935585,943,127c23cb-d119-4ecc-b801-d8b643248022,1761936528,1761939801,3273,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 247 --learning_rate 0.0001 --batch_size 103 --hidden_size 726 --dropout 0.44092796428054731317 --num_dense_layers 1 --filter 119 --num_conv_layers 5,0,,c143,1206012,60_0,COMPLETED,BOTORCH_MODULAR,59.979999999999996873611962655559,247,0.000100000000000000004792173602,103,726,0.440927964280547313169478229611,1,119,5
61,1761935586,1063,127c23cb-d119-4ecc-b801-d8b643248022,1761936649,1761940361,3712,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 245 --learning_rate 0.0001 --batch_size 64 --hidden_size 1484 --dropout 0.41054020095503679366 --num_dense_layers 1 --filter 117 --num_conv_layers 5,0,,c61,1206026,61_0,COMPLETED,BOTORCH_MODULAR,63.090000000000003410605131648481,245,0.000100000000000000004792173602,64,1484,0.410540200955036793661889760187,1,117,5
62,1761935585,973,127c23cb-d119-4ecc-b801-d8b643248022,1761936558,1761940199,3641,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 249 --learning_rate 0.0001 --batch_size 64 --hidden_size 512 --dropout 0.39226539867324028421 --num_dense_layers 1 --filter 108 --num_conv_layers 5,0,,c119,1206015,62_0,COMPLETED,BOTORCH_MODULAR,60.799999999999997157829056959599,249,0.000100000000000000004792173602,64,512,0.392265398673240284210805839393,1,108,5
63,1761935585,932,127c23cb-d119-4ecc-b801-d8b643248022,1761936517,1761939703,3186,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 218 --learning_rate 0.0001 --batch_size 64 --hidden_size 518 --dropout 0.36765908984623740796 --num_dense_layers 1 --filter 108 --num_conv_layers 5,0,,c70,1206011,63_0,COMPLETED,BOTORCH_MODULAR,60.57000000000000028421709430404,218,0.000100000000000000004792173602,64,518,0.367659089846237407961382359645,1,108,5
64,1761935585,927,127c23cb-d119-4ecc-b801-d8b643248022,1761936512,1761940119,3607,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 242 --learning_rate 0.0001 --batch_size 64 --hidden_size 1359 --dropout 0.40108989671182843084 --num_dense_layers 1 --filter 111 --num_conv_layers 5,0,,c118,1206009,64_0,COMPLETED,BOTORCH_MODULAR,62.53000000000000113686837721616,242,0.000100000000000000004792173602,64,1359,0.401089896711828430841961790065,1,111,5
65,1761935585,973,127c23cb-d119-4ecc-b801-d8b643248022,1761936558,1761939924,3366,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 225 --learning_rate 0.0001 --batch_size 64 --hidden_size 837 --dropout 0.38217033189452731534 --num_dense_layers 1 --filter 110 --num_conv_layers 5,0,,c61,1206017,65_0,COMPLETED,BOTORCH_MODULAR,61.979999999999996873611962655559,225,0.000100000000000000004792173602,64,837,0.382170331894527315341747453203,1,110,5
66,1761935585,933,127c23cb-d119-4ecc-b801-d8b643248022,1761936518,1761940208,3690,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 244 --learning_rate 0.0001 --batch_size 64 --hidden_size 1569 --dropout 0.40749603873240919372 --num_dense_layers 1 --filter 111 --num_conv_layers 5,0,,c104,1206010,66_0,COMPLETED,BOTORCH_MODULAR,62.39000000000000056843418860808,244,0.000100000000000000004792173602,64,1569,0.407496038732409193716677009434,1,111,5
67,1761935586,1031,127c23cb-d119-4ecc-b801-d8b643248022,1761936617,1761940017,3400,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 233 --learning_rate 0.0001 --batch_size 64 --hidden_size 1072 --dropout 0.38721853549392737381 --num_dense_layers 1 --filter 108 --num_conv_layers 5,0,,c21,1206022,67_0,COMPLETED,BOTORCH_MODULAR,62.14000000000000056843418860808,233,0.000100000000000000004792173602,64,1072,0.387218535493927373813960457483,1,108,5
68,1761935585,967,127c23cb-d119-4ecc-b801-d8b643248022,1761936552,1761940093,3541,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 226 --learning_rate 0.0001 --batch_size 64 --hidden_size 1307 --dropout 0.39890091333521987549 --num_dense_layers 1 --filter 113 --num_conv_layers 5,0,,c23,1206018,68_0,COMPLETED,BOTORCH_MODULAR,63.1000000000000014210854715202,226,0.000100000000000000004792173602,64,1307,0.398900913335219875488490970383,1,113,5
69,1761935585,1009,127c23cb-d119-4ecc-b801-d8b643248022,1761936594,1761940405,3811,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 248 --learning_rate 0.00011112358573938562 --batch_size 64 --hidden_size 1604 --dropout 0.45323693304661749615 --num_dense_layers 1 --filter 127 --num_conv_layers 5,0,,c67,1206020,69_0,COMPLETED,BOTORCH_MODULAR,64.200000000000002842170943040401,248,0.000111123585739385623890468358,64,1604,0.453236933046617496145813674957,1,127,5
70,1761935585,973,127c23cb-d119-4ecc-b801-d8b643248022,1761936558,1761940300,3742,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 246 --learning_rate 0.0001 --batch_size 64 --hidden_size 1471 --dropout 0.41604606396247023614 --num_dense_layers 1 --filter 119 --num_conv_layers 5,0,,c77,1206016,70_0,COMPLETED,BOTORCH_MODULAR,63.340000000000003410605131648481,246,0.000100000000000000004792173602,64,1471,0.416046063962470236141655277606,1,119,5
71,1761935585,949,127c23cb-d119-4ecc-b801-d8b643248022,1761936534,1761939790,3256,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 220 --learning_rate 0.0001 --batch_size 64 --hidden_size 569 --dropout 0.38155312074621255958 --num_dense_layers 1 --filter 111 --num_conv_layers 5,0,,c45,1206014,71_0,COMPLETED,BOTORCH_MODULAR,60.759999999999998010480339871719,220,0.000100000000000000004792173602,64,569,0.38155312074621255957751486676,1,111,5
72,1761935585,1027,127c23cb-d119-4ecc-b801-d8b643248022,1761936612,1761940216,3604,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 240 --learning_rate 0.0001 --batch_size 64 --hidden_size 875 --dropout 0.38884520131101502072 --num_dense_layers 1 --filter 109 --num_conv_layers 5,0,,c64,1206021,72_0,COMPLETED,BOTORCH_MODULAR,61.57999999999999829469743417576,240,0.000100000000000000004792173602,64,875,0.388845201311015020717576362586,1,109,5
73,1761935586,1062,127c23cb-d119-4ecc-b801-d8b643248022,1761936648,1761940343,3695,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 249 --learning_rate 0.00010209580670763042 --batch_size 64 --hidden_size 1586 --dropout 0.45725052592273057739 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c67,1206025,73_0,COMPLETED,BOTORCH_MODULAR,63.96999999999999886313162278384,249,0.000102095806707630415194505702,64,1586,0.457250525922730577388364281433,1,128,5
74,1761935585,943,127c23cb-d119-4ecc-b801-d8b643248022,1761936528,1761939698,3170,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 203 --learning_rate 0.0001 --batch_size 64 --hidden_size 1359 --dropout 0.39274162264191103677 --num_dense_layers 1 --filter 114 --num_conv_layers 5,0,,c85,1206013,74_0,COMPLETED,BOTORCH_MODULAR,63.39000000000000056843418860808,203,0.000100000000000000004792173602,64,1359,0.392741622641911036772910392756,1,114,5
75,1761935585,999,127c23cb-d119-4ecc-b801-d8b643248022,1761936584,1761939987,3403,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 224 --learning_rate 0.0001 --batch_size 64 --hidden_size 771 --dropout 0.38082519593607183639 --num_dense_layers 1 --filter 109 --num_conv_layers 5,0,,c120,1206019,75_0,COMPLETED,BOTORCH_MODULAR,61.46000000000000085265128291212,224,0.000100000000000000004792173602,64,771,0.380825195936071836388947531304,1,109,5
76,1761935587,1036,127c23cb-d119-4ecc-b801-d8b643248022,1761936623,1761939769,3146,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 212 --learning_rate 0.0001 --batch_size 64 --hidden_size 793 --dropout 0.37283111227276072297 --num_dense_layers 1 --filter 109 --num_conv_layers 5,0,,c18,1206023,76_0,COMPLETED,BOTORCH_MODULAR,61.1000000000000014210854715202,212,0.000100000000000000004792173602,64,793,0.372831112272760722969877633659,1,109,5
77,1761935587,1067,127c23cb-d119-4ecc-b801-d8b643248022,1761936654,1761940339,3685,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 245 --learning_rate 0.0001 --batch_size 64 --hidden_size 1487 --dropout 0.41427242198397795647 --num_dense_layers 1 --filter 118 --num_conv_layers 5,0,,c75,1206024,77_0,COMPLETED,BOTORCH_MODULAR,63.6000000000000014210854715202,245,0.000100000000000000004792173602,64,1487,0.414272421983977956472244841279,1,118,5
78,1761935587,1061,127c23cb-d119-4ecc-b801-d8b643248022,1761936648,1761940096,3448,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 238 --learning_rate 0.0001 --batch_size 64 --hidden_size 853 --dropout 0.40088185993592895251 --num_dense_layers 1 --filter 112 --num_conv_layers 5,0,,c4,1206027,78_0,COMPLETED,BOTORCH_MODULAR,61.71999999999999886313162278384,238,0.000100000000000000004792173602,64,853,0.400881859935928952509698319773,1,112,5
79,1761935591,1067,127c23cb-d119-4ecc-b801-d8b643248022,1761936658,1761940240,3582,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 236 --learning_rate 0.0001 --batch_size 64 --hidden_size 1708 --dropout 0.39881217156320808437 --num_dense_layers 1 --filter 110 --num_conv_layers 5,0,,c110,1206028,79_0,COMPLETED,BOTORCH_MODULAR,62.939999999999997726263245567679,236,0.000100000000000000004792173602,64,1708,0.398812171563208084368312711376,1,110,5
80,1761940535,85,127c23cb-d119-4ecc-b801-d8b643248022,1761940620,1761942468,1848,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 115 --learning_rate 0.00057319828153422749 --batch_size 64 --hidden_size 2376 --dropout 0.1600398941868081959 --num_dense_layers 2 --filter 127 --num_conv_layers 5,0,,c64,1206476,80_0,COMPLETED,BOTORCH_MODULAR,68.620000000000004547473508864641,115,0.00057319828153422748649031826,64,2376,0.160039894186808195897242512729,2,127,5
81,1761940535,75,127c23cb-d119-4ecc-b801-d8b643248022,1761940610,1761942491,1881,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 116 --learning_rate 0.00057340840637636536 --batch_size 64 --hidden_size 2375 --dropout 0.16101099037372984535 --num_dense_layers 2 --filter 127 --num_conv_layers 5,0,,c119,1206468,81_0,COMPLETED,BOTORCH_MODULAR,68.82999999999999829469743417576,116,0.000573408406376365361450941904,64,2375,0.161010990373729845348549361006,2,127,5
82,1761940535,75,127c23cb-d119-4ecc-b801-d8b643248022,1761940610,1761942434,1824,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 114 --learning_rate 0.00057762171095252217 --batch_size 64 --hidden_size 2385 --dropout 0.16128626080217248195 --num_dense_layers 2 --filter 126 --num_conv_layers 5,0,,c145,1206466,82_0,COMPLETED,BOTORCH_MODULAR,68.35999999999999943156581139192,114,0.000577621710952522173128376171,64,2385,0.161286260802172481954031013629,2,126,5
83,1761940535,87,127c23cb-d119-4ecc-b801-d8b643248022,1761940622,1761942507,1885,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 115 --learning_rate 0.00057315158868595549 --batch_size 64 --hidden_size 2375 --dropout 0.15950293451531694089 --num_dense_layers 2 --filter 127 --num_conv_layers 5,0,,c115,1206469,83_0,COMPLETED,BOTORCH_MODULAR,67.82999999999999829469743417576,115,0.000573151588685955493823742657,64,2375,0.159502934515316940888851604541,2,127,5
84,1761940535,75,127c23cb-d119-4ecc-b801-d8b643248022,1761940610,1761942479,1869,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 115 --learning_rate 0.00057259586400214507 --batch_size 64 --hidden_size 2374 --dropout 0.16068350051354282626 --num_dense_layers 2 --filter 127 --num_conv_layers 5,0,,c104,1206471,84_0,COMPLETED,BOTORCH_MODULAR,68.89000000000000056843418860808,115,0.000572595864002145072714500262,64,2374,0.160683500513542826260149354312,2,127,5
85,1761940535,75,127c23cb-d119-4ecc-b801-d8b643248022,1761940610,1761942617,2007,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 124 --learning_rate 0.00058234882701489559 --batch_size 64 --hidden_size 2278 --dropout 0.15571658171269428528 --num_dense_layers 2 --filter 126 --num_conv_layers 5,0,,c67,1206474,85_0,COMPLETED,BOTORCH_MODULAR,68.42000000000000170530256582424,124,0.000582348827014895586810794281,64,2278,0.155716581712694285277720496197,2,126,5
86,1761940535,75,127c23cb-d119-4ecc-b801-d8b643248022,1761940610,1761942431,1821,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 117 --learning_rate 0.00056995406243990677 --batch_size 64 --hidden_size 2359 --dropout 0.1593587905240855529 --num_dense_layers 2 --filter 128 --num_conv_layers 5,0,,c76,1206473,86_0,COMPLETED,BOTORCH_MODULAR,68.040000000000006252776074688882,117,0.000569954062439906772481734709,64,2359,0.159358790524085552897659567861,2,128,5
87,,,,,,,,,,,,87_0,RUNNING,BOTORCH_MODULAR,,115,0.000580558086038064375539180517,64,2267,0.155930491009816346581473567312,2,126,5
88,,,,,,,,,,,,88_0,RUNNING,BOTORCH_MODULAR,,115,0.000569280964603561872791614995,64,2383,0.160677392226324877722021255977,2,128,5
89,1761940535,75,127c23cb-d119-4ecc-b801-d8b643248022,1761940610,1761942435,1825,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 116 --learning_rate 0.00056883417832654997 --batch_size 64 --hidden_size 2381 --dropout 0.16062147133368678831 --num_dense_layers 2 --filter 128 --num_conv_layers 5,0,,c77,1206472,89_0,COMPLETED,BOTORCH_MODULAR,68.120000000000004547473508864641,116,0.000568834178326549973897519052,64,2381,0.160621471333686788307559822897,2,128,5
90,1761940535,80,127c23cb-d119-4ecc-b801-d8b643248022,1761940615,1761942390,1775,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 110 --learning_rate 0.00057874507296779725 --batch_size 64 --hidden_size 2340 --dropout 0.15940907419613326024 --num_dense_layers 2 --filter 126 --num_conv_layers 5,0,,c66,1206475,90_0,COMPLETED,BOTORCH_MODULAR,68.28000000000000113686837721616,110,0.000578745072967797253085664444,64,2340,0.159409074196133260237218109978,2,126,5
91,1761940536,84,127c23cb-d119-4ecc-b801-d8b643248022,1761940620,1761942500,1880,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 115 --learning_rate 0.00057290767821239 --batch_size 64 --hidden_size 2373 --dropout 0.16015423895575967017 --num_dense_layers 2 --filter 127 --num_conv_layers 5,0,,c40,1206478,91_0,COMPLETED,BOTORCH_MODULAR,68.099999999999994315658113919199,115,0.000572907678212389998018139181,64,2373,0.160154238955759670171019592999,2,127,5
92,1761940535,75,127c23cb-d119-4ecc-b801-d8b643248022,1761940610,1761942534,1924,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 116 --learning_rate 0.00057280818212160638 --batch_size 64 --hidden_size 2372 --dropout 0.16156371645647210622 --num_dense_layers 2 --filter 127 --num_conv_layers 5,0,,c123,1206467,92_0,COMPLETED,BOTORCH_MODULAR,68.689999999999997726263245567679,116,0.000572808182121606378547906679,64,2372,0.161563716456472106219877105104,2,127,5
93,1761940536,94,127c23cb-d119-4ecc-b801-d8b643248022,1761940630,1761942460,1830,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 116 --learning_rate 0.00056849267178144642 --batch_size 64 --hidden_size 2381 --dropout 0.16074763191272800622 --num_dense_layers 2 --filter 128 --num_conv_layers 5,0,,c118,1206479,93_0,COMPLETED,BOTORCH_MODULAR,68.019999999999996020960679743439,116,0.000568492671781446420355143889,64,2381,0.160747631912728006220447696251,2,128,5
94,1761940535,75,127c23cb-d119-4ecc-b801-d8b643248022,1761940610,1761942432,1822,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 116 --learning_rate 0.00057006037673566778 --batch_size 64 --hidden_size 2385 --dropout 0.15903173887459301494 --num_dense_layers 2 --filter 128 --num_conv_layers 5,0,,c104,1206470,94_0,COMPLETED,BOTORCH_MODULAR,68.040000000000006252776074688882,116,0.000570060376735667781629424145,64,2385,0.159031738874593014942959712243,2,128,5
95,1761940535,90,127c23cb-d119-4ecc-b801-d8b643248022,1761940625,1761942462,1837,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 116 --learning_rate 0.0005695212671830537 --batch_size 64 --hidden_size 2380 --dropout 0.16079145546364065344 --num_dense_layers 2 --filter 128 --num_conv_layers 5,0,,c41,1206477,95_0,COMPLETED,BOTORCH_MODULAR,68.310000000000002273736754432321,116,0.000569521267183053700976225198,64,2380,0.160791455463640653444912231862,2,128,5
96,1761940591,79,127c23cb-d119-4ecc-b801-d8b643248022,1761940670,1761942531,1861,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 116 --learning_rate 0.00057418448375078015 --batch_size 64 --hidden_size 2367 --dropout 0.16005407869242910257 --num_dense_layers 2 --filter 127 --num_conv_layers 5,0,,c115,1206483,96_0,COMPLETED,BOTORCH_MODULAR,68.060000000000002273736754432321,116,0.000574184483750780146234238277,64,2367,0.160054078692429102570571330943,2,127,5
97,1761940591,84,127c23cb-d119-4ecc-b801-d8b643248022,1761940675,1761942531,1856,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 115 --learning_rate 0.00057534318812375754 --batch_size 64 --hidden_size 2373 --dropout 0.15999455060649417359 --num_dense_layers 2 --filter 127 --num_conv_layers 5,0,,c114,1206485,97_0,COMPLETED,BOTORCH_MODULAR,68.07999999999999829469743417576,115,0.00057534318812375753564303249,64,2373,0.15999455060649417359464052879,2,127,5
98,1761940591,84,127c23cb-d119-4ecc-b801-d8b643248022,1761940675,1761942486,1811,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 115 --learning_rate 0.00057053956359457943 --batch_size 64 --hidden_size 2382 --dropout 0.15987414156819901301 --num_dense_layers 2 --filter 128 --num_conv_layers 5,0,,c115,1206484,98_0,COMPLETED,BOTORCH_MODULAR,68.269999999999996020960679743439,115,0.000570539563594579433002118574,64,2382,0.159874141568199013008211295528,2,128,5
99,1761940591,84,127c23cb-d119-4ecc-b801-d8b643248022,1761940675,1761942544,1869,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 114 --learning_rate 0.00057649274832104029 --batch_size 64 --hidden_size 2379 --dropout 0.15954401302357593129 --num_dense_layers 2 --filter 127 --num_conv_layers 5,0,,c114,1206486,99_0,COMPLETED,BOTORCH_MODULAR,67.959999999999993747223925311118,114,0.000576492748321040288268790608,64,2379,0.15954401302357593128711243935,2,127,5
100,1761942720,9,127c23cb-d119-4ecc-b801-d8b643248022,1761942729,1761944172,1443,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 93 --learning_rate 0.0007663903749987825 --batch_size 64 --hidden_size 2144 --dropout 0.13495464118028485667 --num_dense_layers 1 --filter 117 --num_conv_layers 5,0,,c146,1206547,100_0,COMPLETED,BOTORCH_MODULAR,69.549999999999997157829056959599,93,0.000766390374998782500370886339,64,2144,0.134954641180284856671889315294,1,117,5
101,1761942720,29,127c23cb-d119-4ecc-b801-d8b643248022,1761942749,1761946612,3863,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 274 --learning_rate 0.00078197282999096704 --batch_size 95 --hidden_size 2067 --dropout 0.17199956173759783917 --num_dense_layers 2 --filter 106 --num_conv_layers 5,0,,c118,1206556,101_0,COMPLETED,BOTORCH_MODULAR,67.709999999999993747223925311118,274,0.000781972829990967041417782024,95,2067,0.171999561737597839172764224713,2,106,5
102,1761942720,30,127c23cb-d119-4ecc-b801-d8b643248022,1761942750,1761944807,2057,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 134 --learning_rate 0.00078813222127181444 --batch_size 64 --hidden_size 2106 --dropout 0.10995342191119673869 --num_dense_layers 1 --filter 114 --num_conv_layers 5,0,,c145,1206549,102_0,COMPLETED,BOTORCH_MODULAR,68.599999999999994315658113919199,134,0.000788132221271814438143255011,64,2106,0.109953421911196738691707253111,1,114,5
103,1761942720,29,127c23cb-d119-4ecc-b801-d8b643248022,1761942749,1761944575,1826,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 109 --learning_rate 0.00075473422651379878 --batch_size 64 --hidden_size 1627 --dropout 0.14325127697675030247 --num_dense_layers 2 --filter 107 --num_conv_layers 5,0,,c146,1206548,103_0,COMPLETED,BOTORCH_MODULAR,67.290000000000006252776074688882,109,0.000754734226513798780663910826,64,1627,0.143251276976750302472041198598,2,107,5
104,1761942720,49,127c23cb-d119-4ecc-b801-d8b643248022,1761942769,1761944905,2136,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 139 --learning_rate 0.00078333034238531069 --batch_size 64 --hidden_size 2123 --dropout 0.14937719262477247573 --num_dense_layers 1 --filter 117 --num_conv_layers 5,0,,c118,1206557,104_0,COMPLETED,BOTORCH_MODULAR,69.28000000000000113686837721616,139,0.00078333034238531069198829826,64,2123,0.149377192624772475726402376495,1,117,5
105,1761942720,29,127c23cb-d119-4ecc-b801-d8b643248022,1761942749,1761945433,2684,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 178 --learning_rate 0.00071562652127681362 --batch_size 64 --hidden_size 2222 --dropout 0.11313939787723575892 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c119,1206554,105_0,COMPLETED,BOTORCH_MODULAR,69.730000000000003979039320256561,178,0.000715626521276813620450751863,64,2222,0.113139397877235758915759333831,1,128,5
106,1761942721,68,127c23cb-d119-4ecc-b801-d8b643248022,1761942789,1761945011,2222,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 147 --learning_rate 0.00070819737824904692 --batch_size 64 --hidden_size 2248 --dropout 0.09142454039288716583 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c115,1206560,106_0,COMPLETED,BOTORCH_MODULAR,69.400000000000005684341886080801,147,0.00070819737824904692088945346,64,2248,0.091424540392887165829449713783,1,128,5
107,1761942720,54,127c23cb-d119-4ecc-b801-d8b643248022,1761942774,1761945279,2505,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 157 --learning_rate 0.0007697062796932719 --batch_size 64 --hidden_size 2093 --dropout 0.36165839636793362111 --num_dense_layers 2 --filter 112 --num_conv_layers 5,0,,c117,1206558,107_0,COMPLETED,BOTORCH_MODULAR,69.5,157,0.000769706279693271899246254097,64,2093,0.361658396367933621107226827007,2,112,5
108,1761942720,29,127c23cb-d119-4ecc-b801-d8b643248022,1761942749,1761947438,4689,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 300 --learning_rate 0.00076527206885422495 --batch_size 64 --hidden_size 1991 --dropout 0.15123669203502973502 --num_dense_layers 2 --filter 102 --num_conv_layers 5,0,,c131,1206550,108_0,COMPLETED,BOTORCH_MODULAR,67.439999999999997726263245567679,300,0.000765272068854224948343534241,64,1991,0.1512366920350297350150725606,2,102,5
109,1761942720,34,127c23cb-d119-4ecc-b801-d8b643248022,1761942754,1761945181,2427,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 159 --learning_rate 0.00078440950763177095 --batch_size 64 --hidden_size 2099 --dropout 0.10892189690834556959 --num_dense_layers 1 --filter 114 --num_conv_layers 5,0,,c131,1206551,109_0,COMPLETED,BOTORCH_MODULAR,68.450000000000002842170943040401,159,0.000784409507631770946088634044,64,2099,0.108921896908345569587872603279,1,114,5
110,1761942720,30,127c23cb-d119-4ecc-b801-d8b643248022,1761942750,1761945128,2378,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 148 --learning_rate 0.00073705312051935013 --batch_size 64 --hidden_size 2101 --dropout 0.41715211817121600202 --num_dense_layers 2 --filter 114 --num_conv_layers 5,0,,c118,1206555,110_0,COMPLETED,BOTORCH_MODULAR,69.659999999999996589394868351519,148,0.000737053120519350134058622626,64,2101,0.41715211817121600201829778598,2,114,5
111,1761942720,29,127c23cb-d119-4ecc-b801-d8b643248022,1761942749,1761945388,2639,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 189 --learning_rate 0.00082984019806066703 --batch_size 93 --hidden_size 1551 --dropout 0.16578801790325567445 --num_dense_layers 2 --filter 100 --num_conv_layers 5,0,,c123,1206553,111_0,COMPLETED,BOTORCH_MODULAR,67.230000000000003979039320256561,189,0.000829840198060667025466152769,93,1551,0.165788017903255674445617273705,2,100,5
112,1761942721,66,127c23cb-d119-4ecc-b801-d8b643248022,1761942787,1761945137,2350,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 151 --learning_rate 0.00075968713000701155 --batch_size 64 --hidden_size 1942 --dropout 0.35909868479508977313 --num_dense_layers 2 --filter 111 --num_conv_layers 5,0,,c115,1206561,112_0,COMPLETED,BOTORCH_MODULAR,69.739999999999994884092302527279,151,0.000759687130007011550587858739,64,1942,0.359098684795089773125198462367,2,111,5
113,1761942721,48,127c23cb-d119-4ecc-b801-d8b643248022,1761942769,1761944680,1911,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 126 --learning_rate 0.00074358414047493967 --batch_size 64 --hidden_size 2237 --dropout 0.12443048554258703819 --num_dense_layers 1 --filter 121 --num_conv_layers 5,0,,c114,1206563,113_0,COMPLETED,BOTORCH_MODULAR,69.730000000000003979039320256561,126,0.000743584140474939665060860605,64,2237,0.124430485542587038194639603716,1,121,5
114,1761942721,66,127c23cb-d119-4ecc-b801-d8b643248022,1761942787,1761945876,3089,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 228 --learning_rate 0.00084499111788802618 --batch_size 117 --hidden_size 1779 --dropout 0.27340857669683443776 --num_dense_layers 2 --filter 109 --num_conv_layers 5,0,,c115,1206559,114_0,COMPLETED,BOTORCH_MODULAR,68.269999999999996020960679743439,228,0.000844991117888026178547877798,117,1779,0.273408576696834437758099056737,2,109,5
115,1761942721,28,127c23cb-d119-4ecc-b801-d8b643248022,1761942749,1761944881,2132,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 131 --learning_rate 0.00070010618254440324 --batch_size 64 --hidden_size 2220 --dropout 0.08047400438407203982 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c125,1206552,115_0,COMPLETED,BOTORCH_MODULAR,68.849999999999994315658113919199,131,0.000700106182544403240000652211,64,2220,0.080474004384072039819386645831,1,128,5
116,1761942721,68,127c23cb-d119-4ecc-b801-d8b643248022,1761942789,1761944756,1967,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 143 --learning_rate 0.00081685846353659122 --batch_size 105 --hidden_size 1850 --dropout 0.26691549326469676817 --num_dense_layers 2 --filter 108 --num_conv_layers 5,0,,c115,1206562,116_0,COMPLETED,BOTORCH_MODULAR,68.379999999999995452526491135359,143,0.000816858463536591222764471354,105,1850,0.266915493264696768171972962591,2,108,5
117,1761942732,37,127c23cb-d119-4ecc-b801-d8b643248022,1761942769,1761945843,3074,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 190 --learning_rate 0.00074949230539435275 --batch_size 64 --hidden_size 2145 --dropout 0.36880392979746956517 --num_dense_layers 2 --filter 113 --num_conv_layers 5,0,,c114,1206564,117_0,COMPLETED,BOTORCH_MODULAR,69.35999999999999943156581139192,190,0.000749492305394352750259889806,64,2145,0.368803929797469565166068150575,2,113,5
118,1761942732,37,127c23cb-d119-4ecc-b801-d8b643248022,1761942769,1761943868,1099,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 70 --learning_rate 0.00074938967649996894 --batch_size 64 --hidden_size 1927 --dropout 0.31895827707198259882 --num_dense_layers 2 --filter 109 --num_conv_layers 5,0,,c114,1206565,118_0,COMPLETED,BOTORCH_MODULAR,68.92000000000000170530256582424,70,0.000749389676499968935413642512,64,1927,0.31895827707198259881593571663,2,109,5
119,1761942732,37,127c23cb-d119-4ecc-b801-d8b643248022,1761942769,1761943914,1145,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 74 --learning_rate 0.00077413249019426394 --batch_size 64 --hidden_size 1778 --dropout 0.34862770052328390102 --num_dense_layers 2 --filter 110 --num_conv_layers 5,0,,c113,1206566,119_0,COMPLETED,BOTORCH_MODULAR,69.159999999999996589394868351519,74,0.000774132490194263944704999858,64,1778,0.348627700523283901024029773907,2,110,5
120,1761947538,35,127c23cb-d119-4ecc-b801-d8b643248022,1761947573,1761948971,1398,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 91 --learning_rate 0.00077695903392985006 --batch_size 64 --hidden_size 2719 --dropout 0.35456645027591349173 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c120,1206664,120_0,COMPLETED,BOTORCH_MODULAR,70.92000000000000170530256582424,91,0.000776959033929850058364241505,64,2719,0.354566450275913491729795623542,1,128,5
121,1761947539,42,127c23cb-d119-4ecc-b801-d8b643248022,1761947581,1761948656,1075,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 69 --learning_rate 0.00077609547099922126 --batch_size 64 --hidden_size 2658 --dropout 0.35422557246082209126 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c118,1206669,121_0,COMPLETED,BOTORCH_MODULAR,70.439999999999997726263245567679,69,0.000776095470999221262106693153,64,2658,0.354225572460822091258592081431,1,128,5
122,1761947538,12,127c23cb-d119-4ecc-b801-d8b643248022,1761947550,1761948907,1357,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 87 --learning_rate 0.00078159805364038759 --batch_size 64 --hidden_size 2564 --dropout 0.35577110935741668163 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c122,1206660,122_0,COMPLETED,BOTORCH_MODULAR,71.019999999999996020960679743439,87,0.000781598053640387589388605072,64,2564,0.355771109357416681628905053003,1,128,5
123,1761947538,13,127c23cb-d119-4ecc-b801-d8b643248022,1761947551,1761948514,963,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 62 --learning_rate 0.0007795904137624769 --batch_size 64 --hidden_size 2665 --dropout 0.35753468669287497006 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c122,1206661,123_0,COMPLETED,BOTORCH_MODULAR,71.07999999999999829469743417576,62,0.000779590413762476898765219069,64,2665,0.35753468669287497005981890652,1,128,5
124,1761947539,42,127c23cb-d119-4ecc-b801-d8b643248022,1761947581,1761948312,731,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 46 --learning_rate 0.0007753271683570757 --batch_size 64 --hidden_size 2576 --dropout 0.35188715397792869055 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c118,1206670,124_0,COMPLETED,BOTORCH_MODULAR,69.909999999999996589394868351519,46,0.000775327168357075702069536316,64,2576,0.351887153977928690551379986573,1,128,5
125,1761947538,12,127c23cb-d119-4ecc-b801-d8b643248022,1761947550,1761948158,608,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 38 --learning_rate 0.00077721200967394242 --batch_size 64 --hidden_size 2587 --dropout 0.35454914096787637501 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c123,1206658,125_0,COMPLETED,BOTORCH_MODULAR,69.46999999999999886313162278384,38,0.000777212009673942418042091873,64,2587,0.354549140967876375007961087249,1,128,5
126,1761947539,35,127c23cb-d119-4ecc-b801-d8b643248022,1761947574,1761948918,1344,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 86 --learning_rate 0.00078062989166423672 --batch_size 64 --hidden_size 2562 --dropout 0.35315292070826992399 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c120,1206665,126_0,COMPLETED,BOTORCH_MODULAR,70.96999999999999886313162278384,86,0.000780629891664236718815117477,64,2562,0.353152920708269923988353866662,1,128,5
127,1761947538,28,127c23cb-d119-4ecc-b801-d8b643248022,1761947566,1761948404,838,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 53 --learning_rate 0.00077558948450458384 --batch_size 64 --hidden_size 2558 --dropout 0.3508381467370216833 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c120,1206662,127_0,COMPLETED,BOTORCH_MODULAR,70.019999999999996020960679743439,53,0.000775589484504583836534108432,64,2558,0.350838146737021683296831042753,1,128,5
128,1761947539,41,127c23cb-d119-4ecc-b801-d8b643248022,1761947580,1761948831,1251,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 81 --learning_rate 0.00077569263526670862 --batch_size 64 --hidden_size 2610 --dropout 0.3514995771410605041 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c117,1206672,128_0,COMPLETED,BOTORCH_MODULAR,70.799999999999997157829056959599,81,0.000775692635266708621459563755,64,2610,0.351499577141060504104075334908,1,128,5
129,1761947539,42,127c23cb-d119-4ecc-b801-d8b643248022,1761947581,1761948731,1150,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 74 --learning_rate 0.00077893376767631888 --batch_size 64 --hidden_size 2609 --dropout 0.35313138932978982432 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c118,1206671,129_0,COMPLETED,BOTORCH_MODULAR,71.069999999999993178789736703038,74,0.00077893376767631888023257769,64,2609,0.353131389329789824316208068922,1,128,5
130,1761947538,12,127c23cb-d119-4ecc-b801-d8b643248022,1761947550,1761948669,1119,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 72 --learning_rate 0.00077550905955400546 --batch_size 64 --hidden_size 2605 --dropout 0.3530552458622278067 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c122,1206659,130_0,COMPLETED,BOTORCH_MODULAR,70.5,72,0.000775509059554005462759629363,64,2605,0.353055245862227806696864718106,1,128,5
131,1761947539,34,127c23cb-d119-4ecc-b801-d8b643248022,1761947573,1761948275,702,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 45 --learning_rate 0.0007785121949506333 --batch_size 64 --hidden_size 2567 --dropout 0.35336594099722706819 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c119,1206667,131_0,COMPLETED,BOTORCH_MODULAR,70.14000000000000056843418860808,45,0.000778512194950633303232312432,64,2567,0.353365940997227068187669374311,1,128,5
132,1761947544,61,127c23cb-d119-4ecc-b801-d8b643248022,1761947605,1761948717,1112,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 72 --learning_rate 0.00077732611141741387 --batch_size 64 --hidden_size 2616 --dropout 0.3533229766673077199 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c115,1206676,132_0,COMPLETED,BOTORCH_MODULAR,70.53000000000000113686837721616,72,0.00077732611141741387358189419,64,2616,0.35332297666730771990017956341,1,128,5
133,1761947539,34,127c23cb-d119-4ecc-b801-d8b643248022,1761947573,1761948737,1164,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 75 --learning_rate 0.00077922627724490276 --batch_size 64 --hidden_size 2562 --dropout 0.35336415555556005552 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c118,1206668,133_0,COMPLETED,BOTORCH_MODULAR,70.379999999999995452526491135359,75,0.000779226277244902758821465394,64,2562,0.353364155555560055521624462926,1,128,5
134,1761947539,34,127c23cb-d119-4ecc-b801-d8b643248022,1761947573,1761948769,1196,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 77 --learning_rate 0.00077815067554885885 --batch_size 64 --hidden_size 2622 --dropout 0.35448379441055838379 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c119,1206666,134_0,COMPLETED,BOTORCH_MODULAR,70.78000000000000113686837721616,77,0.000778150675548858845528843453,64,2622,0.354483794410558383791709502475,1,128,5
135,1761947538,36,127c23cb-d119-4ecc-b801-d8b643248022,1761947574,1761948750,1176,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 76 --learning_rate 0.000778337108456518 --batch_size 64 --hidden_size 2709 --dropout 0.3547795556486864621 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c120,1206663,135_0,COMPLETED,BOTORCH_MODULAR,70.590000000000003410605131648481,76,0.000778337108456518002828905534,64,2709,0.354779555648686462099306027085,1,128,5
136,1761947541,39,127c23cb-d119-4ecc-b801-d8b643248022,1761947580,1761948518,938,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 59 --learning_rate 0.00077703530329426126 --batch_size 64 --hidden_size 2676 --dropout 0.35415546241747974943 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c117,1206673,136_0,COMPLETED,BOTORCH_MODULAR,69.980000000000003979039320256561,59,0.000777035303294261263905295944,64,2676,0.354155462417479749426263424539,1,128,5
137,1761947541,52,127c23cb-d119-4ecc-b801-d8b643248022,1761947593,1761948838,1245,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 81 --learning_rate 0.0007805916041271182 --batch_size 64 --hidden_size 2646 --dropout 0.35544311239145448544 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c117,1206674,137_0,COMPLETED,BOTORCH_MODULAR,70.5,81,0.000780591604127118198451495967,64,2646,0.355443112391454485443631483577,1,128,5
138,1761947541,57,127c23cb-d119-4ecc-b801-d8b643248022,1761947598,1761948361,763,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 49 --learning_rate 0.00077710802473644313 --batch_size 64 --hidden_size 2606 --dropout 0.35331537918018590672 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c116,1206675,138_0,COMPLETED,BOTORCH_MODULAR,69.620000000000004547473508864641,49,0.000777108024736443132700347558,64,2606,0.353315379180185906715649934995,1,128,5
139,1761947545,60,127c23cb-d119-4ecc-b801-d8b643248022,1761947605,1761948510,905,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 58 --learning_rate 0.00077926455068185135 --batch_size 64 --hidden_size 2672 --dropout 0.35536959797877920586 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c115,1206677,139_0,COMPLETED,BOTORCH_MODULAR,70.21999999999999886313162278384,58,0.000779264550681851354309304103,64,2672,0.355369597978779205860178080911,1,128,5
140,1761949113,24,127c23cb-d119-4ecc-b801-d8b643248022,1761949137,1761951686,2549,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 165 --learning_rate 0.00089777374066169749 --batch_size 64 --hidden_size 2597 --dropout 0.3781582892647559202 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c122,1206708,140_0,COMPLETED,BOTORCH_MODULAR,70.620000000000004547473508864641,165,0.000897773740661697485648806705,64,2597,0.378158289264755920200400396425,1,128,5
141,1761949113,23,127c23cb-d119-4ecc-b801-d8b643248022,1761949136,1761951686,2550,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 165 --learning_rate 0.00089882694284770879 --batch_size 64 --hidden_size 2592 --dropout 0.37916285780875147449 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c122,1206707,141_0,COMPLETED,BOTORCH_MODULAR,70.60999999999999943156581139192,165,0.000898826942847708791443916976,64,2592,0.379162857808751474486541610531,1,128,5
142,1761949112,6,127c23cb-d119-4ecc-b801-d8b643248022,1761949118,1761951652,2534,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 165 --learning_rate 0.00089688113519439928 --batch_size 64 --hidden_size 2606 --dropout 0.37963433574276195248 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c123,1206704,142_0,COMPLETED,BOTORCH_MODULAR,71.21999999999999886313162278384,165,0.000896881135194399275664678406,64,2606,0.379634335742761952481316711783,1,128,5
143,1761949113,54,127c23cb-d119-4ecc-b801-d8b643248022,1761949167,1761951702,2535,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 165 --learning_rate 0.00089639295121709411 --batch_size 64 --hidden_size 2605 --dropout 0.37855245054955521944 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c120,1206711,143_0,COMPLETED,BOTORCH_MODULAR,70.790000000000006252776074688882,165,0.000896392951217094111245053956,64,2605,0.378552450549555219438957465172,1,128,5
144,1761949113,27,127c23cb-d119-4ecc-b801-d8b643248022,1761949140,1761951653,2513,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 165 --learning_rate 0.00089793411186709791 --batch_size 64 --hidden_size 2616 --dropout 0.37994249312451250367 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c122,1206709,144_0,COMPLETED,BOTORCH_MODULAR,70.939999999999997726263245567679,165,0.00089793411186709791351606702,64,2616,0.379942493124512503666068141683,1,128,5
145,1761949113,4,127c23cb-d119-4ecc-b801-d8b643248022,1761949117,1761951671,2554,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 165 --learning_rate 0.00089534009176847151 --batch_size 64 --hidden_size 2599 --dropout 0.37868248170748414205 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c123,1206706,145_0,COMPLETED,BOTORCH_MODULAR,70.459999999999993747223925311118,165,0.000895340091768471514101224162,64,2599,0.378682481707484142052777542631,1,128,5
146,1761949112,4,127c23cb-d119-4ecc-b801-d8b643248022,1761949116,1761951605,2489,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 165 --learning_rate 0.00089703789556734679 --batch_size 64 --hidden_size 2594 --dropout 0.37901001026340669364 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c123,1206705,146_0,COMPLETED,BOTORCH_MODULAR,71.180000000000006821210263296962,165,0.000897037895567346786791784741,64,2594,0.37901001026340669364245172801,1,128,5
147,1761949114,88,127c23cb-d119-4ecc-b801-d8b643248022,1761949202,1761951724,2522,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 165 --learning_rate 0.00089789720837390812 --batch_size 64 --hidden_size 2598 --dropout 0.37896244165489312294 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c118,1206717,147_0,COMPLETED,BOTORCH_MODULAR,70.939999999999997726263245567679,165,0.000897897208373908120235262764,64,2598,0.378962441654893122944258720963,1,128,5
148,1761949114,82,127c23cb-d119-4ecc-b801-d8b643248022,1761949196,1761951744,2548,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 165 --learning_rate 0.00090009308850619784 --batch_size 64 --hidden_size 2606 --dropout 0.37980310828752489316 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c119,1206715,148_0,COMPLETED,BOTORCH_MODULAR,71.019999999999996020960679743439,165,0.000900093088506197843562395278,64,2606,0.379803108287524893160735928177,1,128,5
149,1761949114,53,127c23cb-d119-4ecc-b801-d8b643248022,1761949167,1761951714,2547,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 165 --learning_rate 0.0009090090595707818 --batch_size 64 --hidden_size 2444 --dropout 0.37799682490355501763 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c120,1206710,149_0,COMPLETED,BOTORCH_MODULAR,70.760000000000005115907697472721,165,0.000909009059570781803236161345,64,2444,0.377996824903555017627354573051,1,128,5
150,1761949114,88,127c23cb-d119-4ecc-b801-d8b643248022,1761949202,1761951743,2541,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 165 --learning_rate 0.00089438134653273499 --batch_size 64 --hidden_size 2590 --dropout 0.37724554458818920777 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c118,1206718,150_0,COMPLETED,BOTORCH_MODULAR,71.060000000000002273736754432321,165,0.000894381346532734989619728427,64,2590,0.377245544588189207768635924367,1,128,5
151,1761949113,63,127c23cb-d119-4ecc-b801-d8b643248022,1761949176,1761951663,2487,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 165 --learning_rate 0.00092745414211586549 --batch_size 64 --hidden_size 2257 --dropout 0.37914629150954970438 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c119,1206714,151_0,COMPLETED,BOTORCH_MODULAR,70.760000000000005115907697472721,165,0.000927454142115865490421378059,64,2257,0.379146291509549704379367085494,1,128,5
152,1761949114,88,127c23cb-d119-4ecc-b801-d8b643248022,1761949202,1761951743,2541,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 165 --learning_rate 0.00089573628617097706 --batch_size 64 --hidden_size 2596 --dropout 0.37870656800032104217 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c118,1206716,152_0,COMPLETED,BOTORCH_MODULAR,70.870000000000004547473508864641,165,0.000895736286170977055905162434,64,2596,0.378706568000321042166689267106,1,128,5
153,1761949114,61,127c23cb-d119-4ecc-b801-d8b643248022,1761949175,1761951727,2552,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 166 --learning_rate 0.00090061571395512214 --batch_size 64 --hidden_size 2593 --dropout 0.37981949056821062705 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c120,1206712,153_0,COMPLETED,BOTORCH_MODULAR,70.230000000000003979039320256561,166,0.000900615713955122136787079246,64,2593,0.379819490568210627046141780738,1,128,5
154,1761949114,102,127c23cb-d119-4ecc-b801-d8b643248022,1761949216,1761951760,2544,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 165 --learning_rate 0.00089704555385390009 --batch_size 64 --hidden_size 2592 --dropout 0.3778866614035868432 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c131,1206719,154_0,COMPLETED,BOTORCH_MODULAR,70.959999999999993747223925311118,165,0.000897045553853900094580520186,64,2592,0.377886661403586843199775557878,1,128,5
155,1761949114,56,127c23cb-d119-4ecc-b801-d8b643248022,1761949170,1761951717,2547,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 165 --learning_rate 0.00089774263001540029 --batch_size 64 --hidden_size 2595 --dropout 0.37871368284822920502 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c120,1206713,155_0,COMPLETED,BOTORCH_MODULAR,70.71999999999999886313162278384,165,0.000897742630015400293677640953,64,2595,0.378713682848229205024637167298,1,128,5
156,,,,,,,,,,,,156_0,RUNNING,BOTORCH_MODULAR,,165,0.000899716702831433842897645992,64,2599,0.380651419144225067192621736467,1,128,5
157,,,,,,,,,,,,157_0,RUNNING,BOTORCH_MODULAR,,165,0.000894363687590991971593235021,64,2602,0.378028880900386832220050337128,1,128,5
158,,,,,,,,,,,,158_0,RUNNING,BOTORCH_MODULAR,,165,0.000896162853954901843928082528,64,2592,0.377834787522244475166388610887,1,128,5
159,,,,,,,,,,,,159_0,RUNNING,BOTORCH_MODULAR,,165,0.00089786142403573470857636174,64,2599,0.378660581290602482606999501513,1,128,5
160,1761951952,32,127c23cb-d119-4ecc-b801-d8b643248022,1761951984,1761954353,2369,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 153 --learning_rate 0.00072356269838195803 --batch_size 64 --hidden_size 2638 --dropout 0.35786566825934607028 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c120,1206774,160_0,COMPLETED,BOTORCH_MODULAR,69.879999999999995452526491135359,153,0.000723562698381958026641602721,64,2638,0.357865668259346070279036666761,1,128,5
161,1761951951,24,127c23cb-d119-4ecc-b801-d8b643248022,1761951975,1761954389,2414,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 157 --learning_rate 0.00072538336484485736 --batch_size 64 --hidden_size 2549 --dropout 0.35633143928399307887 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c122,1206770,161_0,COMPLETED,BOTORCH_MODULAR,70.64000000000000056843418860808,157,0.000725383364844857359519936235,64,2549,0.356331439283993078870338422348,1,128,5
162,1761951951,4,127c23cb-d119-4ecc-b801-d8b643248022,1761951955,1761954389,2434,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 157 --learning_rate 0.00072394893835966208 --batch_size 64 --hidden_size 2542 --dropout 0.35573495109924130331 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c131,1206763,162_0,COMPLETED,BOTORCH_MODULAR,71.379999999999995452526491135359,157,0.000723948938359662082404899497,64,2542,0.355734951099241303307252337618,1,128,5
163,1761951951,33,127c23cb-d119-4ecc-b801-d8b643248022,1761951984,1761954407,2423,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 157 --learning_rate 0.00072431489522128338 --batch_size 64 --hidden_size 2545 --dropout 0.35605469726073957215 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c120,1206773,163_0,COMPLETED,BOTORCH_MODULAR,70.82999999999999829469743417576,157,0.000724314895221283379031507188,64,2545,0.356054697260739572151067022787,1,128,5
164,1761951951,4,127c23cb-d119-4ecc-b801-d8b643248022,1761951955,1761954358,2403,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 157 --learning_rate 0.0007225027031848519 --batch_size 64 --hidden_size 2560 --dropout 0.35728165875856343625 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c124,1206764,164_0,COMPLETED,BOTORCH_MODULAR,70.340000000000003410605131648481,157,0.00072250270318485190160912035,64,2560,0.357281658758563436251165512658,1,128,5
165,1761951951,40,127c23cb-d119-4ecc-b801-d8b643248022,1761951991,1761954401,2410,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 157 --learning_rate 0.00072422957487019068 --batch_size 64 --hidden_size 2544 --dropout 0.35661358092863132407 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c119,1206777,165_0,COMPLETED,BOTORCH_MODULAR,70.409999999999996589394868351519,157,0.000724229574870190683476278704,64,2544,0.356613580928631324074018493775,1,128,5
166,1761951951,11,127c23cb-d119-4ecc-b801-d8b643248022,1761951962,1761954391,2429,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 157 --learning_rate 0.00072513920042486786 --batch_size 64 --hidden_size 2550 --dropout 0.35550058945311852066 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c123,1206766,166_0,COMPLETED,BOTORCH_MODULAR,70.540000000000006252776074688882,157,0.000725139200424867861639877109,64,2550,0.355500589453118520655294787502,1,128,5
167,1761951951,11,127c23cb-d119-4ecc-b801-d8b643248022,1761951962,1761954371,2409,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 157 --learning_rate 0.00072647667448748647 --batch_size 64 --hidden_size 2545 --dropout 0.35553374996778641659 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c123,1206765,167_0,COMPLETED,BOTORCH_MODULAR,70.75,157,0.000726476674487486467207686403,64,2545,0.355533749967786416590342923882,1,128,5
168,1761951952,32,127c23cb-d119-4ecc-b801-d8b643248022,1761951984,1761954428,2444,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 157 --learning_rate 0.00072455937584206889 --batch_size 64 --hidden_size 2545 --dropout 0.35627822937559527894 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c120,1206775,168_0,COMPLETED,BOTORCH_MODULAR,70.689999999999997726263245567679,157,0.000724559375842068892348279974,64,2545,0.356278229375595278938249066414,1,128,5
169,1761951951,40,127c23cb-d119-4ecc-b801-d8b643248022,1761951991,1761954420,2429,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 157 --learning_rate 0.00072450448292933514 --batch_size 64 --hidden_size 2544 --dropout 0.35706221808473775914 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c119,1206776,169_0,COMPLETED,BOTORCH_MODULAR,70.939999999999997726263245567679,157,0.00072450448292933514009284135,64,2544,0.357062218084737759138391766101,1,128,5
170,1761951951,13,127c23cb-d119-4ecc-b801-d8b643248022,1761951964,1761954391,2427,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 157 --learning_rate 0.0007273278551771389 --batch_size 64 --hidden_size 2465 --dropout 0.35591877292584317427 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c123,1206768,170_0,COMPLETED,BOTORCH_MODULAR,70.090000000000003410605131648481,157,0.000727327855177138898716548976,64,2465,0.355918772925843174270710278506,1,128,5
171,1761951952,24,127c23cb-d119-4ecc-b801-d8b643248022,1761951976,1761954334,2358,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 153 --learning_rate 0.00072721340857292223 --batch_size 64 --hidden_size 2534 --dropout 0.35744723298827479896 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c122,1206771,171_0,COMPLETED,BOTORCH_MODULAR,71.180000000000006821210263296962,153,0.000727213408572922230879709282,64,2534,0.357447232988274798959338340865,1,128,5
172,1761951953,31,127c23cb-d119-4ecc-b801-d8b643248022,1761951984,1761954391,2407,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 157 --learning_rate 0.00072417876757218411 --batch_size 64 --hidden_size 2551 --dropout 0.35666226983663351646 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c120,1206772,172_0,COMPLETED,BOTORCH_MODULAR,70.790000000000006252776074688882,157,0.000724178767572184107527422103,64,2551,0.356662269836633516462143234094,1,128,5
173,1761951952,11,127c23cb-d119-4ecc-b801-d8b643248022,1761951963,1761954379,2416,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 157 --learning_rate 0.00072622423499340443 --batch_size 64 --hidden_size 2541 --dropout 0.35595818342229224029 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c123,1206767,173_0,COMPLETED,BOTORCH_MODULAR,70.379999999999995452526491135359,157,0.000726224234993404433105568252,64,2541,0.355958183422292240294382281718,1,128,5
174,1761951952,39,127c23cb-d119-4ecc-b801-d8b643248022,1761951991,1761954401,2410,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 157 --learning_rate 0.00072360053147521401 --batch_size 64 --hidden_size 2552 --dropout 0.35690279479728470591 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c119,1206778,174_0,COMPLETED,BOTORCH_MODULAR,70.459999999999993747223925311118,157,0.000723600531475214014780206195,64,2552,0.356902794797284705907713941997,1,128,5
175,1761951952,24,127c23cb-d119-4ecc-b801-d8b643248022,1761951976,1761954432,2456,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 158 --learning_rate 0.00070598275666205448 --batch_size 64 --hidden_size 2831 --dropout 0.35944308947934267007 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c122,1206769,175_0,COMPLETED,BOTORCH_MODULAR,70.64000000000000056843418860808,158,0.000705982756662054482775514597,64,2831,0.359443089479342670067296694469,1,128,5
176,1761951955,40,127c23cb-d119-4ecc-b801-d8b643248022,1761951995,1761954426,2431,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 157 --learning_rate 0.00072400719959680201 --batch_size 64 --hidden_size 2538 --dropout 0.35659656204015355296 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c118,1206780,176_0,COMPLETED,BOTORCH_MODULAR,70.230000000000003979039320256561,157,0.000724007199596802012916962887,64,2538,0.356596562040153552963772654039,1,128,5
177,1761951955,40,127c23cb-d119-4ecc-b801-d8b643248022,1761951995,1761954437,2442,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 157 --learning_rate 0.00072336023623051674 --batch_size 64 --hidden_size 2544 --dropout 0.3565816286530978374 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c118,1206779,177_0,COMPLETED,BOTORCH_MODULAR,70.71999999999999886313162278384,157,0.000723360236230516742174379008,64,2544,0.356581628653097837400309799705,1,128,5
178,1761951955,42,127c23cb-d119-4ecc-b801-d8b643248022,1761951997,1761954432,2435,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 157 --learning_rate 0.00072473735840682737 --batch_size 64 --hidden_size 2546 --dropout 0.35557286697366546901 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c118,1206781,178_0,COMPLETED,BOTORCH_MODULAR,70.989999999999994884092302527279,157,0.000724737358406827365982227906,64,2546,0.355572866973665469014775908363,1,128,5
179,1761951959,36,127c23cb-d119-4ecc-b801-d8b643248022,1761951995,1761954525,2530,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 162 --learning_rate 0.00070700696102674932 --batch_size 64 --hidden_size 2805 --dropout 0.35831808040883939004 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c118,1206782,179_0,COMPLETED,BOTORCH_MODULAR,70.870000000000004547473508864641,162,0.000707006961026749322987705604,64,2805,0.358318080408839390038622241264,1,128,5
180,1761954749,4,127c23cb-d119-4ecc-b801-d8b643248022,1761954753,1761956640,1887,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 122 --learning_rate 0.00098217529996678021 --batch_size 64 --hidden_size 2877 --dropout 0.33760884757294418179 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c129,1206819,180_0,COMPLETED,BOTORCH_MODULAR,70.599999999999994315658113919199,122,0.000982175299966780209620642594,64,2877,0.337608847572944181791854134644,1,128,5
181,1761954748,12,127c23cb-d119-4ecc-b801-d8b643248022,1761954760,1761956908,2148,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 140 --learning_rate 0.00098030307703502514 --batch_size 64 --hidden_size 2668 --dropout 0.32805530586926834324 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c129,1206820,181_0,COMPLETED,BOTORCH_MODULAR,71.07999999999999829469743417576,140,0.000980303077035025137442314502,64,2668,0.328055305869268343244016250537,1,128,5
182,1761954748,42,127c23cb-d119-4ecc-b801-d8b643248022,1761954790,1761956962,2172,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 140 --learning_rate 0.00098727098100565968 --batch_size 64 --hidden_size 2602 --dropout 0.32689435646305026184 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c122,1206827,182_0,COMPLETED,BOTORCH_MODULAR,70.620000000000004547473508864641,140,0.000987270981005659679918817773,64,2602,0.326894356463050261840663779367,1,128,5
183,1761954748,5,127c23cb-d119-4ecc-b801-d8b643248022,1761954753,1761956921,2168,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 140 --learning_rate 0.00097768943826269253 --batch_size 64 --hidden_size 2782 --dropout 0.32857503162006740371 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c154,1206817,183_0,COMPLETED,BOTORCH_MODULAR,70.700000000000002842170943040401,140,0.000977689438262692531861342005,64,2782,0.328575031620067403714813281113,1,128,5
184,1761954749,23,127c23cb-d119-4ecc-b801-d8b643248022,1761954772,1761956852,2080,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 135 --learning_rate 0.0009781241582934733 --batch_size 64 --hidden_size 2691 --dropout 0.33299286777047415464 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c124,1206821,184_0,COMPLETED,BOTORCH_MODULAR,70.680000000000006821210263296962,135,0.000978124158293473301706288936,64,2691,0.332992867770474154642812436578,1,128,5
185,1761954748,5,127c23cb-d119-4ecc-b801-d8b643248022,1761954753,1761956915,2162,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 140 --learning_rate 0.00098221338084130945 --batch_size 64 --hidden_size 2663 --dropout 0.32759246005374442756 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c131,1206818,185_0,COMPLETED,BOTORCH_MODULAR,70.42000000000000170530256582424,140,0.0009822133808413094531453158,64,2663,0.327592460053744427561639440682,1,128,5
186,1761954749,29,127c23cb-d119-4ecc-b801-d8b643248022,1761954778,1761956928,2150,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 140 --learning_rate 0.00098119176761417163 --batch_size 64 --hidden_size 2655 --dropout 0.32858550712127404525 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c123,1206823,186_0,COMPLETED,BOTORCH_MODULAR,70.5,140,0.000981191767614171626160635142,64,2655,0.328585507121274045250203243995,1,128,5
187,1761954749,41,127c23cb-d119-4ecc-b801-d8b643248022,1761954790,1761956985,2195,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 140 --learning_rate 0.00098280822189663209 --batch_size 64 --hidden_size 2670 --dropout 0.32711691455800462336 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c123,1206825,187_0,COMPLETED,BOTORCH_MODULAR,70.810000000000002273736754432321,140,0.00098280822189663209070831229,64,2670,0.327116914558004623359011020511,1,128,5
188,1761954749,29,127c23cb-d119-4ecc-b801-d8b643248022,1761954778,1761956918,2140,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 140 --learning_rate 0.00098388387080936392 --batch_size 64 --hidden_size 2663 --dropout 0.32767042365405324444 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c123,1206824,188_0,COMPLETED,BOTORCH_MODULAR,70.230000000000003979039320256561,140,0.000983883870809363920290069316,64,2663,0.327670423654053244444384063172,1,128,5
189,1761954749,46,127c23cb-d119-4ecc-b801-d8b643248022,1761954795,1761956948,2153,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 139 --learning_rate 0.00098480124699117425 --batch_size 64 --hidden_size 2645 --dropout 0.32837709203353665499 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c122,1206826,189_0,COMPLETED,BOTORCH_MODULAR,70.319999999999993178789736703038,139,0.000984801246991174250230982601,64,2645,0.328377092033536654991365821843,1,128,5
190,1761954749,51,127c23cb-d119-4ecc-b801-d8b643248022,1761954800,1761956946,2146,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 139 --learning_rate 0.00098394843444129469 --batch_size 64 --hidden_size 2664 --dropout 0.32813315813784016406 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c120,1206831,190_0,COMPLETED,BOTORCH_MODULAR,70.92000000000000170530256582424,139,0.000983948434441294685071088821,64,2664,0.328133158137840164059184644429,1,128,5
191,1761954749,46,127c23cb-d119-4ecc-b801-d8b643248022,1761954795,1761956791,1996,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 130 --learning_rate 0.00097619227162847435 --batch_size 64 --hidden_size 2800 --dropout 0.33576040497616199687 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c122,1206828,191_0,COMPLETED,BOTORCH_MODULAR,71.090000000000003410605131648481,130,0.000976192271628474345784853838,64,2800,0.335760404976161996870587245212,1,128,5
192,1761954749,51,127c23cb-d119-4ecc-b801-d8b643248022,1761954800,1761956966,2166,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 140 --learning_rate 0.00098224373716495695 --batch_size 64 --hidden_size 2661 --dropout 0.32794676084552282225 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c120,1206830,192_0,COMPLETED,BOTORCH_MODULAR,70.989999999999994884092302527279,140,0.000982243737164956946111837865,64,2661,0.327946760845522822247488647918,1,128,5
193,1761954749,52,127c23cb-d119-4ecc-b801-d8b643248022,1761954802,1761956961,2159,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 140 --learning_rate 0.00098033673480485027 --batch_size 64 --hidden_size 2667 --dropout 0.32826047015357012748 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c120,1206832,193_0,COMPLETED,BOTORCH_MODULAR,70.700000000000002842170943040401,140,0.000980336734804850267605003111,64,2667,0.328260470153570127482822726961,1,128,5
194,1761954750,50,127c23cb-d119-4ecc-b801-d8b643248022,1761954800,1761956616,1816,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 117 --learning_rate 0.00099234834380633333 --batch_size 64 --hidden_size 2701 --dropout 0.33875693252825439528 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c120,1206829,194_0,COMPLETED,BOTORCH_MODULAR,70.629999999999995452526491135359,117,0.000992348343806333330757718514,64,2701,0.338756932528254395275979504731,1,128,5
195,1761954749,29,127c23cb-d119-4ecc-b801-d8b643248022,1761954778,1761956804,2026,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 131 --learning_rate 0.00099194864851178299 --batch_size 64 --hidden_size 2590 --dropout 0.33312342461372701496 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c123,1206822,195_0,COMPLETED,BOTORCH_MODULAR,71.049999999999997157829056959599,131,0.000991948648511782994988128515,64,2590,0.333123424613727014964581485401,1,128,5
196,1761954752,40,127c23cb-d119-4ecc-b801-d8b643248022,1761954792,1761956934,2142,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 140 --learning_rate 0.0009819725248270024 --batch_size 64 --hidden_size 2677 --dropout 0.32865080716015104834 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c119,1206833,196_0,COMPLETED,BOTORCH_MODULAR,71.560000000000002273736754432321,140,0.000981972524827002396508035531,64,2677,0.328650807160151048336160783947,1,128,5
197,1761954752,60,127c23cb-d119-4ecc-b801-d8b643248022,1761954812,1761956931,2119,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 138 --learning_rate 0.0009794636278042067 --batch_size 64 --hidden_size 2690 --dropout 0.32992356636097486255 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c131,1206834,197_0,COMPLETED,BOTORCH_MODULAR,71.239999999999994884092302527279,138,0.000979463627804206702839873167,64,2690,0.329923566360974862554655828717,1,128,5
198,1761954752,60,127c23cb-d119-4ecc-b801-d8b643248022,1761954812,1761956667,1855,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 120 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 2493 --dropout 0.33594414832656216419 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c119,1206835,198_0,COMPLETED,BOTORCH_MODULAR,70.25,120,0.001000000000000000020816681712,64,2493,0.33594414832656216418627082021,1,128,5
199,1761954755,57,127c23cb-d119-4ecc-b801-d8b643248022,1761954812,1761956840,2028,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 129 --learning_rate 0.00098062403112355342 --batch_size 64 --hidden_size 2916 --dropout 0.33347344965974651254 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c119,1206836,199_0,COMPLETED,BOTORCH_MODULAR,70.939999999999997726263245567679,129,0.000980624031123553422870098295,64,2916,0.333473449659746512541147467346,1,128,5
200,1761957247,17,127c23cb-d119-4ecc-b801-d8b643248022,1761957264,1761959302,2038,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 132 --learning_rate 0.00087305236837451842 --batch_size 64 --hidden_size 2898 --dropout 0.43901141198431437029 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c139,1206864,200_0,COMPLETED,BOTORCH_MODULAR,71.310000000000002273736754432321,132,0.000873052368374518418525642716,64,2898,0.439011411984314370293702722847,1,128,5
201,1761957247,33,127c23cb-d119-4ecc-b801-d8b643248022,1761957280,1761959503,2223,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 145 --learning_rate 0.00088120337705847992 --batch_size 64 --hidden_size 2796 --dropout 0.44168410927084345019 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c131,1206866,201_0,COMPLETED,BOTORCH_MODULAR,71,145,0.00088120337705847992439828209,64,2796,0.441684109270843450190113799181,1,128,5
202,1761957247,35,127c23cb-d119-4ecc-b801-d8b643248022,1761957282,1761959594,2312,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 149 --learning_rate 0.0008902710848892549 --batch_size 64 --hidden_size 2732 --dropout 0.45718240081570399314 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c131,1206865,202_0,COMPLETED,BOTORCH_MODULAR,71.32999999999999829469743417576,149,0.000890271084889254901359456618,64,2732,0.457182400815703993135485916355,1,128,5
203,1761957250,74,127c23cb-d119-4ecc-b801-d8b643248022,1761957324,1761959592,2268,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 146 --learning_rate 0.00088111442125456477 --batch_size 64 --hidden_size 2783 --dropout 0.43899534013892432815 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c123,1206877,203_0,COMPLETED,BOTORCH_MODULAR,71.120000000000004547473508864641,146,0.000881114421254564766927686037,64,2783,0.438995340138924328154956810977,1,128,5
204,1761957247,17,127c23cb-d119-4ecc-b801-d8b643248022,1761957264,1761959520,2256,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 144 --learning_rate 0.00087475813155712121 --batch_size 64 --hidden_size 3175 --dropout 0.47221785162091139965 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c141,1206862,204_0,COMPLETED,BOTORCH_MODULAR,70.760000000000005115907697472721,144,0.000874758131557121210684913049,64,3175,0.472217851620911399646018935528,1,128,5
205,1761957247,4,127c23cb-d119-4ecc-b801-d8b643248022,1761957251,1761959502,2251,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 146 --learning_rate 0.00087926592189958256 --batch_size 64 --hidden_size 2781 --dropout 0.43391560790602273778 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c154,1206861,205_0,COMPLETED,BOTORCH_MODULAR,70.659999999999996589394868351519,146,0.000879265921899582557526298121,64,2781,0.433915607906022737783047205085,1,128,5
206,1761957248,55,127c23cb-d119-4ecc-b801-d8b643248022,1761957303,1761959542,2239,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 144 --learning_rate 0.00087144940395824776 --batch_size 64 --hidden_size 3002 --dropout 0.43766599113736254223 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c124,1206873,206_0,COMPLETED,BOTORCH_MODULAR,70.769999999999996020960679743439,144,0.000871449403958247763302136235,64,3002,0.437665991137362542229283235429,1,128,5
207,1761957248,33,127c23cb-d119-4ecc-b801-d8b643248022,1761957281,1761959425,2144,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 137 --learning_rate 0.00086883948441539424 --batch_size 64 --hidden_size 3094 --dropout 0.45218798199548648764 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c130,1206867,207_0,COMPLETED,BOTORCH_MODULAR,70.909999999999996589394868351519,137,0.000868839484415394238542296179,64,3094,0.452187981995486487640789619036,1,128,5
208,1761957248,61,127c23cb-d119-4ecc-b801-d8b643248022,1761957309,1761959555,2246,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 145 --learning_rate 0.00087581469765511872 --batch_size 64 --hidden_size 2789 --dropout 0.42781228919869224159 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c123,1206874,208_0,COMPLETED,BOTORCH_MODULAR,70.560000000000002273736754432321,145,0.000875814697655118721067446508,64,2789,0.427812289198692241587451690066,1,128,5
209,1761957247,16,127c23cb-d119-4ecc-b801-d8b643248022,1761957263,1761959495,2232,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 145 --learning_rate 0.00087202412427251524 --batch_size 64 --hidden_size 3032 --dropout 0.45113805489088515399 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c140,1206863,209_0,COMPLETED,BOTORCH_MODULAR,70.620000000000004547473508864641,145,0.000872024124272515236376557279,64,3032,0.45113805489088515399132006678,1,128,5
210,1761957248,55,127c23cb-d119-4ecc-b801-d8b643248022,1761957303,1761959394,2091,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 136 --learning_rate 0.00087385166179900517 --batch_size 64 --hidden_size 2848 --dropout 0.43512648844451495833 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c129,1206871,210_0,COMPLETED,BOTORCH_MODULAR,70.82999999999999829469743417576,136,0.0008738516617990051702294374,64,2848,0.435126488444514958331410525716,1,128,5
211,1761957248,55,127c23cb-d119-4ecc-b801-d8b643248022,1761957303,1761959552,2249,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 145 --learning_rate 0.00087815692948938124 --batch_size 64 --hidden_size 2776 --dropout 0.43151683732881213063 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c129,1206870,211_0,COMPLETED,BOTORCH_MODULAR,70.950000000000002842170943040401,145,0.000878156929489381241418777257,64,2776,0.431516837328812130625266263451,1,128,5
212,1761957248,62,127c23cb-d119-4ecc-b801-d8b643248022,1761957310,1761959564,2254,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 146 --learning_rate 0.00088036056988289625 --batch_size 64 --hidden_size 2875 --dropout 0.44781505658000736458 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c123,1206875,212_0,COMPLETED,BOTORCH_MODULAR,70.96999999999999886313162278384,146,0.000880360569882896251692194767,64,2875,0.44781505658000736458390633743,1,128,5
213,1761957248,60,127c23cb-d119-4ecc-b801-d8b643248022,1761957308,1761959596,2288,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 146 --learning_rate 0.000880456221557399 --batch_size 64 --hidden_size 2783 --dropout 0.43191619001145115098 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c124,1206872,213_0,COMPLETED,BOTORCH_MODULAR,71.049999999999997157829056959599,146,0.000880456221557399001768906555,64,2783,0.431916190011451150976284907301,1,128,5
214,1761957248,32,127c23cb-d119-4ecc-b801-d8b643248022,1761957280,1761959502,2222,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 145 --learning_rate 0.00087984096307820595 --batch_size 64 --hidden_size 2823 --dropout 0.44498703641991038671 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c130,1206868,214_0,COMPLETED,BOTORCH_MODULAR,70.430000000000006821210263296962,145,0.000879840963078205948871834963,64,2823,0.444987036419910386708664873368,1,128,5
215,1761957248,35,127c23cb-d119-4ecc-b801-d8b643248022,1761957283,1761959506,2223,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 145 --learning_rate 0.00088060669722323437 --batch_size 64 --hidden_size 2781 --dropout 0.4379528295573235086 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c129,1206869,215_0,COMPLETED,BOTORCH_MODULAR,70.71999999999999886313162278384,145,0.000880606697223234365784483302,64,2781,0.437952829557323508602451056504,1,128,5
216,1761957249,74,127c23cb-d119-4ecc-b801-d8b643248022,1761957323,1761959336,2013,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 131 --learning_rate 0.00087168052143808791 --batch_size 64 --hidden_size 3057 --dropout 0.45890253370217293227 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c123,1206876,216_0,COMPLETED,BOTORCH_MODULAR,71.14000000000000056843418860808,131,0.000871680521438087914723458205,64,3057,0.458902533702172932272844718682,1,128,5
217,1761957260,81,127c23cb-d119-4ecc-b801-d8b643248022,1761957341,1761959587,2246,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 145 --learning_rate 0.00088090543945047554 --batch_size 64 --hidden_size 2799 --dropout 0.44009033639435712892 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c122,1206880,217_0,COMPLETED,BOTORCH_MODULAR,70.590000000000003410605131648481,145,0.000880905439450475544194141264,64,2799,0.440090336394357128924070821085,1,128,5
218,1761957260,80,127c23cb-d119-4ecc-b801-d8b643248022,1761957340,1761959593,2253,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 146 --learning_rate 0.00087881575472156131 --batch_size 64 --hidden_size 2777 --dropout 0.43273162323334890544 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c122,1206879,218_0,COMPLETED,BOTORCH_MODULAR,71.069999999999993178789736703038,146,0.000878815754721561310028321579,64,2777,0.432731623233348905444017873378,1,128,5
219,1761957260,85,127c23cb-d119-4ecc-b801-d8b643248022,1761957345,1761959233,1888,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 122 --learning_rate 0.00087389377541503192 --batch_size 64 --hidden_size 3087 --dropout 0.47746343515402983604 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c122,1206881,219_0,COMPLETED,BOTORCH_MODULAR,70.819999999999993178789736703038,122,0.000873893775415031924015674125,64,3087,0.477463435154029836038347411886,1,128,5
220,1761959879,63,127c23cb-d119-4ecc-b801-d8b643248022,1761959942,1761963095,3153,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 203 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 2526 --dropout 0.37465693550028184022 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c129,1206925,220_0,COMPLETED,BOTORCH_MODULAR,69.540000000000006252776074688882,203,0.001000000000000000020816681712,64,2526,0.374656935500281840223379958843,2,128,6
221,1761959880,22,127c23cb-d119-4ecc-b801-d8b643248022,1761959902,1761961058,1156,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 75 --learning_rate 0.00096218139409260837 --batch_size 64 --hidden_size 3124 --dropout 0.5 --num_dense_layers 1 --filter 108 --num_conv_layers 5,0,,c131,1206920,221_0,COMPLETED,BOTORCH_MODULAR,70.10999999999999943156581139192,75,0.000962181394092608368619201631,64,3124,0.5,1,108,5
222,1761959879,3,127c23cb-d119-4ecc-b801-d8b643248022,1761959882,1761961259,1377,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 90 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 2206 --dropout 0.5 --num_dense_layers 1 --filter 111 --num_conv_layers 5,0,,c143,1206915,222_0,COMPLETED,BOTORCH_MODULAR,70.21999999999999886313162278384,90,0.001000000000000000020816681712,64,2206,0.5,1,111,5
223,1761959879,23,127c23cb-d119-4ecc-b801-d8b643248022,1761959902,1761962186,2284,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 143 --learning_rate 0.00096588792101483679 --batch_size 64 --hidden_size 2839 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 5,0,,c141,1206916,223_0,COMPLETED,BOTORCH_MODULAR,69.10999999999999943156581139192,143,0.000965887921014836788036195259,64,2839,0.5,2,128,5
224,1761959879,41,127c23cb-d119-4ecc-b801-d8b643248022,1761959920,1761962019,2099,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 131 --learning_rate 0.00098415722850464017 --batch_size 64 --hidden_size 2457 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 5,0,,c130,1206922,224_0,COMPLETED,BOTORCH_MODULAR,69.200000000000002842170943040401,131,0.000984157228504640166702466253,64,2457,0.5,2,128,5
225,1761959879,41,127c23cb-d119-4ecc-b801-d8b643248022,1761959920,1761962920,3000,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 195 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 2534 --dropout 0.37322922272868008786 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c131,1206921,225_0,COMPLETED,BOTORCH_MODULAR,69.569999999999993178789736703038,195,0.001000000000000000020816681712,64,2534,0.373229222728680087861619085743,2,128,6
226,1761959879,24,127c23cb-d119-4ecc-b801-d8b643248022,1761959903,1761962721,2818,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 255 --learning_rate 0.00100000000000000002 --batch_size 808 --hidden_size 2750 --dropout 0 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c140,1206917,226_0,COMPLETED,BOTORCH_MODULAR,60.32000000000000028421709430404,255,0.001000000000000000020816681712,808,2750,0,2,128,6
227,1761959879,23,127c23cb-d119-4ecc-b801-d8b643248022,1761959902,1761962968,3066,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 198 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 2587 --dropout 0.38316514650722754975 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c139,1206918,227_0,COMPLETED,BOTORCH_MODULAR,70.14000000000000056843418860808,198,0.001000000000000000020816681712,64,2587,0.383165146507227549754759365896,2,128,6
228,1761959879,4,127c23cb-d119-4ecc-b801-d8b643248022,1761959883,1761962184,2301,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 137 --learning_rate 0.00097153023477931878 --batch_size 64 --hidden_size 2506 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 5,0,,c153,1206914,228_0,COMPLETED,BOTORCH_MODULAR,69.25,137,0.000971530234779318779131385142,64,2506,0.5,2,128,5
229,1761959881,39,127c23cb-d119-4ecc-b801-d8b643248022,1761959920,1761963209,3289,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 215 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 2198 --dropout 0.31142379031517769539 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c130,1206923,229_0,COMPLETED,BOTORCH_MODULAR,69.409999999999996589394868351519,215,0.001000000000000000020816681712,64,2198,0.311423790315177695386950063039,2,128,6
230,1761959881,39,127c23cb-d119-4ecc-b801-d8b643248022,1761959920,1761961185,1265,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 82 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 2035 --dropout 0.5 --num_dense_layers 1 --filter 109 --num_conv_layers 5,0,,c129,1206924,230_0,COMPLETED,BOTORCH_MODULAR,69.760000000000005115907697472721,82,0.001000000000000000020816681712,64,2035,0.5,1,109,5
231,1761959880,62,127c23cb-d119-4ecc-b801-d8b643248022,1761959942,1761962143,2201,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 139 --learning_rate 0.00096723529674895212 --batch_size 64 --hidden_size 2696 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 5,0,,c129,1206926,231_0,COMPLETED,BOTORCH_MODULAR,69.340000000000003410605131648481,139,0.000967235296748952116940856172,64,2696,0.5,2,128,5
232,1761959880,62,127c23cb-d119-4ecc-b801-d8b643248022,1761959942,1761962910,2968,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 252 --learning_rate 0.00100000000000000002 --batch_size 825 --hidden_size 2813 --dropout 0 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c127,1206927,232_0,COMPLETED,BOTORCH_MODULAR,60.520000000000003126388037344441,252,0.001000000000000000020816681712,825,2813,0,2,128,6
233,1761959881,71,127c23cb-d119-4ecc-b801-d8b643248022,1761959952,1761963265,3313,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 211 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 2267 --dropout 0.39874575128872791208 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c124,1206931,233_0,COMPLETED,BOTORCH_MODULAR,69.92000000000000170530256582424,211,0.001000000000000000020816681712,64,2267,0.398745751288727912076126358443,2,128,6
234,1761959879,28,127c23cb-d119-4ecc-b801-d8b643248022,1761959907,1761962183,2276,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 143 --learning_rate 0.00095457624822830277 --batch_size 64 --hidden_size 2731 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 5,0,,c139,1206919,234_0,COMPLETED,BOTORCH_MODULAR,69.71999999999999886313162278384,143,0.000954576248228302770386377585,64,2731,0.5,2,128,5
235,1761959881,61,127c23cb-d119-4ecc-b801-d8b643248022,1761959942,1761962128,2186,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 137 --learning_rate 0.00095829327441106335 --batch_size 64 --hidden_size 2576 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 5,0,,c124,1206928,235_0,COMPLETED,BOTORCH_MODULAR,69.25,137,0.000958293274411063352238859814,64,2576,0.5,2,128,5
236,1761959883,59,127c23cb-d119-4ecc-b801-d8b643248022,1761959942,1761961266,1324,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 84 --learning_rate 0.0009405138262032069 --batch_size 64 --hidden_size 3241 --dropout 0.49728602075861583209 --num_dense_layers 1 --filter 109 --num_conv_layers 5,0,,c124,1206929,236_0,COMPLETED,BOTORCH_MODULAR,70.680000000000006821210263296962,84,0.0009405138262032068955861841,64,3241,0.497286020758615832093596509367,1,109,5
237,1761959883,76,127c23cb-d119-4ecc-b801-d8b643248022,1761959959,1761961115,1156,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 73 --learning_rate 0.00092740823716000746 --batch_size 64 --hidden_size 3245 --dropout 0.5 --num_dense_layers 1 --filter 107 --num_conv_layers 5,0,,c124,1206930,237_0,COMPLETED,BOTORCH_MODULAR,69.560000000000002273736754432321,73,0.000927408237160007461151456365,64,3245,0.5,1,107,5
238,1761959892,76,127c23cb-d119-4ecc-b801-d8b643248022,1761959968,1761962060,2092,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 130 --learning_rate 0.00096653166987546344 --batch_size 64 --hidden_size 2692 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 5,0,,c123,1206932,238_0,COMPLETED,BOTORCH_MODULAR,69.39000000000000056843418860808,130,0.000966531669875463441722607261,64,2692,0.5,2,128,5
239,1761959892,89,127c23cb-d119-4ecc-b801-d8b643248022,1761959981,1761962260,2279,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 144 --learning_rate 0.00096668073834290031 --batch_size 64 --hidden_size 2731 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 5,0,,c123,1206933,239_0,COMPLETED,BOTORCH_MODULAR,69.480000000000003979039320256561,144,0.000966680738342900309177652129,64,2731,0.5,2,128,5
240,1761963461,24,127c23cb-d119-4ecc-b801-d8b643248022,1761963485,1761965774,2289,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 152 --learning_rate 0.00091343689224691286 --batch_size 64 --hidden_size 2694 --dropout 0.43578821525407418491 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c139,1206992,240_0,COMPLETED,BOTORCH_MODULAR,70.189999999999997726263245567679,152,0.000913436892246912855893026251,64,2694,0.435788215254074184912269629422,1,128,6
241,1761963461,3,127c23cb-d119-4ecc-b801-d8b643248022,1761963464,1761965747,2283,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 152 --learning_rate 0.00091528164945005959 --batch_size 64 --hidden_size 2696 --dropout 0.43632815439840644256 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c140,1206991,241_0,COMPLETED,BOTORCH_MODULAR,70.629999999999995452526491135359,152,0.000915281649450059588656036791,64,2696,0.436328154398406442560087725724,1,128,6
242,1761963462,22,127c23cb-d119-4ecc-b801-d8b643248022,1761963484,1761965791,2307,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 151 --learning_rate 0.00091492533675789699 --batch_size 64 --hidden_size 2604 --dropout 0.43626623612559051191 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c129,1206995,242_0,COMPLETED,BOTORCH_MODULAR,70.189999999999997726263245567679,151,0.000914925336757896985259708167,64,2604,0.436266236125590511907290647287,1,128,6
243,1761963462,44,127c23cb-d119-4ecc-b801-d8b643248022,1761963506,1761965755,2249,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 150 --learning_rate 0.0009142493158008938 --batch_size 64 --hidden_size 2700 --dropout 0.43706948568415787681 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c119,1207001,243_0,COMPLETED,BOTORCH_MODULAR,70.5,150,0.000914249315800893798227011455,64,2700,0.43706948568415787681473716475,1,128,6
244,1761963463,63,127c23cb-d119-4ecc-b801-d8b643248022,1761963526,1761965828,2302,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 152 --learning_rate 0.0009136703722722922 --batch_size 64 --hidden_size 2694 --dropout 0.43635351416824380566 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c118,1207004,244_0,COMPLETED,BOTORCH_MODULAR,70.5,152,0.000913670372272292201538956835,64,2694,0.436353514168243805659841427769,1,128,6
245,1761963461,24,127c23cb-d119-4ecc-b801-d8b643248022,1761963485,1761965755,2270,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 152 --learning_rate 0.00091451429649791807 --batch_size 64 --hidden_size 2689 --dropout 0.43623494961956427174 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c131,1206993,245_0,COMPLETED,BOTORCH_MODULAR,70.85999999999999943156581139192,152,0.000914514296497918074795030474,64,2689,0.436234949619564271738880734119,1,128,6
246,1761963462,42,127c23cb-d119-4ecc-b801-d8b643248022,1761963504,1761965805,2301,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 152 --learning_rate 0.00091471659060808033 --batch_size 64 --hidden_size 2690 --dropout 0.43594631488959278975 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c119,1207000,246_0,COMPLETED,BOTORCH_MODULAR,70.60999999999999943156581139192,152,0.000914716590608080333882345947,64,2690,0.435946314889592789754146906489,1,128,6
247,1761963462,23,127c23cb-d119-4ecc-b801-d8b643248022,1761963485,1761965750,2265,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 152 --learning_rate 0.0009151373006969 --batch_size 64 --hidden_size 2690 --dropout 0.43573104099165399505 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c124,1206997,247_0,COMPLETED,BOTORCH_MODULAR,70.14000000000000056843418860808,152,0.000915137300696900000268607656,64,2690,0.435731040991653995053667358661,1,128,6
248,1761963462,28,127c23cb-d119-4ecc-b801-d8b643248022,1761963490,1761965671,2181,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 146 --learning_rate 0.00091474631844938332 --batch_size 64 --hidden_size 2763 --dropout 0.4366712225456177987 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c123,1206999,248_0,COMPLETED,BOTORCH_MODULAR,70.519999999999996020960679743439,146,0.000914746318449383317983336639,64,2763,0.436671222545617798704853385061,1,128,6
249,1761963462,22,127c23cb-d119-4ecc-b801-d8b643248022,1761963484,1761965774,2290,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 152 --learning_rate 0.00091389608519002331 --batch_size 64 --hidden_size 2691 --dropout 0.43613305067277113869 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c130,1206994,249_0,COMPLETED,BOTORCH_MODULAR,70.700000000000002842170943040401,152,0.000913896085190023309101359228,64,2691,0.436133050672771138689398640054,1,128,6
250,1761963462,42,127c23cb-d119-4ecc-b801-d8b643248022,1761963504,1761966041,2537,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 168 --learning_rate 0.00091211328543105833 --batch_size 64 --hidden_size 2573 --dropout 0.43164179701930227573 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c119,1207002,250_0,COMPLETED,BOTORCH_MODULAR,70.180000000000006821210263296962,168,0.000912113285431058332455855897,64,2573,0.431641797019302275728591666848,1,128,6
251,1761963462,22,127c23cb-d119-4ecc-b801-d8b643248022,1761963484,1761966018,2534,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 152 --learning_rate 0.00091741116818562193 --batch_size 64 --hidden_size 2498 --dropout 0.43637577133855071088 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c127,1206996,251_0,COMPLETED,BOTORCH_MODULAR,70.379999999999995452526491135359,152,0.000917411168185621925773298724,64,2498,0.436375771338550710876091898172,1,128,6
252,1761963463,27,127c23cb-d119-4ecc-b801-d8b643248022,1761963490,1761965787,2297,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 152 --learning_rate 0.00091422523317698495 --batch_size 64 --hidden_size 2674 --dropout 0.43640855701920605592 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c124,1206998,252_0,COMPLETED,BOTORCH_MODULAR,70.379999999999995452526491135359,152,0.000914225233176984945770993107,64,2674,0.436408557019206055915816477864,1,128,6
253,1761963462,64,127c23cb-d119-4ecc-b801-d8b643248022,1761963526,1761965818,2292,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 152 --learning_rate 0.00091518157760720874 --batch_size 64 --hidden_size 2519 --dropout 0.43596125242599398364 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c118,1207003,253_0,COMPLETED,BOTORCH_MODULAR,70.67000000000000170530256582424,152,0.000915181577607208744662425914,64,2519,0.435961252425993983639074258463,1,128,6
254,1761963463,64,127c23cb-d119-4ecc-b801-d8b643248022,1761963527,1761965875,2348,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 152 --learning_rate 0.00091217455807699019 --batch_size 64 --hidden_size 2691 --dropout 0.43521831387225784482 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c118,1207006,254_0,COMPLETED,BOTORCH_MODULAR,70.480000000000003979039320256561,152,0.000912174558076990190172428363,64,2691,0.435218313872257844820978789357,1,128,6
255,1761963463,64,127c23cb-d119-4ecc-b801-d8b643248022,1761963527,1761965818,2291,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 152 --learning_rate 0.00091486687444738925 --batch_size 64 --hidden_size 2688 --dropout 0.43585729107199555621 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c118,1207005,255_0,COMPLETED,BOTORCH_MODULAR,70.60999999999999943156581139192,152,0.00091486687444738924637060995,64,2688,0.435857291071995556208662492281,1,128,6
256,1761963464,62,127c23cb-d119-4ecc-b801-d8b643248022,1761963526,1761965817,2291,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 152 --learning_rate 0.00091294493084861873 --batch_size 64 --hidden_size 2686 --dropout 0.43593218022979257631 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c117,1207007,256_0,COMPLETED,BOTORCH_MODULAR,70.189999999999997726263245567679,152,0.000912944930848618731687726946,64,2686,0.435932180229792576309222340569,1,128,6
257,1761963468,58,127c23cb-d119-4ecc-b801-d8b643248022,1761963526,1761965803,2277,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 152 --learning_rate 0.00091337447952532071 --batch_size 64 --hidden_size 2692 --dropout 0.43599741852621071159 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c117,1207008,257_0,COMPLETED,BOTORCH_MODULAR,70.379999999999995452526491135359,152,0.000913374479525320710077140873,64,2692,0.435997418526210711586799106954,1,128,6
258,1761963474,70,127c23cb-d119-4ecc-b801-d8b643248022,1761963544,1761965748,2204,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 147 --learning_rate 0.00091451380881876255 --batch_size 64 --hidden_size 2678 --dropout 0.43691880340027333673 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c117,1207009,258_0,COMPLETED,BOTORCH_MODULAR,70.450000000000002842170943040401,147,0.000914513808818762552639569652,64,2678,0.436918803400273336734471740783,1,128,6
259,1761963474,75,127c23cb-d119-4ecc-b801-d8b643248022,1761963549,1761965874,2325,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 152 --learning_rate 0.00091629784305670057 --batch_size 64 --hidden_size 2528 --dropout 0.43678069744201625246 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c117,1207010,259_0,COMPLETED,BOTORCH_MODULAR,70.340000000000003410605131648481,152,0.000916297843056700566863326252,64,2528,0.436780697442016252463048431309,1,128,6
260,1761966276,4,127c23cb-d119-4ecc-b801-d8b643248022,1761966280,1761968653,2373,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 153 --learning_rate 0.00061813832430709188 --batch_size 64 --hidden_size 2557 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c143,1207043,260_0,COMPLETED,BOTORCH_MODULAR,69.290000000000006252776074688882,153,0.000618138324307091879122877387,64,2557,0.5,2,128,6
261,1761966277,38,127c23cb-d119-4ecc-b801-d8b643248022,1761966315,1761968598,2283,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 146 --learning_rate 0.0006359868831492078 --batch_size 64 --hidden_size 2465 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c120,1207058,261_0,COMPLETED,BOTORCH_MODULAR,69.07999999999999829469743417576,146,0.000635986883149207795663804266,64,2465,0.5,2,128,6
262,1761966276,29,127c23cb-d119-4ecc-b801-d8b643248022,1761966305,1761968423,2118,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 139 --learning_rate 0.00064728117992735664 --batch_size 64 --hidden_size 1746 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c124,1207049,262_0,COMPLETED,BOTORCH_MODULAR,68.799999999999997157829056959599,139,0.000647281179927356635842028432,64,1746,0.5,2,128,6
263,1761966276,4,127c23cb-d119-4ecc-b801-d8b643248022,1761966280,1761968552,2272,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 151 --learning_rate 0.00063056129810353423 --batch_size 72 --hidden_size 2384 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c139,1207044,263_0,COMPLETED,BOTORCH_MODULAR,69.46999999999999886313162278384,151,0.000630561298103534230777289515,72,2384,0.5,2,128,6
264,1761966276,5,127c23cb-d119-4ecc-b801-d8b643248022,1761966281,1761968511,2230,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 146 --learning_rate 0.00063918826760941787 --batch_size 64 --hidden_size 2345 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c130,1207045,264_0,COMPLETED,BOTORCH_MODULAR,69.310000000000002273736754432321,146,0.000639188267609417867798349278,64,2345,0.5,2,128,6
265,1761966277,23,127c23cb-d119-4ecc-b801-d8b643248022,1761966300,1761968521,2221,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 141 --learning_rate 0.00064289681885124972 --batch_size 64 --hidden_size 2370 --dropout 0.5 --num_dense_layers 2 --filter 127 --num_conv_layers 6,0,,c123,1207052,265_0,COMPLETED,BOTORCH_MODULAR,69.439999999999997726263245567679,141,0.000642896818851249724456609069,64,2370,0.5,2,127,6
266,1761966277,28,127c23cb-d119-4ecc-b801-d8b643248022,1761966305,1761968547,2242,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 144 --learning_rate 0.00061789199447886967 --batch_size 64 --hidden_size 2738 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c123,1207053,266_0,COMPLETED,BOTORCH_MODULAR,69.310000000000002273736754432321,144,0.000617891994478869666096443325,64,2738,0.5,2,128,6
267,1761966278,29,127c23cb-d119-4ecc-b801-d8b643248022,1761966307,1761968569,2262,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 146 --learning_rate 0.00063485600674990917 --batch_size 64 --hidden_size 2344 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c124,1207050,267_0,COMPLETED,BOTORCH_MODULAR,69.299999999999997157829056959599,146,0.000634856006749909165635947783,64,2344,0.5,2,128,6
268,1761966276,24,127c23cb-d119-4ecc-b801-d8b643248022,1761966300,1761968566,2266,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 145 --learning_rate 0.00064742563027433443 --batch_size 64 --hidden_size 2300 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c129,1207046,268_0,COMPLETED,BOTORCH_MODULAR,69.510000000000005115907697472721,145,0.000647425630274334434725858056,64,2300,0.5,2,128,6
269,1761966277,33,127c23cb-d119-4ecc-b801-d8b643248022,1761966310,1761968601,2291,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 149 --learning_rate 0.00064139925314419567 --batch_size 64 --hidden_size 2111 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c122,1207055,269_0,COMPLETED,BOTORCH_MODULAR,69.64000000000000056843418860808,149,0.000641399253144195671816341076,64,2111,0.5,2,128,6
270,1761966278,22,127c23cb-d119-4ecc-b801-d8b643248022,1761966300,1761968546,2246,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 146 --learning_rate 0.00063785105364891652 --batch_size 64 --hidden_size 2330 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c123,1207051,270_0,COMPLETED,BOTORCH_MODULAR,69.450000000000002842170943040401,146,0.000637851053648916515442790498,64,2330,0.5,2,128,6
271,1761966277,28,127c23cb-d119-4ecc-b801-d8b643248022,1761966305,1761968574,2269,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 147 --learning_rate 0.00063599342686304638 --batch_size 64 --hidden_size 2386 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c124,1207047,271_0,COMPLETED,BOTORCH_MODULAR,68.950000000000002842170943040401,147,0.000635993426863046382342681273,64,2386,0.5,2,128,6
272,1761966278,22,127c23cb-d119-4ecc-b801-d8b643248022,1761966300,1761968446,2146,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 137 --learning_rate 0.00064040225402298753 --batch_size 64 --hidden_size 2425 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c122,1207054,272_0,COMPLETED,BOTORCH_MODULAR,69.07999999999999829469743417576,137,0.000640402254022987525716725798,64,2425,0.5,2,128,6
273,1761966278,32,127c23cb-d119-4ecc-b801-d8b643248022,1761966310,1761967735,1425,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 96 --learning_rate 0.0007209694937266839 --batch_size 82 --hidden_size 2663 --dropout 0.5 --num_dense_layers 2 --filter 117 --num_conv_layers 6,0,,c120,1207057,273_0,COMPLETED,BOTORCH_MODULAR,68.71999999999999886313162278384,96,0.000720969493726683900887419743,82,2663,0.5,2,117,6
274,1761966277,30,127c23cb-d119-4ecc-b801-d8b643248022,1761966307,1761968543,2236,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 143 --learning_rate 0.00065247304067604173 --batch_size 64 --hidden_size 2205 --dropout 0.5 --num_dense_layers 2 --filter 127 --num_conv_layers 6,0,,c124,1207048,274_0,COMPLETED,BOTORCH_MODULAR,70.299999999999997157829056959599,143,0.000652473040676041730195899859,64,2205,0.5,2,127,6
275,1761966278,33,127c23cb-d119-4ecc-b801-d8b643248022,1761966311,1761968543,2232,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 145 --learning_rate 0.0006425209809432324 --batch_size 64 --hidden_size 2341 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c120,1207056,275_0,COMPLETED,BOTORCH_MODULAR,69.17000000000000170530256582424,145,0.000642520980943232398671649541,64,2341,0.5,2,128,6
276,1761966281,30,127c23cb-d119-4ecc-b801-d8b643248022,1761966311,1761968768,2457,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 159 --learning_rate 0.00061413200301499156 --batch_size 64 --hidden_size 2631 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c119,1207059,276_0,COMPLETED,BOTORCH_MODULAR,69.569999999999993178789736703038,159,0.000614132003014991557574009384,64,2631,0.5,2,128,6
277,1761966281,29,127c23cb-d119-4ecc-b801-d8b643248022,1761966310,1761969736,3426,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 223 --learning_rate 0.00059745547092650557 --batch_size 64 --hidden_size 2268 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c119,1207060,277_0,COMPLETED,BOTORCH_MODULAR,69.120000000000004547473508864641,223,0.000597455470926505573421583239,64,2268,0.5,2,128,6
278,1761966281,39,127c23cb-d119-4ecc-b801-d8b643248022,1761966320,1761968587,2267,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 146 --learning_rate 0.00063043613311745202 --batch_size 64 --hidden_size 2461 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c119,1207061,278_0,COMPLETED,BOTORCH_MODULAR,69.019999999999996020960679743439,146,0.00063043613311745201784053183,64,2461,0.5,2,128,6
279,1761966284,42,127c23cb-d119-4ecc-b801-d8b643248022,1761966326,1761968342,2016,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 132 --learning_rate 0.00066172465349312987 --batch_size 64 --hidden_size 1522 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c118,1207062,279_0,COMPLETED,BOTORCH_MODULAR,69.17000000000000170530256582424,132,0.000661724653493129871470457282,64,1522,0.5,2,128,6
280,1761970004,26,127c23cb-d119-4ecc-b801-d8b643248022,1761970030,1761972423,2393,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 154 --learning_rate 0.00084772297213864061 --batch_size 64 --hidden_size 3260 --dropout 0.34387155397816898672 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c119,1207109,280_0,COMPLETED,BOTORCH_MODULAR,71.150000000000005684341886080801,154,0.000847722972138640609371385004,64,3260,0.343871553978168986720476141272,1,128,5
281,1761970004,56,127c23cb-d119-4ecc-b801-d8b643248022,1761970060,1761971615,1555,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 132 --learning_rate 0.00100000000000000002 --batch_size 294 --hidden_size 2689 --dropout 0.42767757669105316287 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c118,1207115,281_0,COMPLETED,BOTORCH_MODULAR,67.900000000000005684341886080801,132,0.001000000000000000020816681712,294,2689,0.427677576691053162871725135119,1,128,6
282,1761970003,15,127c23cb-d119-4ecc-b801-d8b643248022,1761970018,1761971827,1809,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 150 --learning_rate 0.00100000000000000002 --batch_size 222 --hidden_size 2615 --dropout 0.42126919532493828369 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c120,1207106,282_0,COMPLETED,BOTORCH_MODULAR,68.980000000000003979039320256561,150,0.001000000000000000020816681712,222,2615,0.421269195324938283686577733533,1,128,6
283,1761970004,24,127c23cb-d119-4ecc-b801-d8b643248022,1761970028,1761972569,2541,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 162 --learning_rate 0.0008355496673449189 --batch_size 64 --hidden_size 3570 --dropout 0.32591437377852622292 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c120,1207108,283_0,COMPLETED,BOTORCH_MODULAR,71.35999999999999943156581139192,162,0.000835549667344918900978301135,64,3570,0.325914373778526222924512012469,1,128,5
284,1761970004,14,127c23cb-d119-4ecc-b801-d8b643248022,1761970018,1761971947,1929,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 156 --learning_rate 0.00095963385138640278 --batch_size 195 --hidden_size 2858 --dropout 0.37694233175769303879 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c120,1207107,284_0,COMPLETED,BOTORCH_MODULAR,69.650000000000005684341886080801,156,0.000959633851386402776488526722,195,2858,0.376942331757693038785106409705,1,128,5
285,1761970004,43,127c23cb-d119-4ecc-b801-d8b643248022,1761970047,1761971405,1358,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 120 --learning_rate 0.00100000000000000002 --batch_size 308 --hidden_size 2183 --dropout 0.45500405550264599874 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c119,1207110,285_0,COMPLETED,BOTORCH_MODULAR,68.200000000000002842170943040401,120,0.001000000000000000020816681712,308,2183,0.45500405550264599874310533778,1,128,6
286,1761970003,15,127c23cb-d119-4ecc-b801-d8b643248022,1761970018,1761972486,2468,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 158 --learning_rate 0.00084967877227256684 --batch_size 64 --hidden_size 3217 --dropout 0.34596610248567660761 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c120,1207105,286_0,COMPLETED,BOTORCH_MODULAR,71.409999999999996589394868351519,158,0.000849678772272566837711615939,64,3217,0.345966102485676607614095701138,1,128,5
287,1761970004,48,127c23cb-d119-4ecc-b801-d8b643248022,1761970052,1761971731,1679,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 139 --learning_rate 0.00100000000000000002 --batch_size 243 --hidden_size 2952 --dropout 0.39069741469740565387 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c119,1207111,287_0,COMPLETED,BOTORCH_MODULAR,69.459999999999993747223925311118,139,0.001000000000000000020816681712,243,2952,0.390697414697405653871697950308,1,128,5
288,1761970004,49,127c23cb-d119-4ecc-b801-d8b643248022,1761970053,1761971741,1688,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 141 --learning_rate 0.00100000000000000002 --batch_size 275 --hidden_size 3352 --dropout 0.37181883369418167185 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c118,1207113,288_0,COMPLETED,BOTORCH_MODULAR,69.370000000000004547473508864641,141,0.001000000000000000020816681712,275,3352,0.371818833694181671845058190229,1,128,5
289,1761970005,48,127c23cb-d119-4ecc-b801-d8b643248022,1761970053,1761972541,2488,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 160 --learning_rate 0.00084817871500906053 --batch_size 64 --hidden_size 3291 --dropout 0.34032271551642440111 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c118,1207114,289_0,COMPLETED,BOTORCH_MODULAR,70.82999999999999829469743417576,160,0.000848178715009060527237061411,64,3291,0.340322715516424401105410879609,1,128,5
290,1761970004,84,127c23cb-d119-4ecc-b801-d8b643248022,1761970088,1761972599,2511,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 160 --learning_rate 0.00084848026307001096 --batch_size 64 --hidden_size 3217 --dropout 0.34380192177896501393 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c117,1207119,290_0,COMPLETED,BOTORCH_MODULAR,70.599999999999994315658113919199,160,0.000848480263070010959879085899,64,3217,0.343801921778965013931639305156,1,128,5
291,1761970007,80,127c23cb-d119-4ecc-b801-d8b643248022,1761970087,1761971873,1786,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 144 --learning_rate 0.00095586940608642255 --batch_size 184 --hidden_size 2997 --dropout 0.37950324309811533929 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c116,1207120,291_0,COMPLETED,BOTORCH_MODULAR,69.659999999999996589394868351519,144,0.000955869406086422550988812574,184,2997,0.37950324309811533929348570382,1,128,5
292,1761970004,62,127c23cb-d119-4ecc-b801-d8b643248022,1761970066,1761972593,2527,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 163 --learning_rate 0.00085416715662047903 --batch_size 64 --hidden_size 3149 --dropout 0.34491364793223744378 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c117,1207116,292_0,COMPLETED,BOTORCH_MODULAR,70.540000000000006252776074688882,163,0.00085416715662047903306897112,64,3149,0.344913647932237443782810260018,1,128,5
293,1761970004,49,127c23cb-d119-4ecc-b801-d8b643248022,1761970053,1761972529,2476,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 159 --learning_rate 0.00083879929070085086 --batch_size 64 --hidden_size 3395 --dropout 0.33107778229414663862 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c118,1207112,293_0,COMPLETED,BOTORCH_MODULAR,70.82999999999999829469743417576,159,0.000838799290700850859459070108,64,3395,0.331077782294146638619736222608,1,128,5
294,1761970005,83,127c23cb-d119-4ecc-b801-d8b643248022,1761970088,1761972549,2461,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 159 --learning_rate 0.00085047622031400464 --batch_size 64 --hidden_size 3254 --dropout 0.34362126751495625232 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c117,1207117,294_0,COMPLETED,BOTORCH_MODULAR,70.96999999999999886313162278384,159,0.000850476220314004636297022799,64,3254,0.343621267514956252320246221643,1,128,5
295,1761970006,81,127c23cb-d119-4ecc-b801-d8b643248022,1761970087,1761972518,2431,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 157 --learning_rate 0.00085895731385957986 --batch_size 64 --hidden_size 3035 --dropout 0.35268342526776241819 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c117,1207118,295_0,COMPLETED,BOTORCH_MODULAR,70.840000000000003410605131648481,157,0.000858957313859579855291892514,64,3035,0.352683425267762418187089679122,1,128,5
296,1761970009,83,127c23cb-d119-4ecc-b801-d8b643248022,1761970092,1761971966,1874,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 154 --learning_rate 0.00097723306840761994 --batch_size 199 --hidden_size 2762 --dropout 0.38065512071041823772 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c116,1207121,296_0,COMPLETED,BOTORCH_MODULAR,69.200000000000002842170943040401,154,0.000977233068407619941131425634,199,2762,0.380655120710418237717220790728,1,128,5
297,1761970009,88,127c23cb-d119-4ecc-b801-d8b643248022,1761970097,1761971594,1497,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 128 --learning_rate 0.00100000000000000002 --batch_size 302 --hidden_size 2565 --dropout 0.44346070305413431978 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c115,1207122,297_0,COMPLETED,BOTORCH_MODULAR,68.409999999999996589394868351519,128,0.001000000000000000020816681712,302,2565,0.443460703054134319778256667632,1,128,6
298,1761970009,90,127c23cb-d119-4ecc-b801-d8b643248022,1761970099,1761971878,1779,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 146 --learning_rate 0.00097870726053353647 --batch_size 213 --hidden_size 3095 --dropout 0.38173205695452844255 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c115,1207123,298_0,COMPLETED,BOTORCH_MODULAR,69.290000000000006252776074688882,146,0.000978707260533536469240822875,213,3095,0.381732056954528442549445799159,1,128,5
299,1761970016,81,127c23cb-d119-4ecc-b801-d8b643248022,1761970097,1761971764,1667,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 137 --learning_rate 0.00100000000000000002 --batch_size 277 --hidden_size 3388 --dropout 0.37969709975710519423 --num_dense_layers 1 --filter 127 --num_conv_layers 5,0,,c115,1207124,299_0,COMPLETED,BOTORCH_MODULAR,68.790000000000006252776074688882,137,0.001000000000000000020816681712,277,3388,0.379697099757105194228756772645,1,127,5
300,1761972915,3,127c23cb-d119-4ecc-b801-d8b643248022,1761972918,1761974957,2039,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 132 --learning_rate 0.0008693361649341158 --batch_size 64 --hidden_size 2801 --dropout 0.37074478519478498706 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c141,1207145,300_0,COMPLETED,BOTORCH_MODULAR,70.569999999999993178789736703038,132,0.000869336164934115802720160371,64,2801,0.370744785194784987059080094696,1,128,5
301,1761972915,54,127c23cb-d119-4ecc-b801-d8b643248022,1761972969,1761975879,2910,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 187 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 1952 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 7,0,,c120,1207154,301_0,COMPLETED,BOTORCH_MODULAR,68.510000000000005115907697472721,187,0.001000000000000000020816681712,64,1952,0.5,2,128,7
302,1761972916,53,127c23cb-d119-4ecc-b801-d8b643248022,1761972969,1761975362,2393,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 158 --learning_rate 0.00076121410400414966 --batch_size 64 --hidden_size 3670 --dropout 0.16979949748194350656 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c120,1207156,302_0,COMPLETED,BOTORCH_MODULAR,68.540000000000006252776074688882,158,0.000761214104004149659694899999,64,3670,0.169799497481943506560497780811,1,128,6
303,1761972915,3,127c23cb-d119-4ecc-b801-d8b643248022,1761972918,1761976104,3186,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 204 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 1664 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 7,0,,c140,1207146,303_0,COMPLETED,BOTORCH_MODULAR,68.659999999999996589394868351519,204,0.001000000000000000020816681712,64,1664,0.5,2,128,7
304,1761972915,23,127c23cb-d119-4ecc-b801-d8b643248022,1761972938,1761976128,3190,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 207 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 1670 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 7,0,,c123,1207149,304_0,COMPLETED,BOTORCH_MODULAR,69.180000000000006821210263296962,207,0.001000000000000000020816681712,64,1670,0.5,2,128,7
305,1761972915,23,127c23cb-d119-4ecc-b801-d8b643248022,1761972938,1761974980,2042,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 132 --learning_rate 0.00084635686407743388 --batch_size 64 --hidden_size 3089 --dropout 0.36332922150164087549 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c123,1207148,305_0,COMPLETED,BOTORCH_MODULAR,70.78000000000000113686837721616,132,0.000846356864077433884360757155,64,3089,0.363329221501640875491290216814,1,128,5
306,1761972915,44,127c23cb-d119-4ecc-b801-d8b643248022,1761972959,1761975982,3023,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 194 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 1924 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 7,0,,c122,1207152,306_0,COMPLETED,BOTORCH_MODULAR,69.10999999999999943156581139192,194,0.001000000000000000020816681712,64,1924,0.5,2,128,7
307,1761972915,55,127c23cb-d119-4ecc-b801-d8b643248022,1761972970,1761975692,2722,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 156 --learning_rate 0.00074361492650526495 --batch_size 64 --hidden_size 3494 --dropout 0.33156488596164346294 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c127,1207157,307_0,COMPLETED,BOTORCH_MODULAR,70.989999999999994884092302527279,156,0.000743614926505264950407081415,64,3494,0.331564885961643462941594862059,1,128,5
308,1761972915,43,127c23cb-d119-4ecc-b801-d8b643248022,1761972958,1761975332,2374,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 153 --learning_rate 0.00085020659983624822 --batch_size 64 --hidden_size 3061 --dropout 0.3687165413899954336 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c122,1207151,308_0,COMPLETED,BOTORCH_MODULAR,70.950000000000002842170943040401,153,0.0008502065998362482151379238,64,3061,0.368716541389995433597448482033,1,128,5
309,1761972916,53,127c23cb-d119-4ecc-b801-d8b643248022,1761972969,1761974705,1736,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 110 --learning_rate 0.000659208313713672 --batch_size 64 --hidden_size 4020 --dropout 0.30417760661086645779 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c120,1207155,309_0,COMPLETED,BOTORCH_MODULAR,70.25,110,0.000659208313713672004914567726,64,4020,0.304177606610866457792496930779,1,128,5
310,1761972915,25,127c23cb-d119-4ecc-b801-d8b643248022,1761972940,1761977179,4239,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 280 --learning_rate 0.0006825428084830475 --batch_size 64 --hidden_size 2688 --dropout 0.06247149799780878782 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c123,1207150,310_0,COMPLETED,BOTORCH_MODULAR,67.799999999999997157829056959599,280,0.000682542808483047503016749591,64,2688,0.062471497997808787816520492697,1,128,6
311,1761972915,3,127c23cb-d119-4ecc-b801-d8b643248022,1761972918,1761977388,4470,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 300 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 3716 --dropout 0.47904565307920038419 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c131,1207147,311_0,COMPLETED,BOTORCH_MODULAR,70.989999999999994884092302527279,300,0.001000000000000000020816681712,64,3716,0.479045653079200384194535899951,1,128,6
312,1761972917,53,127c23cb-d119-4ecc-b801-d8b643248022,1761972970,1761975463,2493,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 159 --learning_rate 0.00069642735000759366 --batch_size 64 --hidden_size 3790 --dropout 0.32079696835758336748 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c119,1207159,312_0,COMPLETED,BOTORCH_MODULAR,70.959999999999993747223925311118,159,0.000696427350007593659771132355,64,3790,0.320796968357583367481566938295,1,128,5
313,1761972916,62,127c23cb-d119-4ecc-b801-d8b643248022,1761972978,1761975386,2408,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 159 --learning_rate 0.0006527179343178756 --batch_size 64 --hidden_size 3811 --dropout 0.20147484331509069033 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c119,1207160,313_0,COMPLETED,BOTORCH_MODULAR,68.650000000000005684341886080801,159,0.000652717934317875595265356914,64,3811,0.20147484331509069033216974276,1,128,6
314,1761972916,44,127c23cb-d119-4ecc-b801-d8b643248022,1761972960,1761976139,3179,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 206 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 1742 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 7,0,,c122,1207153,314_0,COMPLETED,BOTORCH_MODULAR,69,206,0.001000000000000000020816681712,64,1742,0.5,2,128,7
315,1761972917,54,127c23cb-d119-4ecc-b801-d8b643248022,1761972971,1761975447,2476,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 156 --learning_rate 0.00062129254209713038 --batch_size 64 --hidden_size 4021 --dropout 0.27741122751492675036 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c120,1207158,315_0,COMPLETED,BOTORCH_MODULAR,70.290000000000006252776074688882,156,0.000621292542097130382448832986,64,4021,0.277411227514926750359336438123,1,128,5
316,1761972920,78,127c23cb-d119-4ecc-b801-d8b643248022,1761972998,1761976087,3089,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 199 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 1657 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 7,0,,c119,1207161,316_0,COMPLETED,BOTORCH_MODULAR,68.980000000000003979039320256561,199,0.001000000000000000020816681712,64,1657,0.5,2,128,7
317,1761972920,84,127c23cb-d119-4ecc-b801-d8b643248022,1761973004,1761975407,2403,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 158 --learning_rate 0.00080727705720691153 --batch_size 64 --hidden_size 3627 --dropout 0.20888594678900113122 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c118,1207162,317_0,COMPLETED,BOTORCH_MODULAR,69.25,158,0.000807277057206911533189519492,64,3627,0.208885946789001131218554974112,1,128,6
318,1761972920,85,127c23cb-d119-4ecc-b801-d8b643248022,1761973005,1761976160,3155,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 205 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 1702 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 7,0,,c118,1207163,318_0,COMPLETED,BOTORCH_MODULAR,69.17000000000000170530256582424,205,0.001000000000000000020816681712,64,1702,0.5,2,128,7
319,1761972927,77,127c23cb-d119-4ecc-b801-d8b643248022,1761973004,1761976336,3332,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 221 --learning_rate 0.00070421333453786006 --batch_size 64 --hidden_size 3668 --dropout 0.19378608489325713227 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c118,1207164,319_0,COMPLETED,BOTORCH_MODULAR,69.260000000000005115907697472721,221,0.00070421333453786006187358204,64,3668,0.193786084893257132266697340128,1,128,6
320,1761977733,37,127c23cb-d119-4ecc-b801-d8b643248022,1761977770,1761982512,4742,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 300 --learning_rate 0.00088485798525506662 --batch_size 64 --hidden_size 3737 --dropout 0.39698109316480878483 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c130,1207213,320_0,COMPLETED,BOTORCH_MODULAR,70.60999999999999943156581139192,300,0.000884857985255066621134434346,64,3737,0.39698109316480878483446304017,1,128,5
321,1761977733,3,127c23cb-d119-4ecc-b801-d8b643248022,1761977736,1761981464,3728,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 239 --learning_rate 0.00089343705030056977 --batch_size 64 --hidden_size 3079 --dropout 0.38267663244853750149 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c140,1207207,321_0,COMPLETED,BOTORCH_MODULAR,71.040000000000006252776074688882,239,0.000893437050300569771295322585,64,3079,0.382676632448537501485219536335,1,128,5
322,1761977733,3,127c23cb-d119-4ecc-b801-d8b643248022,1761977736,1761982198,4462,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 300 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 2933 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c141,1207206,322_0,COMPLETED,BOTORCH_MODULAR,69.900000000000005684341886080801,300,0.001000000000000000020816681712,64,2933,0.5,1,128,6
323,1761977733,23,127c23cb-d119-4ecc-b801-d8b643248022,1761977756,1761981474,3718,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 239 --learning_rate 0.00090109369563230171 --batch_size 64 --hidden_size 3077 --dropout 0.38451796832738283083 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c139,1207209,323_0,COMPLETED,BOTORCH_MODULAR,70.71999999999999886313162278384,239,0.000901093695632301707604261409,64,3077,0.384517968327382830828753412789,1,128,5
324,1761977733,28,127c23cb-d119-4ecc-b801-d8b643248022,1761977761,1761981479,3718,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 240 --learning_rate 0.00089500174889059611 --batch_size 64 --hidden_size 3136 --dropout 0.3865800477171033589 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c131,1207211,324_0,COMPLETED,BOTORCH_MODULAR,70.810000000000002273736754432321,240,0.000895001748890596107027795014,64,3136,0.386580047717103358895229803238,1,128,5
325,1761977733,23,127c23cb-d119-4ecc-b801-d8b643248022,1761977756,1761981705,3949,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 250 --learning_rate 0.00087558106496025024 --batch_size 64 --hidden_size 3510 --dropout 0.38617629966118172113 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c131,1207210,325_0,COMPLETED,BOTORCH_MODULAR,70.939999999999997726263245567679,250,0.000875581064960250237023953179,64,3510,0.386176299661181721134539657214,1,128,5
326,1761977733,63,127c23cb-d119-4ecc-b801-d8b643248022,1761977796,1761981842,4046,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 240 --learning_rate 0.00089590112218763702 --batch_size 64 --hidden_size 3189 --dropout 0.38733826485534716966 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c127,1207219,326_0,COMPLETED,BOTORCH_MODULAR,70.650000000000005684341886080801,240,0.0008959011221876370155772773,64,3189,0.387338264855347169657306949375,1,128,5
327,1761977734,22,127c23cb-d119-4ecc-b801-d8b643248022,1761977756,1761982251,4495,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 300 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 2955 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c130,1207212,327_0,COMPLETED,BOTORCH_MODULAR,70.340000000000003410605131648481,300,0.001000000000000000020816681712,64,2955,0.5,1,128,6
328,1761977735,61,127c23cb-d119-4ecc-b801-d8b643248022,1761977796,1761982694,4898,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 299 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 2959 --dropout 0.5 --num_dense_layers 1 --filter 121 --num_conv_layers 6,0,,c125,1207221,328_0,COMPLETED,BOTORCH_MODULAR,70.17000000000000170530256582424,299,0.001000000000000000020816681712,64,2959,0.5,1,121,6
329,1761977734,64,127c23cb-d119-4ecc-b801-d8b643248022,1761977798,1761981271,3473,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 222 --learning_rate 0.00087074258853842706 --batch_size 64 --hidden_size 3449 --dropout 0.38730294790007246952 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c129,1207217,329_0,COMPLETED,BOTORCH_MODULAR,71.290000000000006252776074688882,222,0.000870742588538427064737135197,64,3449,0.387302947900072469522569917899,1,128,5
330,1761977734,36,127c23cb-d119-4ecc-b801-d8b643248022,1761977770,1761981425,3655,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 239 --learning_rate 0.00090058491524209225 --batch_size 64 --hidden_size 3076 --dropout 0.38484148225523029385 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c130,1207214,330_0,COMPLETED,BOTORCH_MODULAR,70.980000000000003979039320256561,239,0.000900584915242092247031346908,64,3076,0.384841482255230293851866463228,1,128,5
331,1761977735,63,127c23cb-d119-4ecc-b801-d8b643248022,1761977798,1761981570,3772,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 240 --learning_rate 0.00089259146176033936 --batch_size 64 --hidden_size 3120 --dropout 0.3824018499250164127 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c126,1207220,331_0,COMPLETED,BOTORCH_MODULAR,71.019999999999996020960679743439,240,0.000892591461760339362728478019,64,3120,0.382401849925016412701239687522,1,128,5
332,1761977733,23,127c23cb-d119-4ecc-b801-d8b643248022,1761977756,1761982476,4720,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 300 --learning_rate 0.00089874772453797398 --batch_size 64 --hidden_size 3503 --dropout 0.39397179150364181055 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c139,1207208,332_0,COMPLETED,BOTORCH_MODULAR,71.010000000000005115907697472721,300,0.000898747724537973975700300144,64,3503,0.39397179150364181055010703858,1,128,5
333,1761977735,54,127c23cb-d119-4ecc-b801-d8b643248022,1761977789,1761981573,3784,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 239 --learning_rate 0.00090016540130729249 --batch_size 64 --hidden_size 3078 --dropout 0.38717871263419090244 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c129,1207215,333_0,COMPLETED,BOTORCH_MODULAR,70.659999999999996589394868351519,239,0.000900165401307292489634093169,64,3078,0.387178712634190902441844173154,1,128,5
334,1761977734,64,127c23cb-d119-4ecc-b801-d8b643248022,1761977798,1761981826,4028,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 261 --learning_rate 0.00087389527630511092 --batch_size 64 --hidden_size 3817 --dropout 0.40242319529136194589 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c129,1207218,334_0,COMPLETED,BOTORCH_MODULAR,70.769999999999996020960679743439,261,0.000873895276305110919531915492,64,3817,0.402423195291361945891139839659,1,128,5
335,1761977734,62,127c23cb-d119-4ecc-b801-d8b643248022,1761977796,1761982310,4514,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 300 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 2920 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c129,1207216,335_0,COMPLETED,BOTORCH_MODULAR,70.510000000000005115907697472721,300,0.001000000000000000020816681712,64,2920,0.5,1,128,6
336,1761977737,65,127c23cb-d119-4ecc-b801-d8b643248022,1761977802,1761982315,4513,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 300 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 2960 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c124,1207222,336_0,COMPLETED,BOTORCH_MODULAR,70.599999999999994315658113919199,300,0.001000000000000000020816681712,64,2960,0.5,1,128,6
337,1761977737,65,127c23cb-d119-4ecc-b801-d8b643248022,1761977802,1761981818,4016,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 255 --learning_rate 0.00087206048354747487 --batch_size 64 --hidden_size 3739 --dropout 0.39556065657258376866 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c124,1207223,337_0,COMPLETED,BOTORCH_MODULAR,70.900000000000005684341886080801,255,0.000872060483547474870127946822,64,3739,0.395560656572583768664230774448,1,128,5
338,1761977740,76,127c23cb-d119-4ecc-b801-d8b643248022,1761977816,1761981550,3734,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 239 --learning_rate 0.00089831794702650738 --batch_size 64 --hidden_size 3083 --dropout 0.38390276554145597032 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c124,1207224,338_0,COMPLETED,BOTORCH_MODULAR,70.730000000000003979039320256561,239,0.000898317947026507383420645958,64,3083,0.383902765541455970321749191498,1,128,5
339,1761977745,85,127c23cb-d119-4ecc-b801-d8b643248022,1761977830,1761981500,3670,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 233 --learning_rate 0.00088984625366766838 --batch_size 64 --hidden_size 3127 --dropout 0.38353417279793089456 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c124,1207225,339_0,COMPLETED,BOTORCH_MODULAR,71.10999999999999943156581139192,233,0.000889846253667668377410060465,64,3127,0.383534172797930894560636261303,1,128,5
340,1761983073,43,127c23cb-d119-4ecc-b801-d8b643248022,1761983116,1761986092,2976,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 191 --learning_rate 0.00086011404654112603 --batch_size 64 --hidden_size 3328 --dropout 0.37960450535874906697 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c129,1207282,340_0,COMPLETED,BOTORCH_MODULAR,70.89000000000000056843418860808,191,0.000860114046541126026947099437,64,3328,0.379604505358749066967760654734,1,128,5
341,1761983072,4,127c23cb-d119-4ecc-b801-d8b643248022,1761983076,1761985880,2804,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 174 --learning_rate 0.00087774819708183308 --batch_size 64 --hidden_size 3566 --dropout 0.401389269835950524 --num_dense_layers 1 --filter 126 --num_conv_layers 5,0,,c149,1207270,341_0,COMPLETED,BOTORCH_MODULAR,70.870000000000004547473508864641,174,0.00087774819708183308454574334,64,3566,0.401389269835950524001333405977,1,126,5
342,1761983073,43,127c23cb-d119-4ecc-b801-d8b643248022,1761983116,1761986597,3481,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 300 --learning_rate 0.00100000000000000002 --batch_size 359 --hidden_size 4021 --dropout 0 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c129,1207281,342_0,COMPLETED,BOTORCH_MODULAR,65.67000000000000170530256582424,300,0.001000000000000000020816681712,359,4021,0,1,128,5
343,1761983073,3,127c23cb-d119-4ecc-b801-d8b643248022,1761983076,1761985734,2658,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 169 --learning_rate 0.00087684554337564972 --batch_size 64 --hidden_size 3744 --dropout 0.40928750710440464644 --num_dense_layers 1 --filter 124 --num_conv_layers 5,0,,c139,1207272,343_0,COMPLETED,BOTORCH_MODULAR,71.060000000000002273736754432321,169,0.000876845543375649716898168062,64,3744,0.40928750710440464644079838763,1,124,5
344,1761983075,36,127c23cb-d119-4ecc-b801-d8b643248022,1761983111,1761986762,3651,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 218 --learning_rate 0.00081589199715522895 --batch_size 64 --hidden_size 3566 --dropout 0.39870928972471764151 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c125,1207285,344_0,COMPLETED,BOTORCH_MODULAR,71.07999999999999829469743417576,218,0.000815891997155228951114913638,64,3566,0.398709289724717641512086174771,1,128,5
345,1761983073,26,127c23cb-d119-4ecc-b801-d8b643248022,1761983099,1761986506,3407,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 218 --learning_rate 0.00081400913495975028 --batch_size 64 --hidden_size 3471 --dropout 0.38506826844326952353 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c131,1207275,345_0,COMPLETED,BOTORCH_MODULAR,70.959999999999993747223925311118,218,0.000814009134959750276297474336,64,3471,0.385068268443269523526595321528,1,128,5
346,1761983074,22,127c23cb-d119-4ecc-b801-d8b643248022,1761983096,1761986386,3290,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 211 --learning_rate 0.0008439667520848314 --batch_size 64 --hidden_size 3238 --dropout 0.35127537591335167289 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c130,1207278,346_0,COMPLETED,BOTORCH_MODULAR,70.900000000000005684341886080801,211,0.000843966752084831400328168716,64,3238,0.35127537591335167288519869544,1,128,5
347,1761983074,24,127c23cb-d119-4ecc-b801-d8b643248022,1761983098,1761986860,3762,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 239 --learning_rate 0.0007896676073510196 --batch_size 64 --hidden_size 4043 --dropout 0.44077678790880370219 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c130,1207276,347_0,COMPLETED,BOTORCH_MODULAR,70.989999999999994884092302527279,239,0.000789667607351019601967523354,64,4043,0.440776787908803702187299222715,1,128,5
348,1761983072,9,127c23cb-d119-4ecc-b801-d8b643248022,1761983081,1761986027,2946,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 182 --learning_rate 0.00085688883739359325 --batch_size 64 --hidden_size 3862 --dropout 0.42241023729803556241 --num_dense_layers 1 --filter 127 --num_conv_layers 5,0,,c139,1207273,348_0,COMPLETED,BOTORCH_MODULAR,70.560000000000002273736754432321,182,0.000856888837393593254775081558,64,3862,0.422410237298035562414355581495,1,127,5
349,1761983073,3,127c23cb-d119-4ecc-b801-d8b643248022,1761983076,1761987631,4555,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 300 --learning_rate 0.00079271138792372459 --batch_size 64 --hidden_size 4096 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c140,1207271,349_0,COMPLETED,BOTORCH_MODULAR,70.519999999999996020960679743439,300,0.000792711387923724589837926047,64,4096,0.5,1,128,6
350,1761983073,23,127c23cb-d119-4ecc-b801-d8b643248022,1761983096,1761986153,3057,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 197 --learning_rate 0.00093648492198588251 --batch_size 71 --hidden_size 3399 --dropout 0.40328839598622567841 --num_dense_layers 1 --filter 119 --num_conv_layers 5,0,,c131,1207274,350_0,COMPLETED,BOTORCH_MODULAR,70.879999999999995452526491135359,197,0.000936484921985882511584475818,71,3399,0.403288395986225678413461537275,1,119,5
351,1761983074,37,127c23cb-d119-4ecc-b801-d8b643248022,1761983111,1761987483,4372,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 277 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 2104 --dropout 0.5 --num_dense_layers 2 --filter 109 --num_conv_layers 6,0,,c126,1207284,351_0,COMPLETED,BOTORCH_MODULAR,68.599999999999994315658113919199,277,0.001000000000000000020816681712,64,2104,0.5,2,109,6
352,1761983073,24,127c23cb-d119-4ecc-b801-d8b643248022,1761983097,1761986597,3500,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 223 --learning_rate 0.0008070288309107882 --batch_size 64 --hidden_size 3598 --dropout 0.37590633903118619852 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c130,1207277,352_0,COMPLETED,BOTORCH_MODULAR,70.840000000000003410605131648481,223,0.000807028830910788198306493602,64,3598,0.37590633903118619851824178113,1,128,5
353,1761983073,43,127c23cb-d119-4ecc-b801-d8b643248022,1761983116,1761986417,3301,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 300 --learning_rate 0.00100000000000000002 --batch_size 754 --hidden_size 2786 --dropout 0.5 --num_dense_layers 1 --filter 106 --num_conv_layers 5,0,,c129,1207280,353_0,COMPLETED,BOTORCH_MODULAR,63.82000000000000028421709430404,300,0.001000000000000000020816681712,754,2786,0.5,1,106,5
354,1761983073,43,127c23cb-d119-4ecc-b801-d8b643248022,1761983116,1761986560,3444,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 211 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 3805 --dropout 0.5 --num_dense_layers 2 --filter 89 --num_conv_layers 5,0,,c129,1207279,354_0,COMPLETED,BOTORCH_MODULAR,68.010000000000005115907697472721,211,0.001000000000000000020816681712,64,3805,0.5,2,89,5
355,1761983074,37,127c23cb-d119-4ecc-b801-d8b643248022,1761983111,1761986913,3802,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 217 --learning_rate 0.0008313598338326474 --batch_size 64 --hidden_size 3322 --dropout 0.34927079277408235036 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c127,1207283,355_0,COMPLETED,BOTORCH_MODULAR,70.540000000000006252776074688882,217,0.000831359833832647399272375299,64,3322,0.349270792774082350362618853978,1,128,5
356,1761983078,39,127c23cb-d119-4ecc-b801-d8b643248022,1761983117,1761986420,3303,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 300 --learning_rate 0.00100000000000000002 --batch_size 746 --hidden_size 3454 --dropout 0.5 --num_dense_layers 1 --filter 106 --num_conv_layers 5,0,,c124,1207286,356_0,COMPLETED,BOTORCH_MODULAR,62.990000000000001989519660128281,300,0.001000000000000000020816681712,746,3454,0.5,1,106,5
357,1761983078,60,127c23cb-d119-4ecc-b801-d8b643248022,1761983138,1761986104,2966,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 189 --learning_rate 0.00086099731905751582 --batch_size 64 --hidden_size 3243 --dropout 0.37943011978423707431 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c124,1207288,357_0,COMPLETED,BOTORCH_MODULAR,70.629999999999995452526491135359,189,0.000860997319057515823371995456,64,3243,0.379430119784237074309629633717,1,128,5
358,1761983078,39,127c23cb-d119-4ecc-b801-d8b643248022,1761983117,1761986164,3047,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 198 --learning_rate 0.00086207801971627392 --batch_size 64 --hidden_size 3085 --dropout 0.36273174162827320766 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c124,1207287,358_0,COMPLETED,BOTORCH_MODULAR,70.540000000000006252776074688882,198,0.000862078019716273923934990453,64,3085,0.362731741628273207656008025879,1,128,5
359,1761983080,56,127c23cb-d119-4ecc-b801-d8b643248022,1761983136,1761986316,3180,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 202 --learning_rate 0.00085304905809397986 --batch_size 64 --hidden_size 3405 --dropout 0.38227167324759370182 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c124,1207289,359_0,COMPLETED,BOTORCH_MODULAR,71.489999999999994884092302527279,202,0.000853049058093979860155353645,64,3405,0.382271673247593701816526845505,1,128,5
360,1761988317,14,127c23cb-d119-4ecc-b801-d8b643248022,1761988331,1761991327,2996,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 193 --learning_rate 0.00087035185723519028 --batch_size 64 --hidden_size 3351 --dropout 0.42202163639069856238 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c131,1207337,360_0,COMPLETED,BOTORCH_MODULAR,71.019999999999996020960679743439,227,0.001000000000000000020816681712,64,4096,0.5,1,128,6
361,1761988317,4,127c23cb-d119-4ecc-b801-d8b643248022,1761988321,1761988771,450,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 40 --learning_rate 0.00100000000000000002 --batch_size 787 --hidden_size 2877 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 7,0,,c145,1207336,361_0,COMPLETED,BOTORCH_MODULAR,66.239999999999994884092302527279,193,0.000867925767875791457500733728,64,3243,0.420403097675991710424625580345,1,128,5
362,,,,,,,,,,,,362_0,ABANDONED,BOTORCH_MODULAR,,300,0.000902157123413235471041937696,64,3988,0.5,1,128,7
363,,,,,,,,,,,,363_0,ABANDONED,BOTORCH_MODULAR,,300,0.001000000000000000020816681712,64,4096,0.5,1,128,7
364,,,,,,,,,,,,364_0,ABANDONED,BOTORCH_MODULAR,,300,0.000968714838558851665424598298,64,4096,0.5,1,128,7
365,,,,,,,,,,,,363_0,ABANDONED,BOTORCH_MODULAR,,300,0.001000000000000000020816681712,64,4096,0.5,1,128,7
366,,,,,,,,,,,,363_0,ABANDONED,BOTORCH_MODULAR,,300,0.001000000000000000020816681712,64,4096,0.5,1,128,7
367,,,,,,,,,,,,363_0,ABANDONED,BOTORCH_MODULAR,,300,0.001000000000000000020816681712,64,4096,0.5,1,128,7
368,,,,,,,,,,,,368_0,ABANDONED,BOTORCH_MODULAR,,160,0.00080402430679191172480102523,64,3374,0.395064889352026271662765566361,1,128,5
369,,,,,,,,,,,,369_0,ABANDONED,BOTORCH_MODULAR,,300,0.000973745343888833894685497228,64,4096,0.5,1,128,7
370,,,,,,,,,,,,363_0,ABANDONED,BOTORCH_MODULAR,,300,0.001000000000000000020816681712,64,4096,0.5,1,128,7
371,1761991979,12,127c23cb-d119-4ecc-b801-d8b643248022,1761991991,1761996559,4568,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 300 --learning_rate 0.00099067999178052333 --batch_size 64 --hidden_size 3570 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 7,0,,c143,1207367,371_0,COMPLETED,BOTORCH_MODULAR,69.310000000000002273736754432321,300,0.000990679991780523327635221698,64,3570,0.5,1,128,7
372,,,,,,,,,,,,372_0,ABANDONED,BOTORCH_MODULAR,,261,0.000950362388578720258987264646,64,3440,0.5,1,128,7
373,,,,,,,,,,,,363_0,ABANDONED,BOTORCH_MODULAR,,300,0.001000000000000000020816681712,64,4096,0.5,1,128,7
374,,,,,,,,,,,,363_0,ABANDONED,BOTORCH_MODULAR,,300,0.001000000000000000020816681712,64,4096,0.5,1,128,7
375,1761991979,12,127c23cb-d119-4ecc-b801-d8b643248022,1761991991,1761995701,3710,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 287 --learning_rate 0.00100000000000000002 --batch_size 143 --hidden_size 3715 --dropout 0.45949555377161888092 --num_dense_layers 1 --filter 128 --num_conv_layers 7,0,,c141,1207368,375_0,COMPLETED,BOTORCH_MODULAR,69.480000000000003979039320256561,287,0.001000000000000000020816681712,143,3715,0.45949555377161888092274466544,1,128,7
376,,,,,,,,,,,,363_0,ABANDONED,BOTORCH_MODULAR,,300,0.001000000000000000020816681712,64,4096,0.5,1,128,7
377,,,,,,,,,,,,363_0,ABANDONED,BOTORCH_MODULAR,,300,0.001000000000000000020816681712,64,4096,0.5,1,128,7
378,,,,,,,,,,,,378_0,ABANDONED,BOTORCH_MODULAR,,300,0.001000000000000000020816681712,64,3996,0.5,1,128,7
379,,,,,,,,,,,,363_0,ABANDONED,BOTORCH_MODULAR,,300,0.001000000000000000020816681712,64,4096,0.5,1,128,7
380,1761991979,13,127c23cb-d119-4ecc-b801-d8b643248022,1761991992,1761996473,4481,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 293 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 4096 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 7,0,,c148,1207366,363_0,COMPLETED,BOTORCH_MODULAR,69.260000000000005115907697472721,300,0.001000000000000000020816681712,64,4096,0.5,1,128,7
381,1761996944,103,127c23cb-d119-4ecc-b801-d8b643248022,1761997047,1762001540,4493,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 299 --learning_rate 0.00086478600751846066 --batch_size 64 --hidden_size 4082 --dropout 0.39898912052442503384 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c122,1207469,381_0,COMPLETED,BOTORCH_MODULAR,70.099999999999994315658113919199,299,0.000864786007518460663953674405,64,4082,0.398989120524425033842419452412,1,128,6
382,1761996944,92,127c23cb-d119-4ecc-b801-d8b643248022,1761997036,1762001557,4521,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 300 --learning_rate 0.00089182138211432802 --batch_size 64 --hidden_size 4096 --dropout 0.40926213836522640221 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c123,1207468,382_0,COMPLETED,BOTORCH_MODULAR,70.689999999999997726263245567679,300,0.000891821382114328024652560867,64,4096,0.409262138365226402214602785534,1,128,6
383,1761996944,43,127c23cb-d119-4ecc-b801-d8b643248022,1761996987,1762001824,4837,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 300 --learning_rate 0.00082343616572181451 --batch_size 64 --hidden_size 3801 --dropout 0.5 --num_dense_layers 2 --filter 128 --num_conv_layers 6,0,,c126,1207459,383_0,COMPLETED,BOTORCH_MODULAR,69.439999999999997726263245567679,300,0.000823436165721814507766074254,64,3801,0.5,2,128,6
384,1761996944,23,127c23cb-d119-4ecc-b801-d8b643248022,1761996967,1762001650,4683,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 278 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 3515 --dropout 0.38607905254874824719 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c127,1207456,384_0,COMPLETED,BOTORCH_MODULAR,69.989999999999994884092302527279,278,0.001000000000000000020816681712,64,3515,0.386079052548748247186694015909,1,128,6
385,1761996944,64,127c23cb-d119-4ecc-b801-d8b643248022,1761997008,1762001467,4459,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 294 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 3965 --dropout 0.40023055374981125754 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c124,1207463,385_0,COMPLETED,BOTORCH_MODULAR,70.629999999999995452526491135359,294,0.001000000000000000020816681712,64,3965,0.400230553749811257535640152128,1,128,6
386,1761996944,43,127c23cb-d119-4ecc-b801-d8b643248022,1761996987,1762000259,3272,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 300 --learning_rate 0.00100000000000000002 --batch_size 740 --hidden_size 4074 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 7,0,,c126,1207458,386_0,COMPLETED,BOTORCH_MODULAR,66.819999999999993178789736703038,300,0.001000000000000000020816681712,740,4074,0.5,1,128,7
387,1761996945,63,127c23cb-d119-4ecc-b801-d8b643248022,1761997008,1762001504,4496,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 300 --learning_rate 0.00094403432864867453 --batch_size 64 --hidden_size 4042 --dropout 0.3914257052617763355 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c124,1207461,387_0,COMPLETED,BOTORCH_MODULAR,70.049999999999997157829056959599,300,0.000944034328648674526257567052,64,4042,0.391425705261776335497359013971,1,128,6
388,1761996944,64,127c23cb-d119-4ecc-b801-d8b643248022,1761997008,1762000397,3389,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 300 --learning_rate 0.00100000000000000002 --batch_size 703 --hidden_size 4096 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 7,0,,c124,1207464,388_0,COMPLETED,BOTORCH_MODULAR,66.650000000000005684341886080801,300,0.001000000000000000020816681712,703,4096,0.5,1,128,7
389,,,,,,,,,,,,389_0,RUNNING,BOTORCH_MODULAR,,300,0.00098944892634597126149231805,64,3521,0.384631277813374916618727183959,1,128,6
390,1761996944,92,127c23cb-d119-4ecc-b801-d8b643248022,1761997036,1762001571,4535,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 300 --learning_rate 0.00093588404933310162 --batch_size 64 --hidden_size 4096 --dropout 0.40061943338653827063 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c123,1207465,390_0,COMPLETED,BOTORCH_MODULAR,70.42000000000000170530256582424,300,0.000935884049333101622654418339,64,4096,0.400619433386538270625010227377,1,128,6
391,1761996945,56,127c23cb-d119-4ecc-b801-d8b643248022,1761997001,1762001683,4682,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 291 --learning_rate 0.00089089273402794477 --batch_size 64 --hidden_size 3285 --dropout 0.39606068613125944289 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c125,1207460,391_0,COMPLETED,BOTORCH_MODULAR,70.629999999999995452526491135359,291,0.000890892734027944771003915125,64,3285,0.396060686131259442888108424086,1,128,6
392,1761996944,23,127c23cb-d119-4ecc-b801-d8b643248022,1761996967,1762000604,3637,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 238 --learning_rate 0.00099706706963054842 --batch_size 64 --hidden_size 3980 --dropout 0.40519955937310137006 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c126,1207457,392_0,COMPLETED,BOTORCH_MODULAR,69.980000000000003979039320256561,238,0.000997067069630548424505334104,64,3980,0.40519955937310137006335253318,1,128,6
393,1761996944,28,127c23cb-d119-4ecc-b801-d8b643248022,1761996972,1762000108,3136,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 195 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 3478 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c128,1207455,393_0,COMPLETED,BOTORCH_MODULAR,70.689999999999997726263245567679,195,0.001000000000000000020816681712,64,3478,0.5,1,128,6
394,1761996944,92,127c23cb-d119-4ecc-b801-d8b643248022,1761997036,1761999447,2411,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 153 --learning_rate 0.00088287029125441621 --batch_size 64 --hidden_size 3359 --dropout 0.36329907488942186911 --num_dense_layers 1 --filter 118 --num_conv_layers 5,0,,c123,1207466,394_0,COMPLETED,BOTORCH_MODULAR,70.17000000000000170530256582424,153,0.00088287029125441621006664672,64,3359,0.363299074889421869105632367791,1,118,5
395,1761996945,91,127c23cb-d119-4ecc-b801-d8b643248022,1761997036,1762000335,3299,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 300 --learning_rate 0.00100000000000000002 --batch_size 732 --hidden_size 3059 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 7,0,,c123,1207467,395_0,COMPLETED,BOTORCH_MODULAR,67.10999999999999943156581139192,300,0.001000000000000000020816681712,732,3059,0.5,1,128,7
396,1761996945,63,127c23cb-d119-4ecc-b801-d8b643248022,1761997008,1762000239,3231,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 214 --learning_rate 0.00074120800195245657 --batch_size 64 --hidden_size 3272 --dropout 0.46471641263649920983 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c124,1207462,396_0,COMPLETED,BOTORCH_MODULAR,70.019999999999996020960679743439,214,0.000741208001952456570216032361,64,3272,0.464716412636499209831697498885,1,128,6
397,1761996964,110,127c23cb-d119-4ecc-b801-d8b643248022,1761997074,1762000136,3062,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 200 --learning_rate 0.00085868132461181554 --batch_size 64 --hidden_size 3194 --dropout 0.32285217494762641355 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c120,1207472,397_0,COMPLETED,BOTORCH_MODULAR,71.07999999999999829469743417576,200,0.000858681324611815536759773515,64,3194,0.322852174947626413548107393581,1,128,5
398,1761996964,88,127c23cb-d119-4ecc-b801-d8b643248022,1761997052,1761999866,2814,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 186 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 3683 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c122,1207471,398_0,COMPLETED,BOTORCH_MODULAR,70.46999999999999886313162278384,186,0.001000000000000000020816681712,64,3683,0.5,1,128,6
399,1761996964,110,127c23cb-d119-4ecc-b801-d8b643248022,1761997074,1762000405,3331,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 213 --learning_rate 0.0008716834223854202 --batch_size 64 --hidden_size 3274 --dropout 0.32232394221346843954 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c120,1207473,399_0,COMPLETED,BOTORCH_MODULAR,70.519999999999996020960679743439,213,0.000871683422385420201249084382,64,3274,0.322323942213468439543788690571,1,128,5
400,1761996971,103,127c23cb-d119-4ecc-b801-d8b643248022,1761997074,1761997323,249,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 20 --learning_rate 0.00100000000000000002 --batch_size 875 --hidden_size 4096 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 7,0,,c120,1207474,400_0,COMPLETED,BOTORCH_MODULAR,56.82999999999999829469743417576,20,0.001000000000000000020816681712,875,4096,0.5,1,128,7
401,,,,,,,,,,,,401_0,RUNNING,BOTORCH_MODULAR,,242,0.000863222401743758346870372122,64,4096,0.5,1,128,6
402,,,,,,,,,,,,402_0,RUNNING,BOTORCH_MODULAR,,241,0.000687400688797747908692636898,64,4096,0.309447099297051997357499431018,1,128,5
403,,,,,,,,,,,,403_0,RUNNING,BOTORCH_MODULAR,,300,0.000588430326315258047167877642,64,4096,0.328214991232831432288463702207,2,128,5
404,1762002315,23,127c23cb-d119-4ecc-b801-d8b643248022,1762002338,1762005311,2973,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 191 --learning_rate 0.00093004435296682383 --batch_size 64 --hidden_size 3090 --dropout 0.38278713334192643325 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c141,1207531,404_0,COMPLETED,BOTORCH_MODULAR,71.069999999999993178789736703038,191,0.00093004435296682383405020289,64,3090,0.382787133341926433249824412997,1,128,5
405,,,,,,,,,,,,405_0,RUNNING,BOTORCH_MODULAR,,225,0.000765704468908108494724917836,64,3739,0.319615467370035821748075477444,1,128,5
406,,,,,,,,,,,,406_0,RUNNING,BOTORCH_MODULAR,,300,0.000645130705380732500688056863,64,4096,0.238080203696920705835893272706,1,128,5
407,,,,,,,,,,,,407_0,RUNNING,BOTORCH_MODULAR,,300,0.000685212188702954559833824266,64,3864,0.283500842639620165286373776325,1,128,5
408,1762002315,23,127c23cb-d119-4ecc-b801-d8b643248022,1762002338,1762005298,2960,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 190 --learning_rate 0.00080964268106449556 --batch_size 64 --hidden_size 3179 --dropout 0.34366045653485649547 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c139,1207535,408_0,COMPLETED,BOTORCH_MODULAR,70.209999999999993747223925311118,190,0.000809642681064495555939841687,64,3179,0.343660456534856495469654191766,1,128,5
409,1762002315,25,127c23cb-d119-4ecc-b801-d8b643248022,1762002340,1762005444,3104,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 198 --learning_rate 0.00092763569957155358 --batch_size 64 --hidden_size 3117 --dropout 0.35812296705447438372 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c143,1207530,409_0,COMPLETED,BOTORCH_MODULAR,70.790000000000006252776074688882,198,0.000927635699571553577237603694,64,3117,0.358122967054474383719053776076,1,128,5
410,1762002316,42,127c23cb-d119-4ecc-b801-d8b643248022,1762002358,1762005469,3111,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 198 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 3120 --dropout 0.38615740431970557722 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c130,1207540,410_0,COMPLETED,BOTORCH_MODULAR,70.870000000000004547473508864641,198,0.001000000000000000020816681712,64,3120,0.38615740431970557722252124222,1,128,5
411,,,,,,,,,,,,411_0,RUNNING,BOTORCH_MODULAR,,289,0.000631800014303991763243983915,64,3558,0.306022507292061707317998298095,1,128,5
412,,,,,,,,,,,,412_0,RUNNING,BOTORCH_MODULAR,,300,0.001000000000000000020816681712,227,900,0.5,1,128,7
413,,,,,,,,,,,,413_0,RUNNING,BOTORCH_MODULAR,,300,0.000646337633196558637369011358,64,4096,0.328008144400794510175956020248,1,128,5
414,1762002316,42,127c23cb-d119-4ecc-b801-d8b643248022,1762002358,1762005611,3253,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 209 --learning_rate 0.00098665031920311787 --batch_size 64 --hidden_size 3398 --dropout 0.40595328930528795652 --num_dense_layers 1 --filter 128 --num_conv_layers 5,0,,c130,1207541,414_0,COMPLETED,BOTORCH_MODULAR,70.92000000000000170530256582424,209,0.000986650319203117871086350377,64,3398,0.405953289305287956523216053029,1,128,5
415,1762002316,42,127c23cb-d119-4ecc-b801-d8b643248022,1762002358,1762005485,3127,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 208 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 512 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 7,0,,c131,1207538,415_0,COMPLETED,BOTORCH_MODULAR,69.78000000000000113686837721616,208,0.001000000000000000020816681712,64,512,0.5,1,128,7
416,1762002316,42,127c23cb-d119-4ecc-b801-d8b643248022,1762002358,1762002703,345,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 20 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 512 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 6,0,,c127,1207543,416_0,COMPLETED,BOTORCH_MODULAR,59.409999999999996589394868351519,20,0.001000000000000000020816681712,64,512,0.5,1,128,6
417,1762002318,40,127c23cb-d119-4ecc-b801-d8b643248022,1762002358,1762005288,2930,python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 186 --learning_rate 0.00100000000000000002 --batch_size 64 --hidden_size 512 --dropout 0.5 --num_dense_layers 1 --filter 128 --num_conv_layers 7,0,,c128,1207542,417_0,COMPLETED,BOTORCH_MODULAR,70.129999999999995452526491135359,186,0.001000000000000000020816681712,64,512,0.5,1,128,7
418,,,,,,,,,,,,418_0,RUNNING,BOTORCH_MODULAR,,257,0.001000000000000000020816681712,64,512,0.348996358103006443229787691962,1,128,7
419,,,,,,,,,,,,419_0,RUNNING,BOTORCH_MODULAR,,243,0.000686966559427971946126534331,64,4096,0.324076035591995326168301971848,1,128,5
420,,,,,,,,,,,,420_0,RUNNING,BOTORCH_MODULAR,,258,0.000982659494763007566528467684,69,3904,0.5,1,113,6
⚠ FAILED: sbatch: error: Batch job submission failed: Unexpected message received
handle_failed_job: job is None
⚠ FAILED: sbatch: error: Batch job submission failed: Unexpected message received
handle_failed_job: job is None
⚠ FAILED: sbatch: error: Batch job submission failed: Unexpected message received
handle_failed_job: job is None
⚠ FAILED: sbatch: error: Batch job submission failed: Unexpected message received
handle_failed_job: job is None
⚠ FAILED: sbatch: error: Batch job submission failed: Unexpected message received
handle_failed_job: job is None
⚠ FAILED: sbatch: error: Batch job submission failed: Unexpected message received
handle_failed_job: job is None
get_ax_client_trial: trial_index 367 failed
execute_evaluation: _trial was not in execute_evaluation for params [367, {'epochs': 20, 'lr': 0.001, 'batch_size': 782, 'hidden_size': 2792, 'dropout': 0.5, 'num_dense_layers': 1, 'filter': 128, 'num_conv_layers': 7}, 8, 'systematic']
get_ax_client_trial: trial_index 372 failed
execute_evaluation: _trial was not in execute_evaluation for params [372, {'epochs': 51, 'lr': 0.001, 'batch_size': 785, 'hidden_size': 3175, 'dropout': 0.5, 'num_dense_layers': 1, 'filter': 128, 'num_conv_layers': 7}, 12, 'systematic']
get_ax_client_trial: trial_index 364 failed
execute_evaluation: _trial was not in execute_evaluation for params [364, {'epochs': 225, 'lr': 0.001, 'batch_size': 64, 'hidden_size': 4096, 'dropout': 0.5, 'num_dense_layers': 1, 'filter': 128, 'num_conv_layers': 6}, 5, 'systematic']
get_ax_client_trial: trial_index 363 failed
execute_evaluation: _trial was not in execute_evaluation for params [363, {'epochs': 235, 'lr': 0.001, 'batch_size': 64, 'hidden_size': 4096, 'dropout': 0.5, 'num_dense_layers': 1, 'filter': 128, 'num_conv_layers': 6}, 4, 'systematic']
get_ax_client_trial: trial_index 365 failed
get_ax_client_trial: trial_index 370 failed
get_ax_client_trial: trial_index 376 failed
execute_evaluation: _trial was not in execute_evaluation for params [365, {'epochs': 32, 'lr': 0.001, 'batch_size': 782, 'hidden_size': 3237, 'dropout': 0.5, 'num_dense_layers': 1, 'filter': 128, 'num_conv_layers': 7}, 6, 'systematic']
get_ax_client_trial: trial_index 366 failed
execute_evaluation: _trial was not in execute_evaluation for params [376, {'epochs': 211, 'lr': 0.000977203377755779, 'batch_size': 64, 'hidden_size': 3272, 'dropout': 0.43588084276631545, 'num_dense_layers': 1, 'filter': 128, 'num_conv_layers': 5}, 15, 'systematic']
get_ax_client_trial: trial_index 368 failed
execute_evaluation: _trial was not in execute_evaluation for params [366, {'epochs': 228, 'lr': 0.001, 'batch_size': 64, 'hidden_size': 4096, 'dropout': 0.5, 'num_dense_layers': 1, 'filter': 128, 'num_conv_layers': 6}, 7, 'systematic']
execute_evaluation: _trial was not in execute_evaluation for params [370, {'epochs': 300, 'lr': 0.001, 'batch_size': 64, 'hidden_size': 4096, 'dropout': 0.5, 'num_dense_layers': 1, 'filter': 128, 'num_conv_layers': 7}, 11, 'systematic']
execute_evaluation: _trial was not in execute_evaluation for params [368, {'epochs': 69, 'lr': 0.001, 'batch_size': 781, 'hidden_size': 2944, 'dropout': 0.5, 'num_dense_layers': 1, 'filter': 128, 'num_conv_layers': 7}, 9, 'systematic']
get_ax_client_trial: trial_index 369 failed
get_ax_client_trial: trial_index 374 failed
execute_evaluation: _trial was not in execute_evaluation for params [369, {'epochs': 29, 'lr': 0.001, 'batch_size': 774, 'hidden_size': 2706, '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 [374, {'epochs': 229, 'lr': 0.001, 'batch_size': 64, 'hidden_size': 4096, 'dropout': 0.5, 'num_dense_layers': 1, 'filter': 128, 'num_conv_layers': 6}, 14, 'systematic']
get_ax_client_trial: trial_index 373 failed
get_ax_client_trial: trial_index 377 failed
execute_evaluation: _trial was not in execute_evaluation for params [373, {'epochs': 28, 'lr': 0.001, 'batch_size': 789, 'hidden_size': 2926, 'dropout': 0.5, 'num_dense_layers': 1, 'filter': 128, 'num_conv_layers': 7}, 13, 'systematic']
execute_evaluation: _trial was not in execute_evaluation for params [377, {'epochs': 49, 'lr': 0.001, 'batch_size': 785, 'hidden_size': 3127, 'dropout': 0.5, 'num_dense_layers': 1, 'filter': 128, 'num_conv_layers': 7}, 16, 'systematic']
get_ax_client_trial: trial_index 362 failed
execute_evaluation: _trial was not in execute_evaluation for params [362, {'epochs': 233, 'lr': 0.001, 'batch_size': 64, 'hidden_size': 4096, 'dropout': 0.5, 'num_dense_layers': 1, 'filter': 128, 'num_conv_layers': 6}, 3, 'systematic']
get_ax_client_trial: trial_index 378 failed
execute_evaluation: _trial was not in execute_evaluation for params [378, {'epochs': 20, 'lr': 0.001, 'batch_size': 818, 'hidden_size': 3686, 'dropout': 0.5, 'num_dense_layers': 1, 'filter': 128, 'num_conv_layers': 7}, 17, 'systematic']
get_ax_client_trial: trial_index 379 failed
execute_evaluation: _trial was not in execute_evaluation for params [379, {'epochs': 49, 'lr': 0.001, 'batch_size': 786, 'hidden_size': 2979, 'dropout': 0.5, 'num_dense_layers': 1, 'filter': 128, 'num_conv_layers': 7}, 18, 'systematic']
⚠ FAILED: sbatch: error: Batch job submission failed: Unexpected message received
handle_failed_job: job is None
To cancel, press CTRL c, then run 'scancel 1205100'
⠋ Importing logging...
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⠹ Importing torch...
⠋ Importing numpy...
[WARNING 10-31 15:02:18] 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...
⠋ Importing ax.core.generator_run...
⠋ Importing Cont_X_trans and Y_trans from ax.adapter.registry...
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Run-UUID: cb841cf2-1462-466c-8bc8-71bb2f6e98cf
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⠋ Writing worker creation log...
omniopt --partition=alpha --experiment_name=mnist_mono --mem_gb=40 --time=1440 --worker_timeout=120 --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 20 300 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/2...
⠋ 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
[15:02:35] Setup script completed successfully ✅ 8;id=432447;file:///data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.omniopt.py.omniopt.py8;;:8;id=291468;file:///data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.omniopt.py#10622106228;;
Done executing command
⠋ Saving state files...
Run-folder: /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/runs/mnist_mono/2
⠋ 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=3 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 │ 300 │ 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
SOBOL, best VAL_ACC: 66.61, running 20 = ∑20/20, waiting for 20 jobs : 6%|▒░░░░░░░░░| 60/1000 [4:52:50<11:41:42, 44.79s/it]
To cancel, press CTRL c, then run 'scancel 1205100'
⠋ Importing logging...
⠋ Importing warnings...
⠋ Importing argparse...
⠋ Importing datetime...
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⠋ Importing subprocess...
⠋ Importing tqdm...
⠋ Importing beartype...
⠋ Importing statistics...
⠋ Trying to import pyfiglet...
⠋ Importing helpers...
⠋ Importing pareto...
⠋ Parsing arguments...
⠹ Importing torch...
⠋ Importing numpy...
[WARNING 10-31 15:02:18] 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...
⠋ Importing ax.core.generator_run...
⠋ Importing Cont_X_trans and Y_trans from ax.adapter.registry...
⠋ Importing ax.core.arm...
⠋ Importing ax.core.objective...
⠋ Importing ax.core.Metric...
⠋ Importing ax.exceptions.core...
⠋ Importing ax.exceptions.generation_strategy...
⠋ Importing CORE_DECODER_REGISTRY...
⠋ Trying ax.generation_strategy.generation_node...
⠋ Importing GenerationStep, GenerationStrategy from generation_strategy...
⠋ Importing GenerationNode from generation_node...
⠋ Importing ExternalGenerationNode...
⠋ Importing MaxTrials...
⠋ Importing GeneratorSpec...
⠋ Importing Models from ax.generation_strategy.registry...
⠋ Importing get_pending_observation_features...
⠋ Importing load_experiment...
⠋ Importing save_experiment...
⠋ Importing save_experiment_to_db...
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⠋ Importing Experiment...
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⠋ Importing botorch...
⠋ Importing submitit...
⠋ Importing ax logger...
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Run-UUID: cb841cf2-1462-466c-8bc8-71bb2f6e98cf
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⠋ Writing worker creation log...
omniopt --partition=alpha --experiment_name=mnist_mono --mem_gb=40 --time=1440 --worker_timeout=120 --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 20 300 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/2...
⠋ 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
[15:02:35] Setup script completed successfully ✅ 8;id=432447;file:///data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.omniopt.py.omniopt.py8;;:8;id=291468;file:///data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.omniopt.py#10622106228;;
Done executing command
⠋ Saving state files...
Run-folder: /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/runs/mnist_mono/2
⠋ 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=3 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 │ 300 │ 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
SOBOL, best VAL_ACC: 66.61, running 20 = ∑20/20, waiting for 20 jobs : 6%|▒░░░░░░░░░| 60/1000 [4:52:50<11:41:42, 44.79s/it]
SOBOL, best VAL_ACC: 66.61, running/unknown 13/1 = ∑14/20, started new job : 8%|▒░░░░░░░░░| 80/1000 [5:53:16<8:57:28, 35.05s/it]sbatch: error: Batch job submission failed: Unexpected message received
⚠ FAILED: sbatch: error: Batch job submission failed: Unexpected message received
handle_failed_job: job is None
sbatch: error: Batch job submission failed: Unexpected message received
⚠ FAILED: sbatch: error: Batch job submission failed: Unexpected message received
handle_failed_job: job is None
SOBOL, best VAL_ACC: 71.08, running/unknown 15/1 = ∑16/20, started new job : 14%|█░░░░░░░░░| 138/1000 [8:16:16<9:01:27, 37.69s/it]sbatch: error: Batch job submission failed: Unexpected message received
⚠ FAILED: sbatch: error: Batch job submission failed: Unexpected message received
handle_failed_job: job is None
sbatch: error: Batch job submission failed: Unexpected message received
⚠ FAILED: sbatch: error: Batch job submission failed: Unexpected message received
handle_failed_job: job is None
sbatch: error: Batch job submission failed: Unexpected message received
⚠ FAILED: sbatch: error: Batch job submission failed: Unexpected message received
handle_failed_job: job is None
sbatch: error: Batch job submission failed: Unexpected message received
⚠ FAILED: sbatch: error: Batch job submission failed: Unexpected message received
handle_failed_job: job is None
SOBOL, best VAL_ACC: 71.56, running/unknown 14/1 = ∑15/20, started new job : 36%|███▒░░░░░░| 359/1000 [21:33:27<212:55:11, 1195.81s/it]sbatch: error: Batch job submission failed: Unexpected message received
⚠ FAILED: sbatch: error: Batch job submission failed: Unexpected message received
handle_failed_job: job is None
SOBOL, best VAL_ACC: 71.56, running 13 = ∑13/20, new result: VAL_ACC: 70.920000 : 39%|███▒░░░░░░| 386/1000 [23:56:29<35:12:12, 206.40s/it]
2025-10-31 15:03:43 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, Started OmniOpt2 run...
2025-10-31 15:03:44 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, getting new HP set #1/20
2025-10-31 15:03:44 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, getting new HP set #2/20
2025-10-31 15:03:45 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, getting new HP set #3/20
2025-10-31 15:03:45 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, getting new HP set #4/20
2025-10-31 15:03:45 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, getting new HP set #5/20
2025-10-31 15:03:45 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, getting new HP set #6/20
2025-10-31 15:03:45 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, getting new HP set #7/20
2025-10-31 15:03:45 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, getting new HP set #8/20
2025-10-31 15:03:45 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, getting new HP set #9/20
2025-10-31 15:03:45 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, getting new HP set #10/20
2025-10-31 15:03:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, getting new HP set #11/20
2025-10-31 15:03:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, getting new HP set #12/20
2025-10-31 15:03:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, getting new HP set #13/20
2025-10-31 15:03:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, getting new HP set #14/20
2025-10-31 15:03:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, getting new HP set #15/20
2025-10-31 15:03:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, getting new HP set #16/20
2025-10-31 15:03:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, getting new HP set #17/20
2025-10-31 15:03:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, getting new HP set #18/20
2025-10-31 15:03:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, getting new HP set #19/20
2025-10-31 15:03:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, getting new HP set #20/20
2025-10-31 15:03:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, requested 20 jobs, got 20, 0.13 s/job
2025-10-31 15:03:48 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, eval #1/20 start
2025-10-31 15:03:48 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, eval #2/20 start
2025-10-31 15:03:48 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, eval #3/20 start
2025-10-31 15:03:48 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, eval #4/20 start
2025-10-31 15:03:48 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, eval #5/20 start
2025-10-31 15:03:51 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, eval #6/20 start
2025-10-31 15:03:51 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, eval #7/20 start
2025-10-31 15:03:51 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, eval #8/20 start
2025-10-31 15:03:52 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, eval #9/20 start
2025-10-31 15:03:54 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, eval #10/20 start
2025-10-31 15:03:56 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, eval #11/20 start
2025-10-31 15:04:01 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, eval #12/20 start
2025-10-31 15:04:02 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, eval #13/20 start
2025-10-31 15:04:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, eval #14/20 start
2025-10-31 15:04:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, eval #15/20 start
2025-10-31 15:04:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, eval #16/20 start
2025-10-31 15:04:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, eval #17/20 start
2025-10-31 15:04:05 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, eval #18/20 start
2025-10-31 15:04:05 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, eval #19/20 start
2025-10-31 15:04:05 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, eval #20/20 start
2025-10-31 15:04:06 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, starting new job
2025-10-31 15:04:06 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, unknown 1 = ∑1/20, started new job
2025-10-31 15:04:06 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, unknown 2 = ∑2/20, started new job
2025-10-31 15:04:06 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, unknown 2 = ∑2/20, starting new job
2025-10-31 15:04:06 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, unknown 3 = ∑3/20, started new job
2025-10-31 15:04:06 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, unknown 3 = ∑3/20, starting new job
2025-10-31 15:04:10 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, running/pending 2/1 = ∑3/20, starting new job
2025-10-31 15:04:12 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, running/pending/unknown 2/1/1 = ∑4/20, started new job
2025-10-31 15:04:12 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, running/pending/unknown 2/1/1 = ∑4/20, starting new job
2025-10-31 15:04:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, running/pending/unknown 2/2/1 = ∑5/20, started new job
2025-10-31 15:04:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, running/pending/unknown 2/2/2 = ∑6/20, started new job
2025-10-31 15:04:22 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, running/pending/unknown 2/4/2 = ∑8/20, started new job
2025-10-31 15:04:27 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, running/pending/unknown 2/6/1 = ∑9/20, started new job
2025-10-31 15:04:27 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, running/pending/unknown 2/6/2 = ∑10/20, started new job
2025-10-31 15:04:47 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, running/pending/unknown 2/8/4 = ∑14/20, started new job
2025-10-31 15:04:47 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, running/pending/unknown 2/8/5 = ∑15/20, started new job
2025-10-31 15:04:47 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, running/pending/unknown 2/8/6 = ∑16/20, started new job
2025-10-31 15:04:47 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, running/pending/unknown 2/8/7 = ∑17/20, started new job
2025-10-31 15:04:47 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, running/pending/unknown 2/8/8 = ∑18/20, started new job
2025-10-31 15:04:47 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, running/pending/unknown 2/8/9 = ∑19/20, started new job
2025-10-31 15:04:47 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, running/pending/unknown 2/8/10 = ∑20/20, started new job
2025-10-31 15:04:48 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, running/pending/unknown 2/8/10 = ∑20/20, waiting for 20 jobs
2025-10-31 15:04:53 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, running/pending 2/18 = ∑20/20, waiting for 20 jobs
2025-10-31 15:05:12 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, running/pending 3/17 = ∑20/20, waiting for 20 jobs
2025-10-31 15:18:57 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, running/pending 5/15 = ∑20/20, waiting for 20 jobs
2025-10-31 15:21:29 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, running/pending 5/15 = ∑20/20, new result: VAL_ACC: 58.550000
2025-10-31 15:21:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 58.55, running/pending 4/15 = ∑19/20, waiting for 20 jobs, finished 1 job
2025-10-31 15:21:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 58.55, running/pending 4/15 = ∑19/20, waiting for 19 jobs
2025-10-31 15:28:59 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 58.55, running 19 = ∑19/20, waiting for 19 jobs
2025-10-31 15:29:15 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 58.55, running 19 = ∑19/20, new result: VAL_ACC: 58.400000
2025-10-31 15:29:18 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 58.55, running 18 = ∑18/20, waiting for 19 jobs, finished 1 job
2025-10-31 15:29:18 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 58.55, running 18 = ∑18/20, waiting for 18 jobs
2025-10-31 15:30:44 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 58.55, running 18 = ∑18/20, new result: VAL_ACC: 47.910000
2025-10-31 15:30:50 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 58.55, running 17 = ∑17/20, waiting for 18 jobs, finished 1 job
2025-10-31 15:30:50 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 58.55, running 17 = ∑17/20, waiting for 17 jobs
2025-10-31 15:31:43 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 58.55, running 17 = ∑17/20, new result: VAL_ACC: 62.930000
2025-10-31 15:31:47 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 62.93, running 16 = ∑16/20, waiting for 17 jobs, finished 1 job
2025-10-31 15:31:47 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 62.93, running 16 = ∑16/20, waiting for 16 jobs
2025-10-31 15:35:56 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 62.93, running 16 = ∑16/20, new result: VAL_ACC: 57.570000
2025-10-31 15:36:00 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 62.93, running 15 = ∑15/20, waiting for 16 jobs, finished 1 job
2025-10-31 15:36:00 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 62.93, running 15 = ∑15/20, waiting for 15 jobs
2025-10-31 15:38:12 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 62.93, running 15 = ∑15/20, new result: VAL_ACC: 57.840000
2025-10-31 15:38:15 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 62.93, running 14 = ∑14/20, waiting for 15 jobs, finished 1 job
2025-10-31 15:38:15 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 62.93, running 14 = ∑14/20, waiting for 14 jobs
2025-10-31 15:38:16 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 62.93, running 14 = ∑14/20, new result: VAL_ACC: 60.350000
2025-10-31 15:38:19 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 62.93, running 13 = ∑13/20, waiting for 14 jobs, finished 1 job
2025-10-31 15:38:19 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 62.93, running 13 = ∑13/20, waiting for 13 jobs
2025-10-31 15:39:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 62.93, running 13 = ∑13/20, new result: VAL_ACC: 61.670000
2025-10-31 15:39:58 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 62.93, running 12 = ∑12/20, waiting for 13 jobs, finished 1 job
2025-10-31 15:39:58 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 62.93, running 12 = ∑12/20, waiting for 12 jobs
2025-10-31 15:47:01 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 62.93, running 12 = ∑12/20, new result: VAL_ACC: 53.720000
2025-10-31 15:47:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 62.93, running 11 = ∑11/20, waiting for 12 jobs, finished 1 job
2025-10-31 15:47:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 62.93, running 11 = ∑11/20, waiting for 11 jobs
2025-10-31 15:52:32 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 62.93, running 11 = ∑11/20, new result: VAL_ACC: 60.860000
2025-10-31 15:52:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 62.93, running 10 = ∑10/20, waiting for 11 jobs, finished 1 job
2025-10-31 15:52:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 62.93, running 10 = ∑10/20, waiting for 10 jobs
2025-10-31 15:54:01 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 62.93, running 10 = ∑10/20, new result: VAL_ACC: 64.050000
2025-10-31 15:54:07 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 64.05, running 9 = ∑9/20, waiting for 10 jobs, finished 1 job
2025-10-31 15:54:07 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 64.05, running 9 = ∑9/20, waiting for 9 jobs
2025-10-31 15:55:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 64.05, running 9 = ∑9/20, new result: VAL_ACC: 50.830000
2025-10-31 15:55:34 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 64.05, running 8 = ∑8/20, waiting for 9 jobs, finished 1 job
2025-10-31 15:55:34 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 64.05, running 8 = ∑8/20, waiting for 8 jobs
2025-10-31 15:56:34 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 64.05, running 8 = ∑8/20, new result: VAL_ACC: 53.230000
2025-10-31 15:56:37 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 64.05, running 7 = ∑7/20, waiting for 8 jobs, finished 1 job
2025-10-31 15:56:37 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 64.05, running 7 = ∑7/20, waiting for 7 jobs
2025-10-31 15:57:32 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 64.05, running 7 = ∑7/20, new result: VAL_ACC: 62.930000
2025-10-31 15:57:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 64.05, running 6 = ∑6/20, waiting for 7 jobs, finished 1 job
2025-10-31 15:57:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 64.05, running 6 = ∑6/20, waiting for 6 jobs
2025-10-31 15:59:29 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 64.05, running 6 = ∑6/20, new result: VAL_ACC: 63.350000
2025-10-31 15:59:32 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 64.05, running 5 = ∑5/20, waiting for 6 jobs, finished 1 job
2025-10-31 15:59:32 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 64.05, running 5 = ∑5/20, waiting for 5 jobs
2025-10-31 16:08:06 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 64.05, running 5 = ∑5/20, new result: VAL_ACC: 48.080000
2025-10-31 16:08:09 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 64.05, running 4 = ∑4/20, waiting for 5 jobs, finished 1 job
2025-10-31 16:08:09 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 64.05, running 4 = ∑4/20, waiting for 4 jobs
2025-10-31 16:08:32 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 64.05, running 4 = ∑4/20, new result: VAL_ACC: 61.060000
2025-10-31 16:08:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 64.05, running 3 = ∑3/20, waiting for 4 jobs, finished 1 job
2025-10-31 16:08:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 64.05, running 3 = ∑3/20, waiting for 3 jobs
2025-10-31 16:15:14 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 64.05, running 3 = ∑3/20, new result: VAL_ACC: 53.120000
2025-10-31 16:15:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 64.05, running 2 = ∑2/20, waiting for 3 jobs, finished 1 job
2025-10-31 16:15:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 64.05, running 2 = ∑2/20, waiting for 2 jobs
2025-10-31 16:16:21 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 64.05, running 2 = ∑2/20, new result: VAL_ACC: 43.570000
2025-10-31 16:16:26 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 64.05, running 1 = ∑1/20, waiting for 2 jobs, finished 1 job
2025-10-31 16:16:26 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 64.05, running 1 = ∑1/20, waiting for 1 job
2025-10-31 16:18:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 64.05, running 1 = ∑1/20, new result: VAL_ACC: 65.890000
2025-10-31 16:18:40 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, waiting for 1 job, finished 1 job
2025-10-31 16:19:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, getting new HP set #1/20
2025-10-31 16:19:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, getting new HP set #2/20
2025-10-31 16:19:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, getting new HP set #3/20
2025-10-31 16:19:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, getting new HP set #4/20
2025-10-31 16:19:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, getting new HP set #5/20
2025-10-31 16:19:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, getting new HP set #6/20
2025-10-31 16:19:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, getting new HP set #7/20
2025-10-31 16:19:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, getting new HP set #8/20
2025-10-31 16:19:40 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, getting new HP set #9/20
2025-10-31 16:19:40 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, getting new HP set #10/20
2025-10-31 16:19:40 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, getting new HP set #11/20
2025-10-31 16:19:40 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, getting new HP set #12/20
2025-10-31 16:19:40 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, getting new HP set #13/20
2025-10-31 16:19:40 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, getting new HP set #14/20
2025-10-31 16:19:40 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, getting new HP set #15/20
2025-10-31 16:19:43 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, getting new HP set #16/20
2025-10-31 16:19:43 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, getting new HP set #17/20
2025-10-31 16:19:43 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, getting new HP set #18/20
2025-10-31 16:19:43 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, getting new HP set #19/20
2025-10-31 16:19:43 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, getting new HP set #20/20
2025-10-31 16:19:43 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, requested 20 jobs, got 20, 3.12 s/job
2025-10-31 16:19:45 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, eval #1/20 start
2025-10-31 16:19:45 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, eval #2/20 start
2025-10-31 16:19:45 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, eval #3/20 start
2025-10-31 16:19:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, eval #4/20 start
2025-10-31 16:19:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, eval #5/20 start
2025-10-31 16:19:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, eval #6/20 start
2025-10-31 16:19:47 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, eval #7/20 start
2025-10-31 16:19:47 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, eval #8/20 start
2025-10-31 16:19:48 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, eval #9/20 start
2025-10-31 16:19:48 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, eval #10/20 start
2025-10-31 16:19:53 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, eval #11/20 start
2025-10-31 16:19:53 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, eval #12/20 start
2025-10-31 16:19:54 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, eval #13/20 start
2025-10-31 16:19:54 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, eval #14/20 start
2025-10-31 16:19:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, eval #15/20 start
2025-10-31 16:19:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, eval #16/20 start
2025-10-31 16:19:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, eval #17/20 start
2025-10-31 16:19:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, eval #18/20 start
2025-10-31 16:19:56 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, eval #19/20 start
2025-10-31 16:19:56 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, eval #20/20 start
2025-10-31 16:19:57 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, starting new job
2025-10-31 16:19:59 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, unknown 3 = ∑3/20, started new job
2025-10-31 16:19:59 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, unknown 3 = ∑3/20, starting new job
2025-10-31 16:20:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, pending 4 = ∑4/20, started new job
2025-10-31 16:20:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, pending 4 = ∑4/20, starting new job
2025-10-31 16:20:09 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, pending 7 = ∑7/20, started new job
2025-10-31 16:20:14 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, pending 10 = ∑10/20, started new job
2025-10-31 16:20:19 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, pending/unknown 10/3 = ∑13/20, started new job
2025-10-31 16:20:24 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, pending/unknown 13/3 = ∑16/20, started new job
2025-10-31 16:20:29 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, pending/unknown 16/3 = ∑19/20, started new job
2025-10-31 16:20:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, pending 20 = ∑20/20, started new job
2025-10-31 16:20:36 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, pending 20 = ∑20/20, waiting for 20 jobs
2025-10-31 16:21:11 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, running/pending 1/19 = ∑20/20, waiting for 20 jobs
2025-10-31 16:23:05 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, running/pending 2/18 = ∑20/20, waiting for 20 jobs
2025-10-31 16:25:38 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, running/pending 3/17 = ∑20/20, waiting for 20 jobs
2025-10-31 16:30:43 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, running/pending 8/12 = ∑20/20, waiting for 20 jobs
2025-10-31 16:40:43 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, running/pending 13/7 = ∑20/20, waiting for 20 jobs
2025-10-31 17:15:19 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 65.89, running/pending 13/7 = ∑20/20, new result: VAL_ACC: 66.500000
2025-10-31 17:15:23 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.5, running/pending 12/7 = ∑19/20, waiting for 20 jobs, finished 1 job
2025-10-31 17:15:23 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.5, running/pending 12/7 = ∑19/20, waiting for 19 jobs
2025-10-31 17:16:29 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.5, running/pending 12/7 = ∑19/20, new result: VAL_ACC: 66.140000
2025-10-31 17:16:33 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.5, running/pending 11/7 = ∑18/20, waiting for 19 jobs, finished 1 job
2025-10-31 17:16:33 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.5, running/pending 11/7 = ∑18/20, waiting for 18 jobs
2025-10-31 17:19:03 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.5, running/pending 11/7 = ∑18/20, new result: VAL_ACC: 66.050000
2025-10-31 17:19:14 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.5, running/pending 10/7 = ∑17/20, waiting for 18 jobs, finished 1 job
2025-10-31 17:19:14 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.5, running/pending 10/7 = ∑17/20, waiting for 17 jobs
2025-10-31 17:20:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.5, running/pending 10/7 = ∑17/20, new result: VAL_ACC: 66.180000
2025-10-31 17:20:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.5, running/pending 9/7 = ∑16/20, waiting for 17 jobs, finished 1 job
2025-10-31 17:20:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.5, running/pending 9/7 = ∑16/20, waiting for 16 jobs
2025-10-31 17:22:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.5, running/pending 9/7 = ∑16/20, new result: VAL_ACC: 65.650000
2025-10-31 17:22:32 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.5, running/pending 8/7 = ∑15/20, waiting for 16 jobs, finished 1 job
2025-10-31 17:22:32 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.5, running/pending 8/7 = ∑15/20, waiting for 15 jobs
2025-10-31 17:22:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.5, running/pending 8/7 = ∑15/20, new result: VAL_ACC: 65.720000
2025-10-31 17:22:38 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.5, running/pending 7/7 = ∑14/20, waiting for 15 jobs, finished 1 job
2025-10-31 17:22:38 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.5, running/pending 7/7 = ∑14/20, waiting for 14 jobs
2025-10-31 17:23:25 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.5, running/pending 7/7 = ∑14/20, new result: VAL_ACC: 66.070000
2025-10-31 17:23:29 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.5, running/pending 6/7 = ∑13/20, waiting for 14 jobs, finished 1 job
2025-10-31 17:23:29 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.5, running/pending 6/7 = ∑13/20, waiting for 13 jobs
2025-10-31 17:24:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.5, running/pending 6/7 = ∑13/20, new result: VAL_ACC: 66.530000
2025-10-31 17:24:43 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.53, running/pending 5/7 = ∑12/20, waiting for 13 jobs, finished 1 job
2025-10-31 17:24:43 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.53, running/pending 5/7 = ∑12/20, waiting for 12 jobs
2025-10-31 17:27:23 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.53, running/pending 5/7 = ∑12/20, new result: VAL_ACC: 66.610000
2025-10-31 17:27:27 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running/pending 4/7 = ∑11/20, waiting for 12 jobs, finished 1 job
2025-10-31 17:27:27 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running/pending 4/7 = ∑11/20, waiting for 11 jobs
2025-10-31 17:29:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running/pending 4/7 = ∑11/20, new result: VAL_ACC: 66.290000
2025-10-31 17:29:43 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running/pending 3/7 = ∑10/20, waiting for 11 jobs, finished 1 job
2025-10-31 17:29:43 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running/pending 3/7 = ∑10/20, waiting for 10 jobs
2025-10-31 17:30:08 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running/pending 3/7 = ∑10/20, new result: VAL_ACC: 66.470000
2025-10-31 17:30:13 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running/pending 2/7 = ∑9/20, waiting for 10 jobs, finished 1 job
2025-10-31 17:30:13 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running/pending 2/7 = ∑9/20, waiting for 9 jobs
2025-10-31 17:30:45 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 9 = ∑9/20, waiting for 9 jobs
2025-10-31 17:31:29 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 9 = ∑9/20, new result: VAL_ACC: 65.940000
2025-10-31 17:31:33 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 8 = ∑8/20, waiting for 9 jobs, finished 1 job
2025-10-31 17:31:33 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 8 = ∑8/20, waiting for 8 jobs
2025-10-31 17:34:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 8 = ∑8/20, new result: VAL_ACC: 65.190000
2025-10-31 17:34:08 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 7 = ∑7/20, waiting for 8 jobs, finished 1 job
2025-10-31 17:34:08 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 7 = ∑7/20, waiting for 7 jobs
2025-10-31 18:19:54 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 7 = ∑7/20, new result: VAL_ACC: 66.190000
2025-10-31 18:19:59 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 6 = ∑6/20, waiting for 7 jobs, finished 1 job
2025-10-31 18:19:59 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 6 = ∑6/20, waiting for 6 jobs
2025-10-31 18:20:34 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 6 = ∑6/20, new result: VAL_ACC: 65.960000
2025-10-31 18:20:38 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 5 = ∑5/20, waiting for 6 jobs, finished 1 job
2025-10-31 18:20:38 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 5 = ∑5/20, waiting for 5 jobs
2025-10-31 18:21:00 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 5 = ∑5/20, new result: VAL_ACC: 66.140000
2025-10-31 18:21:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 4 = ∑4/20, waiting for 5 jobs, finished 1 job
2025-10-31 18:21:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 4 = ∑4/20, waiting for 4 jobs
2025-10-31 18:21:37 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 4 = ∑4/20, new result: VAL_ACC: 66.070000
2025-10-31 18:21:41 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 3 = ∑3/20, waiting for 4 jobs, finished 1 job
2025-10-31 18:21:42 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 3 = ∑3/20, waiting for 3 jobs
2025-10-31 18:22:00 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 3 = ∑3/20, new result: VAL_ACC: 66.190000
2025-10-31 18:22:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 2 = ∑2/20, waiting for 3 jobs, finished 1 job
2025-10-31 18:22:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 2 = ∑2/20, waiting for 2 jobs
2025-10-31 18:23:15 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 2 = ∑2/20, new result: VAL_ACC: 64.770000
2025-10-31 18:23:20 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 1 = ∑1/20, waiting for 2 jobs, finished 1 job
2025-10-31 18:23:20 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 1 = ∑1/20, waiting for 1 job
2025-10-31 18:24:19 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 1 = ∑1/20, new result: VAL_ACC: 66.080000
2025-10-31 18:24:24 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, waiting for 1 job, finished 1 job
2025-10-31 18:26:50 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #1/20
2025-10-31 18:26:50 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #2/20
2025-10-31 18:26:50 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #3/20
2025-10-31 18:26:51 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #4/20
2025-10-31 18:26:51 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #5/20
2025-10-31 18:26:51 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #6/20
2025-10-31 18:26:51 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #7/20
2025-10-31 18:26:51 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #8/20
2025-10-31 18:26:52 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #9/20
2025-10-31 18:26:52 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #10/20
2025-10-31 18:26:52 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #11/20
2025-10-31 18:26:52 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #12/20
2025-10-31 18:26:52 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #13/20
2025-10-31 18:26:53 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #14/20
2025-10-31 18:26:53 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #15/20
2025-10-31 18:26:53 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #16/20
2025-10-31 18:26:53 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #17/20
2025-10-31 18:26:53 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #18/20
2025-10-31 18:26:54 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #19/20
2025-10-31 18:26:54 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #20/20
2025-10-31 18:26:54 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, requested 20 jobs, got 20, 7.48 s/job
2025-10-31 18:26:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #1/20 start
2025-10-31 18:26:56 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #2/20 start
2025-10-31 18:26:57 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #3/20 start
2025-10-31 18:26:58 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #4/20 start
2025-10-31 18:26:58 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #5/20 start
2025-10-31 18:26:59 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #6/20 start
2025-10-31 18:27:00 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #7/20 start
2025-10-31 18:27:02 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #8/20 start
2025-10-31 18:27:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #9/20 start
2025-10-31 18:27:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #10/20 start
2025-10-31 18:27:05 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #11/20 start
2025-10-31 18:27:05 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #12/20 start
2025-10-31 18:27:06 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #13/20 start
2025-10-31 18:27:07 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #14/20 start
2025-10-31 18:27:07 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #15/20 start
2025-10-31 18:27:08 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #16/20 start
2025-10-31 18:27:09 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #17/20 start
2025-10-31 18:27:09 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #18/20 start
2025-10-31 18:27:11 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #19/20 start
2025-10-31 18:27:11 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #20/20 start
2025-10-31 18:27:14 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, starting new job
2025-10-31 18:27:16 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, unknown 2 = ∑2/20, started new job
2025-10-31 18:27:16 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, unknown 2 = ∑2/20, starting new job
2025-10-31 18:27:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, pending 3 = ∑3/20, started new job
2025-10-31 18:27:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, pending 3 = ∑3/20, starting new job
2025-10-31 18:27:21 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, pending/unknown 3/1 = ∑4/20, started new job
2025-10-31 18:27:21 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, pending/unknown 3/1 = ∑4/20, starting new job
2025-10-31 18:27:26 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, pending/unknown 4/3 = ∑7/20, started new job
2025-10-31 18:27:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, pending/unknown 7/3 = ∑10/20, started new job
2025-10-31 18:27:36 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, pending/unknown 10/2 = ∑12/20, started new job
2025-10-31 18:27:41 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, pending/unknown 12/2 = ∑14/20, started new job
2025-10-31 18:27:42 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, pending 15 = ∑15/20, started new job
2025-10-31 18:27:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, pending/unknown 15/2 = ∑17/20, started new job
2025-10-31 18:27:52 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, pending/unknown 17/3 = ∑20/20, started new job
2025-10-31 18:27:53 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, pending/unknown 17/3 = ∑20/20, waiting for 20 jobs
2025-10-31 18:27:53 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, pending 20 = ∑20/20, waiting for 20 jobs
2025-10-31 18:35:32 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running/pending 4/16 = ∑20/20, waiting for 20 jobs
2025-10-31 18:43:13 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running/pending 16/4 = ∑20/20, waiting for 20 jobs
2025-10-31 18:53:13 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 20 = ∑20/20, waiting for 20 jobs
2025-10-31 19:17:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 20 = ∑20/20, new result: VAL_ACC: 64.420000
2025-10-31 19:17:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 20 = ∑20/20, new result: VAL_ACC: 64.330000
2025-10-31 19:17:52 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 18 = ∑18/20, waiting for 20 jobs, finished 2 jobs
2025-10-31 19:17:52 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 18 = ∑18/20, waiting for 18 jobs
2025-10-31 19:18:58 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 18 = ∑18/20, new result: VAL_ACC: 64.630000
2025-10-31 19:19:16 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 17 = ∑17/20, waiting for 18 jobs, finished 1 job
2025-10-31 19:19:16 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 17 = ∑17/20, waiting for 17 jobs
2025-10-31 19:19:18 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 17 = ∑17/20, new result: VAL_ACC: 64.380000
2025-10-31 19:19:23 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 16 = ∑16/20, waiting for 17 jobs, finished 1 job
2025-10-31 19:19:23 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 16 = ∑16/20, waiting for 16 jobs
2025-10-31 19:20:16 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 16 = ∑16/20, new result: VAL_ACC: 64.100000
2025-10-31 19:20:21 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 15 = ∑15/20, waiting for 16 jobs, finished 1 job
2025-10-31 19:20:21 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 15 = ∑15/20, waiting for 15 jobs
2025-10-31 19:21:56 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 15 = ∑15/20, new result: VAL_ACC: 63.940000
2025-10-31 19:22:03 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 14 = ∑14/20, waiting for 15 jobs, finished 1 job
2025-10-31 19:22:03 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 14 = ∑14/20, waiting for 14 jobs
2025-10-31 19:22:19 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 14 = ∑14/20, new result: VAL_ACC: 64.780000
2025-10-31 19:22:34 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 13 = ∑13/20, waiting for 14 jobs, finished 1 job
2025-10-31 19:22:34 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 13 = ∑13/20, waiting for 13 jobs
2025-10-31 19:22:34 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 13 = ∑13/20, new result: VAL_ACC: 64.260000
2025-10-31 19:22:41 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 12 = ∑12/20, waiting for 13 jobs, finished 1 job
2025-10-31 19:22:41 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 12 = ∑12/20, waiting for 12 jobs
2025-10-31 19:23:58 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 12 = ∑12/20, new result: VAL_ACC: 64.300000
2025-10-31 19:24:03 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 11 = ∑11/20, waiting for 12 jobs, finished 1 job
2025-10-31 19:24:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 11 = ∑11/20, waiting for 11 jobs
2025-10-31 19:24:06 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 11 = ∑11/20, new result: VAL_ACC: 63.890000
2025-10-31 19:24:11 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 10 = ∑10/20, waiting for 11 jobs, finished 1 job
2025-10-31 19:24:11 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 10 = ∑10/20, waiting for 10 jobs
2025-10-31 19:24:33 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 10 = ∑10/20, new result: VAL_ACC: 64.280000
2025-10-31 19:24:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 9 = ∑9/20, waiting for 10 jobs, finished 1 job
2025-10-31 19:24:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 9 = ∑9/20, waiting for 9 jobs
2025-10-31 19:26:05 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 9 = ∑9/20, new result: VAL_ACC: 64.280000
2025-10-31 19:26:10 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 8 = ∑8/20, waiting for 9 jobs, finished 1 job
2025-10-31 19:26:10 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 8 = ∑8/20, waiting for 8 jobs
2025-10-31 19:27:12 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 8 = ∑8/20, new result: VAL_ACC: 64.420000
2025-10-31 19:27:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 7 = ∑7/20, waiting for 8 jobs, finished 1 job
2025-10-31 19:27:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 7 = ∑7/20, waiting for 7 jobs
2025-10-31 19:27:26 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 7 = ∑7/20, new result: VAL_ACC: 64.180000
2025-10-31 19:27:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 6 = ∑6/20, waiting for 7 jobs, finished 1 job
2025-10-31 19:27:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 6 = ∑6/20, waiting for 6 jobs
2025-10-31 19:27:53 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 6 = ∑6/20, new result: VAL_ACC: 64.750000
2025-10-31 19:27:58 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 5 = ∑5/20, waiting for 6 jobs, finished 1 job
2025-10-31 19:27:58 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 5 = ∑5/20, waiting for 5 jobs
2025-10-31 19:28:00 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 5 = ∑5/20, new result: VAL_ACC: 64.550000
2025-10-31 19:28:05 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 4 = ∑4/20, waiting for 5 jobs, finished 1 job
2025-10-31 19:28:06 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 4 = ∑4/20, waiting for 4 jobs
2025-10-31 19:30:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 4 = ∑4/20, new result: VAL_ACC: 65.100000
2025-10-31 19:30:51 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 3 = ∑3/20, waiting for 4 jobs, finished 1 job
2025-10-31 19:30:52 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 3 = ∑3/20, waiting for 3 jobs
2025-10-31 19:30:52 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 3 = ∑3/20, new result: VAL_ACC: 63.740000
2025-10-31 19:30:57 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 2 = ∑2/20, waiting for 3 jobs, finished 1 job
2025-10-31 19:30:57 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 2 = ∑2/20, waiting for 2 jobs
2025-10-31 19:31:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 2 = ∑2/20, new result: VAL_ACC: 64.280000
2025-10-31 19:31:09 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 1 = ∑1/20, waiting for 2 jobs, finished 1 job
2025-10-31 19:31:09 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 1 = ∑1/20, waiting for 1 job
2025-10-31 19:31:23 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 1 = ∑1/20, new result: VAL_ACC: 64.000000
2025-10-31 19:31:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, waiting for 1 job, finished 1 job
2025-10-31 19:32:30 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #1/20
2025-10-31 19:32:30 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #2/20
2025-10-31 19:32:30 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #3/20
2025-10-31 19:32:30 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #4/20
2025-10-31 19:32:30 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #5/20
2025-10-31 19:32:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #6/20
2025-10-31 19:32:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #7/20
2025-10-31 19:32:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #8/20
2025-10-31 19:32:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #9/20
2025-10-31 19:32:32 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #10/20
2025-10-31 19:32:32 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #11/20
2025-10-31 19:32:32 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #12/20
2025-10-31 19:32:32 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #13/20
2025-10-31 19:32:32 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #14/20
2025-10-31 19:32:33 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #15/20
2025-10-31 19:32:33 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #16/20
2025-10-31 19:32:33 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #17/20
2025-10-31 19:32:33 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #18/20
2025-10-31 19:32:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #19/20
2025-10-31 19:32:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #20/20
2025-10-31 19:32:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, requested 20 jobs, got 20, 3.29 s/job
2025-10-31 19:32:37 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #1/20 start
2025-10-31 19:32:37 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #2/20 start
2025-10-31 19:32:38 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #3/20 start
2025-10-31 19:32:40 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #4/20 start
2025-10-31 19:32:41 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #5/20 start
2025-10-31 19:32:41 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #6/20 start
2025-10-31 19:32:42 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #7/20 start
2025-10-31 19:32:42 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #8/20 start
2025-10-31 19:32:43 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #9/20 start
2025-10-31 19:32:44 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #10/20 start
2025-10-31 19:32:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #11/20 start
2025-10-31 19:32:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #12/20 start
2025-10-31 19:32:47 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #13/20 start
2025-10-31 19:32:48 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #14/20 start
2025-10-31 19:32:49 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #15/20 start
2025-10-31 19:32:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #16/20 start
2025-10-31 19:32:57 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #17/20 start
2025-10-31 19:32:57 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #18/20 start
2025-10-31 19:32:58 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #19/20 start
2025-10-31 19:33:01 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #20/20 start
2025-10-31 19:33:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, starting new job
2025-10-31 19:33:06 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, unknown 1 = ∑1/20, starting new job
2025-10-31 19:33:06 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, unknown 2 = ∑2/20, starting new job
2025-10-31 19:33:06 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, unknown 2 = ∑2/20, started new job
2025-10-31 19:33:06 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, unknown 2 = ∑2/20, starting new job
2025-10-31 19:33:06 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, unknown 2 = ∑2/20, started new job
2025-10-31 19:33:07 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, unknown 2 = ∑2/20, starting new job
2025-10-31 19:33:07 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, unknown 3 = ∑3/20, started new job
2025-10-31 19:33:07 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, unknown 3 = ∑3/20, starting new job
2025-10-31 19:33:11 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, pending/unknown 3/1 = ∑4/20, started new job
2025-10-31 19:33:11 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, pending/unknown 3/1 = ∑4/20, starting new job
2025-10-31 19:33:16 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, pending/unknown 4/2 = ∑6/20, started new job
2025-10-31 19:33:21 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, pending/unknown 6/3 = ∑9/20, started new job
2025-10-31 19:33:26 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, pending/unknown 9/3 = ∑12/20, started new job
2025-10-31 19:33:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, pending/unknown 12/3 = ∑15/20, started new job
2025-10-31 19:33:37 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, pending/unknown 15/3 = ∑18/20, started new job
2025-10-31 19:33:41 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, pending/unknown 18/1 = ∑19/20, started new job
2025-10-31 19:33:42 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, pending/unknown 18/2 = ∑20/20, started new job
2025-10-31 19:33:43 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, pending/unknown 18/2 = ∑20/20, waiting for 20 jobs
2025-10-31 19:33:47 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, pending 20 = ∑20/20, waiting for 20 jobs
2025-10-31 19:56:34 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 20 = ∑20/20, waiting for 20 jobs
2025-10-31 20:41:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 20 = ∑20/20, new result: VAL_ACC: 63.390000
2025-10-31 20:41:45 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 19 = ∑19/20, waiting for 20 jobs, finished 1 job
2025-10-31 20:41:45 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 19 = ∑19/20, waiting for 19 jobs
2025-10-31 20:41:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 19 = ∑19/20, new result: VAL_ACC: 60.570000
2025-10-31 20:41:52 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 18 = ∑18/20, waiting for 19 jobs, finished 1 job
2025-10-31 20:41:52 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 18 = ∑18/20, waiting for 18 jobs
2025-10-31 20:42:49 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 18 = ∑18/20, new result: VAL_ACC: 61.100000
2025-10-31 20:42:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 17 = ∑17/20, waiting for 18 jobs, finished 1 job
2025-10-31 20:42:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 17 = ∑17/20, waiting for 17 jobs
2025-10-31 20:43:11 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 17 = ∑17/20, new result: VAL_ACC: 60.760000
2025-10-31 20:43:18 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 16 = ∑16/20, waiting for 17 jobs, finished 1 job
2025-10-31 20:43:18 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 16 = ∑16/20, waiting for 16 jobs
2025-10-31 20:43:22 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 16 = ∑16/20, new result: VAL_ACC: 59.980000
2025-10-31 20:43:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 15 = ∑15/20, waiting for 16 jobs, finished 1 job
2025-10-31 20:43:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 15 = ∑15/20, waiting for 15 jobs
2025-10-31 20:45:25 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 15 = ∑15/20, new result: VAL_ACC: 61.980000
2025-10-31 20:45:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 14 = ∑14/20, waiting for 15 jobs, finished 1 job
2025-10-31 20:45:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 14 = ∑14/20, waiting for 14 jobs
2025-10-31 20:46:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 14 = ∑14/20, new result: VAL_ACC: 61.460000
2025-10-31 20:46:34 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 13 = ∑13/20, waiting for 14 jobs, finished 1 job
2025-10-31 20:46:34 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 13 = ∑13/20, waiting for 13 jobs
2025-10-31 20:46:58 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 13 = ∑13/20, new result: VAL_ACC: 62.140000
2025-10-31 20:47:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 12 = ∑12/20, waiting for 13 jobs, finished 1 job
2025-10-31 20:47:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 12 = ∑12/20, waiting for 12 jobs
2025-10-31 20:48:14 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 12 = ∑12/20, new result: VAL_ACC: 63.100000
2025-10-31 20:48:20 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 11 = ∑11/20, waiting for 12 jobs, finished 1 job
2025-10-31 20:48:20 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 11 = ∑11/20, waiting for 11 jobs
2025-10-31 20:48:21 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 11 = ∑11/20, new result: VAL_ACC: 61.720000
2025-10-31 20:48:27 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 10 = ∑10/20, waiting for 11 jobs, finished 1 job
2025-10-31 20:48:27 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 10 = ∑10/20, waiting for 10 jobs
2025-10-31 20:48:40 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 10 = ∑10/20, new result: VAL_ACC: 62.530000
2025-10-31 20:48:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 9 = ∑9/20, waiting for 10 jobs, finished 1 job
2025-10-31 20:48:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 9 = ∑9/20, waiting for 9 jobs
2025-10-31 20:50:00 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 9 = ∑9/20, new result: VAL_ACC: 60.800000
2025-10-31 20:50:07 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 8 = ∑8/20, waiting for 9 jobs, finished 1 job
2025-10-31 20:50:07 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 8 = ∑8/20, waiting for 8 jobs
2025-10-31 20:50:09 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 8 = ∑8/20, new result: VAL_ACC: 62.390000
2025-10-31 20:50:15 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 7 = ∑7/20, waiting for 8 jobs, finished 1 job
2025-10-31 20:50:15 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 7 = ∑7/20, waiting for 7 jobs
2025-10-31 20:50:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 7 = ∑7/20, new result: VAL_ACC: 61.580000
2025-10-31 20:50:24 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 6 = ∑6/20, waiting for 7 jobs, finished 1 job
2025-10-31 20:50:24 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 6 = ∑6/20, waiting for 6 jobs
2025-10-31 20:50:40 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 6 = ∑6/20, new result: VAL_ACC: 62.940000
2025-10-31 20:50:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 5 = ∑5/20, waiting for 6 jobs, finished 1 job
2025-10-31 20:50:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 5 = ∑5/20, waiting for 5 jobs
2025-10-31 20:51:41 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 5 = ∑5/20, new result: VAL_ACC: 63.340000
2025-10-31 20:51:47 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 4 = ∑4/20, waiting for 5 jobs, finished 1 job
2025-10-31 20:51:47 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 4 = ∑4/20, waiting for 4 jobs
2025-10-31 20:52:20 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 4 = ∑4/20, new result: VAL_ACC: 63.600000
2025-10-31 20:52:26 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 3 = ∑3/20, waiting for 4 jobs, finished 1 job
2025-10-31 20:52:26 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 3 = ∑3/20, waiting for 3 jobs
2025-10-31 20:52:27 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 3 = ∑3/20, new result: VAL_ACC: 63.970000
2025-10-31 20:52:33 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 2 = ∑2/20, waiting for 3 jobs, finished 1 job
2025-10-31 20:52:33 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 2 = ∑2/20, waiting for 2 jobs
2025-10-31 20:52:43 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 2 = ∑2/20, new result: VAL_ACC: 63.090000
2025-10-31 20:52:49 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 1 = ∑1/20, waiting for 2 jobs, finished 1 job
2025-10-31 20:52:49 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 1 = ∑1/20, waiting for 1 job
2025-10-31 20:53:26 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 1 = ∑1/20, new result: VAL_ACC: 64.200000
2025-10-31 20:53:32 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, waiting for 1 job, finished 1 job
2025-10-31 20:54:24 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #1/20
2025-10-31 20:54:25 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #2/20
2025-10-31 20:54:25 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #3/20
2025-10-31 20:54:25 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #4/20
2025-10-31 20:54:25 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #5/20
2025-10-31 20:54:27 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #6/20
2025-10-31 20:54:27 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #7/20
2025-10-31 20:54:27 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #8/20
2025-10-31 20:54:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #9/20
2025-10-31 20:54:29 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #10/20
2025-10-31 20:54:29 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #11/20
2025-10-31 20:54:29 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #12/20
2025-10-31 20:54:29 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #13/20
2025-10-31 20:54:30 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #14/20
2025-10-31 20:54:30 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #15/20
2025-10-31 20:54:30 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #16/20
2025-10-31 20:54:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #17/20
2025-10-31 20:54:36 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #18/20
2025-10-31 20:54:36 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #19/20
2025-10-31 20:54:36 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, getting new HP set #20/20
2025-10-31 20:54:36 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, requested 20 jobs, got 20, 3.17 s/job
2025-10-31 20:54:37 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #1/20 start
2025-10-31 20:54:38 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #2/20 start
2025-10-31 20:54:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #3/20 start
2025-10-31 20:54:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #4/20 start
2025-10-31 20:54:40 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #5/20 start
2025-10-31 20:54:41 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #6/20 start
2025-10-31 20:54:42 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #7/20 start
2025-10-31 20:54:42 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #8/20 start
2025-10-31 20:54:44 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #9/20 start
2025-10-31 20:55:15 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #10/20 start
2025-10-31 20:55:15 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #11/20 start
2025-10-31 20:55:16 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #12/20 start
2025-10-31 20:55:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #13/20 start
2025-10-31 20:55:18 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #14/20 start
2025-10-31 20:55:19 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #15/20 start
2025-10-31 20:55:21 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #16/20 start
2025-10-31 20:55:22 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #17/20 start
2025-10-31 20:55:23 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #18/20 start
2025-10-31 20:55:24 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #19/20 start
2025-10-31 20:55:30 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, eval #20/20 start
2025-10-31 20:55:34 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, starting new job
2025-10-31 20:56:30 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, unknown 9 = ∑9/20, started new job
2025-10-31 20:56:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, unknown 10 = ∑10/20, started new job
2025-10-31 20:56:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, unknown 10 = ∑10/20, starting new job
2025-10-31 20:56:36 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, pending/unknown 10/1 = ∑11/20, started new job
2025-10-31 20:56:45 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, pending/unknown 11/1 = ∑12/20, started new job
2025-10-31 20:56:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running/pending/unknown 10/2/1 = ∑13/20, started new job
2025-10-31 20:57:00 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running/unknown 13/1 = ∑14/20, started new job
2025-10-31 20:57:30 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running/unknown 14/2 = ∑16/20, started new job
2025-10-31 20:57:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running/pending/unknown 14/2/1 = ∑17/20, started new job
2025-10-31 20:57:40 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running/pending/unknown 14/3/1 = ∑18/20, started new job
2025-10-31 20:57:41 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running/pending/unknown 14/3/1 = ∑18/20, waiting for 18 jobs
2025-10-31 20:57:44 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running/pending 14/4 = ∑18/20, waiting for 18 jobs
2025-10-31 20:57:50 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 18 = ∑18/20, waiting for 18 jobs
2025-10-31 21:26:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 66.61, running 18 = ∑18/20, new result: VAL_ACC: 68.280000
2025-10-31 21:26:49 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.28, running 17 = ∑17/20, waiting for 18 jobs, finished 1 job
2025-10-31 21:26:49 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.28, running 17 = ∑17/20, waiting for 17 jobs
2025-10-31 21:27:12 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.28, running 17 = ∑17/20, new result: VAL_ACC: 68.040000
2025-10-31 21:27:25 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.28, running 15 = ∑15/20, waiting for 17 jobs, finished 2 jobs
2025-10-31 21:27:25 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.28, running 15 = ∑15/20, waiting for 15 jobs
2025-10-31 21:27:26 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.28, running 15 = ∑15/20, new result: VAL_ACC: 68.360000
2025-10-31 21:27:26 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.28, running 15 = ∑15/20, new result: VAL_ACC: 68.120000
2025-10-31 21:27:44 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.36, running 13 = ∑13/20, waiting for 15 jobs, finished 2 jobs
2025-10-31 21:27:44 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.36, running 13 = ∑13/20, waiting for 13 jobs
2025-10-31 21:27:45 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.36, running 13 = ∑13/20, new result: VAL_ACC: 68.310000
2025-10-31 21:27:45 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.36, running 13 = ∑13/20, new result: VAL_ACC: 68.020000
2025-10-31 21:28:07 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.36, running 11 = ∑11/20, waiting for 13 jobs, finished 2 jobs
2025-10-31 21:28:07 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.36, running 11 = ∑11/20, waiting for 11 jobs
2025-10-31 21:28:09 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.36, running 11 = ∑11/20, new result: VAL_ACC: 68.890000
2025-10-31 21:28:09 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.36, running 11 = ∑11/20, new result: VAL_ACC: 68.620000
2025-10-31 21:28:09 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.36, running 11 = ∑11/20, new result: VAL_ACC: 68.270000
2025-10-31 21:28:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, running 8 = ∑8/20, waiting for 11 jobs, finished 3 jobs
2025-10-31 21:28:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, running 8 = ∑8/20, waiting for 8 jobs
2025-10-31 21:28:32 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, running 8 = ∑8/20, new result: VAL_ACC: 67.830000
2025-10-31 21:28:32 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, running 8 = ∑8/20, new result: VAL_ACC: 68.830000
2025-10-31 21:28:33 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, running 8 = ∑8/20, new result: VAL_ACC: 68.100000
2025-10-31 21:28:53 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, running 5 = ∑5/20, waiting for 8 jobs, finished 3 jobs
2025-10-31 21:28:53 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, running 5 = ∑5/20, waiting for 5 jobs
2025-10-31 21:28:54 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, running 5 = ∑5/20, new result: VAL_ACC: 68.080000
2025-10-31 21:28:54 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, running 5 = ∑5/20, new result: VAL_ACC: 68.060000
2025-10-31 21:29:11 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, completed/running 2/1 = ∑3/20, waiting for 5 jobs, finished 2 jobs
2025-10-31 21:29:11 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, completed/running 2/1 = ∑3/20, waiting for 3 jobs
2025-10-31 21:29:13 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, completed/running 2/1 = ∑3/20, new result: VAL_ACC: 68.690000
2025-10-31 21:29:13 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, completed/running 2/1 = ∑3/20, new result: VAL_ACC: 67.960000
2025-10-31 21:29:32 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, running 1 = ∑1/20, waiting for 3 jobs, finished 2 jobs
2025-10-31 21:29:32 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, running 1 = ∑1/20, waiting for 1 job
2025-10-31 21:30:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, running 1 = ∑1/20, new result: VAL_ACC: 68.420000
2025-10-31 21:30:26 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, waiting for 1 job, finished 1 job
2025-10-31 21:31:32 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, getting new HP set #1/20
2025-10-31 21:31:32 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, getting new HP set #2/20
2025-10-31 21:31:32 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, getting new HP set #3/20
2025-10-31 21:31:33 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, getting new HP set #4/20
2025-10-31 21:31:33 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, getting new HP set #5/20
2025-10-31 21:31:33 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, getting new HP set #6/20
2025-10-31 21:31:33 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, getting new HP set #7/20
2025-10-31 21:31:33 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, getting new HP set #8/20
2025-10-31 21:31:34 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, getting new HP set #9/20
2025-10-31 21:31:34 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, getting new HP set #10/20
2025-10-31 21:31:34 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, getting new HP set #11/20
2025-10-31 21:31:34 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, getting new HP set #12/20
2025-10-31 21:31:34 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, getting new HP set #13/20
2025-10-31 21:31:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, getting new HP set #14/20
2025-10-31 21:31:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, getting new HP set #15/20
2025-10-31 21:31:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, getting new HP set #16/20
2025-10-31 21:31:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, getting new HP set #17/20
2025-10-31 21:31:36 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, getting new HP set #18/20
2025-10-31 21:31:36 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, getting new HP set #19/20
2025-10-31 21:31:36 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, getting new HP set #20/20
2025-10-31 21:31:36 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, requested 20 jobs, got 20, 3.47 s/job
2025-10-31 21:31:37 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, eval #1/20 start
2025-10-31 21:31:38 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, eval #2/20 start
2025-10-31 21:31:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, eval #3/20 start
2025-10-31 21:31:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, eval #4/20 start
2025-10-31 21:31:40 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, eval #5/20 start
2025-10-31 21:31:42 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, eval #6/20 start
2025-10-31 21:31:42 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, eval #7/20 start
2025-10-31 21:31:43 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, eval #8/20 start
2025-10-31 21:31:43 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, eval #9/20 start
2025-10-31 21:31:44 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, eval #10/20 start
2025-10-31 21:31:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, eval #11/20 start
2025-10-31 21:31:47 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, eval #12/20 start
2025-10-31 21:31:48 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, eval #13/20 start
2025-10-31 21:31:50 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, eval #14/20 start
2025-10-31 21:31:50 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, eval #15/20 start
2025-10-31 21:31:51 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, eval #16/20 start
2025-10-31 21:31:52 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, eval #17/20 start
2025-10-31 21:31:53 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, eval #18/20 start
2025-10-31 21:31:54 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, eval #19/20 start
2025-10-31 21:31:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, eval #20/20 start
2025-10-31 21:31:59 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, starting new job
2025-10-31 21:32:01 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, unknown 1 = ∑1/20, started new job
2025-10-31 21:32:01 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, unknown 1 = ∑1/20, starting new job
2025-10-31 21:32:11 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, running/unknown 1/3 = ∑4/20, started new job
2025-10-31 21:32:12 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, running/unknown 1/3 = ∑4/20, starting new job
2025-10-31 21:32:21 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, running/pending/unknown 1/3/3 = ∑7/20, started new job
2025-10-31 21:32:26 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, running/pending/unknown 1/6/3 = ∑10/20, started new job
2025-10-31 21:32:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, running/unknown 10/2 = ∑12/20, started new job
2025-10-31 21:32:32 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, running/unknown 10/3 = ∑13/20, started new job
2025-10-31 21:32:36 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, running/pending 10/5 = ∑15/20, started new job
2025-10-31 21:32:41 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, running/pending 10/8 = ∑18/20, started new job
2025-10-31 21:32:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, running/pending 10/10 = ∑20/20, started new job
2025-10-31 21:32:47 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, running/pending 10/10 = ∑20/20, waiting for 20 jobs
2025-10-31 21:32:48 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, running 20 = ∑20/20, waiting for 20 jobs
2025-10-31 21:51:08 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.89, running 20 = ∑20/20, new result: VAL_ACC: 68.920000
2025-10-31 21:51:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.92, running 19 = ∑19/20, waiting for 20 jobs, finished 1 job
2025-10-31 21:51:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.92, running 19 = ∑19/20, waiting for 19 jobs
2025-10-31 21:51:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 68.92, running 19 = ∑19/20, new result: VAL_ACC: 69.160000
2025-10-31 21:52:02 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.16, running 18 = ∑18/20, waiting for 19 jobs, finished 1 job
2025-10-31 21:52:02 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.16, running 18 = ∑18/20, waiting for 18 jobs
2025-10-31 21:56:13 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.16, running 18 = ∑18/20, new result: VAL_ACC: 69.550000
2025-10-31 21:56:50 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.55, running 17 = ∑17/20, waiting for 18 jobs, finished 1 job
2025-10-31 21:56:50 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.55, running 17 = ∑17/20, waiting for 17 jobs
2025-10-31 22:02:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.55, running 17 = ∑17/20, new result: VAL_ACC: 67.290000
2025-10-31 22:03:03 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.55, running 16 = ∑16/20, waiting for 17 jobs, finished 1 job
2025-10-31 22:03:03 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.55, running 16 = ∑16/20, waiting for 16 jobs
2025-10-31 22:04:41 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.55, running 16 = ∑16/20, new result: VAL_ACC: 69.730000
2025-10-31 22:04:48 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.73, running 15 = ∑15/20, waiting for 16 jobs, finished 1 job
2025-10-31 22:04:48 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.73, running 15 = ∑15/20, waiting for 15 jobs
2025-10-31 22:05:57 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.73, running 15 = ∑15/20, new result: VAL_ACC: 68.380000
2025-10-31 22:06:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.73, running 14 = ∑14/20, waiting for 15 jobs, finished 1 job
2025-10-31 22:06:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.73, running 14 = ∑14/20, waiting for 14 jobs
2025-10-31 22:06:48 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.73, running 14 = ∑14/20, new result: VAL_ACC: 68.600000
2025-10-31 22:06:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.73, running 13 = ∑13/20, waiting for 14 jobs, finished 1 job
2025-10-31 22:06:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.73, running 13 = ∑13/20, waiting for 13 jobs
2025-10-31 22:08:01 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.73, running 13 = ∑13/20, new result: VAL_ACC: 68.850000
2025-10-31 22:08:08 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.73, running 12 = ∑12/20, waiting for 13 jobs, finished 1 job
2025-10-31 22:08:09 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.73, running 12 = ∑12/20, waiting for 12 jobs
2025-10-31 22:08:26 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.73, running 12 = ∑12/20, new result: VAL_ACC: 69.280000
2025-10-31 22:08:33 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.73, running 11 = ∑11/20, waiting for 12 jobs, finished 1 job
2025-10-31 22:08:33 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.73, running 11 = ∑11/20, waiting for 11 jobs
2025-10-31 22:10:12 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.73, running 11 = ∑11/20, new result: VAL_ACC: 69.400000
2025-10-31 22:10:19 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.73, running 10 = ∑10/20, waiting for 11 jobs, finished 1 job
2025-10-31 22:10:19 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.73, running 10 = ∑10/20, waiting for 10 jobs
2025-10-31 22:12:09 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.73, running 10 = ∑10/20, new result: VAL_ACC: 69.660000
2025-10-31 22:12:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.73, running 9 = ∑9/20, waiting for 10 jobs, finished 1 job
2025-10-31 22:12:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.73, running 9 = ∑9/20, waiting for 9 jobs
2025-10-31 22:12:18 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.73, running 9 = ∑9/20, new result: VAL_ACC: 69.740000
2025-10-31 22:12:26 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, running 8 = ∑8/20, waiting for 9 jobs, finished 1 job
2025-10-31 22:12:26 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, running 8 = ∑8/20, waiting for 8 jobs
2025-10-31 22:13:02 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, running 8 = ∑8/20, new result: VAL_ACC: 68.450000
2025-10-31 22:13:10 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, running 7 = ∑7/20, waiting for 8 jobs, finished 1 job
2025-10-31 22:13:10 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, running 7 = ∑7/20, waiting for 7 jobs
2025-10-31 22:14:40 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, running 7 = ∑7/20, new result: VAL_ACC: 69.500000
2025-10-31 22:14:47 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, running 6 = ∑6/20, waiting for 7 jobs, finished 1 job
2025-10-31 22:14:47 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, running 6 = ∑6/20, waiting for 6 jobs
2025-10-31 22:16:29 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, running 6 = ∑6/20, new result: VAL_ACC: 67.230000
2025-10-31 22:16:37 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, running 5 = ∑5/20, waiting for 6 jobs, finished 1 job
2025-10-31 22:16:37 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, running 5 = ∑5/20, waiting for 5 jobs
2025-10-31 22:17:14 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, running 5 = ∑5/20, new result: VAL_ACC: 69.730000
2025-10-31 22:17:22 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, running 4 = ∑4/20, waiting for 5 jobs, finished 1 job
2025-10-31 22:17:22 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, running 4 = ∑4/20, waiting for 4 jobs
2025-10-31 22:24:03 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, running 4 = ∑4/20, new result: VAL_ACC: 69.360000
2025-10-31 22:24:10 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, running 3 = ∑3/20, waiting for 4 jobs, finished 1 job
2025-10-31 22:24:10 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, running 3 = ∑3/20, waiting for 3 jobs
2025-10-31 22:24:37 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, running 3 = ∑3/20, new result: VAL_ACC: 68.270000
2025-10-31 22:24:44 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, running 2 = ∑2/20, waiting for 3 jobs, finished 1 job
2025-10-31 22:24:44 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, running 2 = ∑2/20, waiting for 2 jobs
2025-10-31 22:36:52 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, running 2 = ∑2/20, new result: VAL_ACC: 67.710000
2025-10-31 22:37:00 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, running 1 = ∑1/20, waiting for 2 jobs, finished 1 job
2025-10-31 22:37:00 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, running 1 = ∑1/20, waiting for 1 job
2025-10-31 22:50:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, running 1 = ∑1/20, new result: VAL_ACC: 67.440000
2025-10-31 22:50:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, waiting for 1 job, finished 1 job
2025-10-31 22:51:51 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, getting new HP set #1/20
2025-10-31 22:51:51 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, getting new HP set #2/20
2025-10-31 22:51:52 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, getting new HP set #3/20
2025-10-31 22:51:52 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, getting new HP set #4/20
2025-10-31 22:51:52 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, getting new HP set #5/20
2025-10-31 22:51:53 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, getting new HP set #6/20
2025-10-31 22:51:54 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, getting new HP set #7/20
2025-10-31 22:51:54 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, getting new HP set #8/20
2025-10-31 22:51:54 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, getting new HP set #9/20
2025-10-31 22:51:54 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, getting new HP set #10/20
2025-10-31 22:51:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, getting new HP set #11/20
2025-10-31 22:51:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, getting new HP set #12/20
2025-10-31 22:51:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, getting new HP set #13/20
2025-10-31 22:51:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, getting new HP set #14/20
2025-10-31 22:51:56 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, getting new HP set #15/20
2025-10-31 22:51:57 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, getting new HP set #16/20
2025-10-31 22:51:57 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, getting new HP set #17/20
2025-10-31 22:51:57 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, getting new HP set #18/20
2025-10-31 22:51:58 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, getting new HP set #19/20
2025-10-31 22:51:58 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, getting new HP set #20/20
2025-10-31 22:51:58 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, requested 20 jobs, got 20, 3.55 s/job
2025-10-31 22:51:59 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, eval #1/20 start
2025-10-31 22:52:00 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, eval #2/20 start
2025-10-31 22:52:00 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, eval #3/20 start
2025-10-31 22:52:01 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, eval #4/20 start
2025-10-31 22:52:02 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, eval #5/20 start
2025-10-31 22:52:03 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, eval #6/20 start
2025-10-31 22:52:03 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, eval #7/20 start
2025-10-31 22:52:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, eval #8/20 start
2025-10-31 22:52:05 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, eval #9/20 start
2025-10-31 22:52:05 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, eval #10/20 start
2025-10-31 22:52:06 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, eval #11/20 start
2025-10-31 22:52:07 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, eval #12/20 start
2025-10-31 22:52:08 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, eval #13/20 start
2025-10-31 22:52:08 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, eval #14/20 start
2025-10-31 22:52:09 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, eval #15/20 start
2025-10-31 22:52:10 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, eval #16/20 start
2025-10-31 22:52:10 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, eval #17/20 start
2025-10-31 22:52:11 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, eval #18/20 start
2025-10-31 22:52:12 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, eval #19/20 start
2025-10-31 22:52:12 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, eval #20/20 start
2025-10-31 22:52:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, starting new job
2025-10-31 22:52:20 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, unknown 3 = ∑3/20, started new job
2025-10-31 22:52:21 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, unknown 3 = ∑3/20, starting new job
2025-10-31 22:52:24 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, pending 3 = ∑3/20, starting new job
2025-10-31 22:52:24 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, pending/unknown 3/1 = ∑4/20, started new job
2025-10-31 22:52:25 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, pending/unknown 3/1 = ∑4/20, starting new job
2025-10-31 22:52:29 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, running/unknown 4/1 = ∑5/20, started new job
2025-10-31 22:52:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, running/unknown 5/2 = ∑7/20, started new job
2025-10-31 22:52:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, running/pending/unknown 5/2/1 = ∑8/20, started new job
2025-10-31 22:52:45 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, running/pending/unknown 5/3/2 = ∑10/20, started new job
2025-10-31 22:52:50 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, running/pending/unknown 5/5/3 = ∑13/20, started new job
2025-10-31 22:52:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, running/unknown 13/3 = ∑16/20, started new job
2025-10-31 22:52:59 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, running/unknown 16/1 = ∑17/20, started new job
2025-10-31 22:53:05 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, running/pending/unknown 16/1/2 = ∑19/20, started new job
2025-10-31 22:53:09 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, running/pending/unknown 16/3/1 = ∑20/20, started new job
2025-10-31 22:53:11 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, running/pending/unknown 16/3/1 = ∑20/20, waiting for 20 jobs
2025-10-31 22:53:12 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, running 20 = ∑20/20, waiting for 20 jobs
2025-10-31 23:02:38 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, running 20 = ∑20/20, new result: VAL_ACC: 69.470000
2025-10-31 23:02:51 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, running 19 = ∑19/20, waiting for 20 jobs, finished 1 job
2025-10-31 23:02:51 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, running 19 = ∑19/20, waiting for 19 jobs
2025-10-31 23:04:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 69.74, running 19 = ∑19/20, new result: VAL_ACC: 70.140000
2025-10-31 23:04:44 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 70.14, running 18 = ∑18/20, waiting for 19 jobs, finished 1 job
2025-10-31 23:04:44 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 70.14, running 18 = ∑18/20, waiting for 18 jobs
2025-10-31 23:05:13 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 70.14, running 18 = ∑18/20, new result: VAL_ACC: 69.910000
2025-10-31 23:05:21 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 70.14, running 17 = ∑17/20, waiting for 18 jobs, finished 1 job
2025-10-31 23:05:21 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 70.14, running 17 = ∑17/20, waiting for 17 jobs
2025-10-31 23:06:02 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 70.14, running 17 = ∑17/20, new result: VAL_ACC: 69.620000
2025-10-31 23:06:10 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 70.14, running 16 = ∑16/20, waiting for 17 jobs, finished 1 job
2025-10-31 23:06:11 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 70.14, running 16 = ∑16/20, waiting for 16 jobs
2025-10-31 23:06:45 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 70.14, running 16 = ∑16/20, new result: VAL_ACC: 70.020000
2025-10-31 23:06:53 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 70.14, running 15 = ∑15/20, waiting for 16 jobs, finished 1 job
2025-10-31 23:06:53 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 70.14, running 15 = ∑15/20, waiting for 15 jobs
2025-10-31 23:08:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 70.14, running 15 = ∑15/20, new result: VAL_ACC: 70.220000
2025-10-31 23:08:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 70.22, running 14 = ∑14/20, waiting for 15 jobs, finished 1 job
2025-10-31 23:08:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 70.22, running 14 = ∑14/20, waiting for 14 jobs
2025-10-31 23:08:41 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 70.22, running 14 = ∑14/20, new result: VAL_ACC: 71.080000
2025-10-31 23:08:41 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 70.22, running 14 = ∑14/20, new result: VAL_ACC: 69.980000
2025-10-31 23:08:59 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running 12 = ∑12/20, waiting for 14 jobs, finished 2 jobs
2025-10-31 23:09:00 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running 12 = ∑12/20, waiting for 12 jobs
2025-10-31 23:10:57 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running 12 = ∑12/20, new result: VAL_ACC: 70.440000
2025-10-31 23:11:06 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running 11 = ∑11/20, waiting for 12 jobs, finished 1 job
2025-10-31 23:11:06 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running 11 = ∑11/20, waiting for 11 jobs
2025-10-31 23:11:09 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running 11 = ∑11/20, new result: VAL_ACC: 70.500000
2025-10-31 23:11:18 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running 10 = ∑10/20, waiting for 11 jobs, finished 1 job
2025-10-31 23:11:18 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running 10 = ∑10/20, waiting for 10 jobs
2025-10-31 23:11:59 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running 10 = ∑10/20, new result: VAL_ACC: 70.530000
2025-10-31 23:12:07 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running 9 = ∑9/20, waiting for 10 jobs, finished 1 job
2025-10-31 23:12:07 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running 9 = ∑9/20, waiting for 9 jobs
2025-10-31 23:12:12 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running 9 = ∑9/20, new result: VAL_ACC: 71.070000
2025-10-31 23:12:20 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running 8 = ∑8/20, waiting for 9 jobs, finished 1 job
2025-10-31 23:12:20 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running 8 = ∑8/20, waiting for 8 jobs
2025-10-31 23:12:21 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running 8 = ∑8/20, new result: VAL_ACC: 70.380000
2025-10-31 23:12:29 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running 7 = ∑7/20, waiting for 8 jobs, finished 1 job
2025-10-31 23:12:30 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running 7 = ∑7/20, waiting for 7 jobs
2025-10-31 23:12:30 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running 7 = ∑7/20, new result: VAL_ACC: 70.590000
2025-10-31 23:12:38 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running 6 = ∑6/20, waiting for 7 jobs, finished 1 job
2025-10-31 23:12:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running 6 = ∑6/20, waiting for 6 jobs
2025-10-31 23:12:49 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running 6 = ∑6/20, new result: VAL_ACC: 70.780000
2025-10-31 23:12:58 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running 5 = ∑5/20, waiting for 6 jobs, finished 1 job
2025-10-31 23:12:58 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running 5 = ∑5/20, waiting for 5 jobs
2025-10-31 23:13:51 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running 5 = ∑5/20, new result: VAL_ACC: 70.800000
2025-10-31 23:14:00 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running 4 = ∑4/20, waiting for 5 jobs, finished 1 job
2025-10-31 23:14:00 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running 4 = ∑4/20, waiting for 4 jobs
2025-10-31 23:14:01 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running 4 = ∑4/20, new result: VAL_ACC: 70.500000
2025-10-31 23:14:09 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running 3 = ∑3/20, waiting for 4 jobs, finished 1 job
2025-10-31 23:14:09 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running 3 = ∑3/20, waiting for 3 jobs
2025-10-31 23:15:07 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running 3 = ∑3/20, new result: VAL_ACC: 71.020000
2025-10-31 23:15:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running 2 = ∑2/20, waiting for 3 jobs, finished 1 job
2025-10-31 23:15:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running 2 = ∑2/20, waiting for 2 jobs
2025-10-31 23:15:19 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running 2 = ∑2/20, new result: VAL_ACC: 70.970000
2025-10-31 23:15:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running 1 = ∑1/20, waiting for 2 jobs, finished 1 job
2025-10-31 23:15:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running 1 = ∑1/20, waiting for 1 job
2025-10-31 23:16:12 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running 1 = ∑1/20, new result: VAL_ACC: 70.920000
2025-10-31 23:16:20 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, waiting for 1 job, finished 1 job
2025-10-31 23:17:50 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, getting new HP set #1/20
2025-10-31 23:17:50 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, getting new HP set #2/20
2025-10-31 23:17:50 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, getting new HP set #3/20
2025-10-31 23:17:51 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, getting new HP set #4/20
2025-10-31 23:17:52 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, getting new HP set #5/20
2025-10-31 23:17:53 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, getting new HP set #6/20
2025-10-31 23:17:54 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, getting new HP set #7/20
2025-10-31 23:17:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, getting new HP set #8/20
2025-10-31 23:17:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, getting new HP set #9/20
2025-10-31 23:17:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, getting new HP set #10/20
2025-10-31 23:17:56 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, getting new HP set #11/20
2025-10-31 23:17:56 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, getting new HP set #12/20
2025-10-31 23:17:56 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, getting new HP set #13/20
2025-10-31 23:17:56 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, getting new HP set #14/20
2025-10-31 23:17:58 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, getting new HP set #15/20
2025-10-31 23:17:59 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, getting new HP set #16/20
2025-10-31 23:18:00 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, getting new HP set #17/20
2025-10-31 23:18:00 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, getting new HP set #18/20
2025-10-31 23:18:01 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, getting new HP set #19/20
2025-10-31 23:18:01 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, getting new HP set #20/20
2025-10-31 23:18:01 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, requested 20 jobs, got 20, 5.03 s/job
2025-10-31 23:18:03 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, eval #1/20 start
2025-10-31 23:18:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, eval #2/20 start
2025-10-31 23:18:05 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, eval #3/20 start
2025-10-31 23:18:05 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, eval #4/20 start
2025-10-31 23:18:06 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, eval #5/20 start
2025-10-31 23:18:12 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, eval #6/20 start
2025-10-31 23:18:12 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, eval #7/20 start
2025-10-31 23:18:13 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, eval #8/20 start
2025-10-31 23:18:14 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, eval #9/20 start
2025-10-31 23:18:15 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, eval #10/20 start
2025-10-31 23:18:15 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, eval #11/20 start
2025-10-31 23:18:16 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, eval #12/20 start
2025-10-31 23:18:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, eval #13/20 start
2025-10-31 23:18:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, eval #14/20 start
2025-10-31 23:18:19 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, eval #15/20 start
2025-10-31 23:18:22 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, eval #16/20 start
2025-10-31 23:18:23 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, eval #17/20 start
2025-10-31 23:18:24 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, eval #18/20 start
2025-10-31 23:18:26 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, eval #19/20 start
2025-10-31 23:18:27 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, eval #20/20 start
2025-10-31 23:18:32 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, starting new job
2025-10-31 23:18:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, pending 3 = ∑3/20, started new job
2025-10-31 23:18:36 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, pending 3 = ∑3/20, starting new job
2025-10-31 23:18:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running/unknown 3/1 = ∑4/20, started new job
2025-10-31 23:18:40 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running/unknown 3/1 = ∑4/20, starting new job
2025-10-31 23:18:49 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running/pending/unknown 3/1/1 = ∑5/20, started new job
2025-10-31 23:18:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running/unknown 5/1 = ∑6/20, started new job
2025-10-31 23:19:05 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running/unknown 6/1 = ∑7/20, started new job
2025-10-31 23:19:09 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running/pending/unknown 6/1/1 = ∑8/20, started new job
2025-10-31 23:19:14 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running/unknown 8/1 = ∑9/20, started new job
2025-10-31 23:19:20 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running/pending/unknown 8/1/1 = ∑10/20, started new job
2025-10-31 23:19:29 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running/unknown 10/1 = ∑11/20, started new job
2025-10-31 23:19:34 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running/unknown 11/1 = ∑12/20, started new job
2025-10-31 23:19:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running/pending/unknown 11/1/1 = ∑13/20, started new job
2025-10-31 23:19:50 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running/pending/unknown 11/2/2 = ∑15/20, started new job
2025-10-31 23:19:59 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running/unknown 15/1 = ∑16/20, started new job
2025-10-31 23:20:11 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running/pending 15/1 = ∑16/20, waiting for 16 jobs
2025-10-31 23:20:22 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running 16 = ∑16/20, waiting for 16 jobs
2025-11-01 00:00:06 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.08, running 16 = ∑16/20, new result: VAL_ACC: 71.180000
2025-11-01 00:00:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.18, running 15 = ∑15/20, waiting for 16 jobs, finished 1 job
2025-11-01 00:00:18 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.18, running 15 = ∑15/20, waiting for 15 jobs
2025-11-01 00:00:53 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.18, running 15 = ∑15/20, new result: VAL_ACC: 71.220000
2025-11-01 00:01:02 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 14 = ∑14/20, waiting for 15 jobs, finished 1 job
2025-11-01 00:01:02 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 14 = ∑14/20, waiting for 14 jobs
2025-11-01 00:01:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 14 = ∑14/20, new result: VAL_ACC: 70.940000
2025-11-01 00:01:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 14 = ∑14/20, new result: VAL_ACC: 70.760000
2025-11-01 00:01:19 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 12 = ∑12/20, waiting for 14 jobs, finished 2 jobs
2025-11-01 00:01:20 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 12 = ∑12/20, waiting for 12 jobs
2025-11-01 00:01:21 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 12 = ∑12/20, new result: VAL_ACC: 70.460000
2025-11-01 00:01:30 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 11 = ∑11/20, waiting for 12 jobs, finished 1 job
2025-11-01 00:01:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 11 = ∑11/20, waiting for 11 jobs
2025-11-01 00:01:32 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 11 = ∑11/20, new result: VAL_ACC: 70.620000
2025-11-01 00:01:32 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 11 = ∑11/20, new result: VAL_ACC: 70.610000
2025-11-01 00:01:48 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 9 = ∑9/20, waiting for 11 jobs, finished 2 jobs
2025-11-01 00:01:48 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 9 = ∑9/20, waiting for 9 jobs
2025-11-01 00:01:49 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 9 = ∑9/20, new result: VAL_ACC: 70.790000
2025-11-01 00:01:58 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 8 = ∑8/20, waiting for 9 jobs, finished 1 job
2025-11-01 00:01:58 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 8 = ∑8/20, waiting for 8 jobs
2025-11-01 00:02:00 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 8 = ∑8/20, new result: VAL_ACC: 70.760000
2025-11-01 00:02:00 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 8 = ∑8/20, new result: VAL_ACC: 70.720000
2025-11-01 00:02:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 6 = ∑6/20, waiting for 8 jobs, finished 2 jobs
2025-11-01 00:02:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 6 = ∑6/20, waiting for 6 jobs
2025-11-01 00:02:18 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 6 = ∑6/20, new result: VAL_ACC: 70.230000
2025-11-01 00:02:18 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 6 = ∑6/20, new result: VAL_ACC: 70.940000
2025-11-01 00:02:34 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 4 = ∑4/20, waiting for 6 jobs, finished 2 jobs
2025-11-01 00:02:34 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 4 = ∑4/20, waiting for 4 jobs
2025-11-01 00:02:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 4 = ∑4/20, new result: VAL_ACC: 70.870000
2025-11-01 00:02:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 4 = ∑4/20, new result: VAL_ACC: 71.020000
2025-11-01 00:02:36 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 4 = ∑4/20, new result: VAL_ACC: 71.060000
2025-11-01 00:03:00 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, completed 1 = ∑1/20, waiting for 4 jobs, finished 3 jobs
2025-11-01 00:03:00 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, completed 1 = ∑1/20, waiting for 1 job
2025-11-01 00:03:01 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, completed 1 = ∑1/20, new result: VAL_ACC: 70.960000
2025-11-01 00:03:15 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, waiting for 1 job, finished 1 job
2025-11-01 00:05:16 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, getting new HP set #1/20
2025-11-01 00:05:16 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, getting new HP set #2/20
2025-11-01 00:05:16 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, getting new HP set #3/20
2025-11-01 00:05:16 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, getting new HP set #4/20
2025-11-01 00:05:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, getting new HP set #5/20
2025-11-01 00:05:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, getting new HP set #6/20
2025-11-01 00:05:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, getting new HP set #7/20
2025-11-01 00:05:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, getting new HP set #8/20
2025-11-01 00:05:18 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, getting new HP set #9/20
2025-11-01 00:05:18 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, getting new HP set #10/20
2025-11-01 00:05:18 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, getting new HP set #11/20
2025-11-01 00:05:19 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, getting new HP set #12/20
2025-11-01 00:05:19 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, getting new HP set #13/20
2025-11-01 00:05:19 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, getting new HP set #14/20
2025-11-01 00:05:20 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, getting new HP set #15/20
2025-11-01 00:05:21 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, getting new HP set #16/20
2025-11-01 00:05:21 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, getting new HP set #17/20
2025-11-01 00:05:21 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, getting new HP set #18/20
2025-11-01 00:05:21 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, getting new HP set #19/20
2025-11-01 00:05:22 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, getting new HP set #20/20
2025-11-01 00:05:22 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, requested 20 jobs, got 20, 6.31 s/job
2025-11-01 00:05:23 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, eval #1/20 start
2025-11-01 00:05:24 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, eval #2/20 start
2025-11-01 00:05:27 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, eval #3/20 start
2025-11-01 00:05:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, eval #4/20 start
2025-11-01 00:05:30 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, eval #5/20 start
2025-11-01 00:05:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, eval #6/20 start
2025-11-01 00:05:32 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, eval #7/20 start
2025-11-01 00:05:32 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, eval #8/20 start
2025-11-01 00:05:33 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, eval #9/20 start
2025-11-01 00:05:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, eval #10/20 start
2025-11-01 00:05:36 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, eval #11/20 start
2025-11-01 00:05:37 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, eval #12/20 start
2025-11-01 00:05:37 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, eval #13/20 start
2025-11-01 00:05:38 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, eval #14/20 start
2025-11-01 00:05:40 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, eval #15/20 start
2025-11-01 00:05:41 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, eval #16/20 start
2025-11-01 00:05:41 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, eval #17/20 start
2025-11-01 00:05:42 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, eval #18/20 start
2025-11-01 00:05:44 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, eval #19/20 start
2025-11-01 00:05:45 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, eval #20/20 start
2025-11-01 00:05:51 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, starting new job
2025-11-01 00:05:53 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, pending 3 = ∑3/20, starting new job
2025-11-01 00:05:53 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, pending 3 = ∑3/20, started new job
2025-11-01 00:05:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, pending 3 = ∑3/20, starting new job
2025-11-01 00:05:58 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running/unknown/pending 3/2/1 = ∑6/20, started new job
2025-11-01 00:05:59 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running/unknown/pending 3/2/1 = ∑6/20, starting new job
2025-11-01 00:06:03 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running/unknown 6/2 = ∑8/20, started new job
2025-11-01 00:06:08 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running/pending/unknown 6/2/3 = ∑11/20, started new job
2025-11-01 00:06:13 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running/pending 11/2 = ∑13/20, started new job
2025-11-01 00:06:18 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running/unknown 13/3 = ∑16/20, started new job
2025-11-01 00:06:23 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running/pending/unknown 13/3/3 = ∑19/20, started new job
2025-11-01 00:06:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running/pending/unknown 13/6/1 = ∑20/20, started new job
2025-11-01 00:06:29 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running/pending/unknown 13/6/1 = ∑20/20, waiting for 20 jobs
2025-11-01 00:06:30 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 20 = ∑20/20, waiting for 20 jobs
2025-11-01 00:45:36 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 20 = ∑20/20, new result: VAL_ACC: 71.180000
2025-11-01 00:45:48 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 19 = ∑19/20, waiting for 20 jobs, finished 1 job
2025-11-01 00:45:48 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 19 = ∑19/20, waiting for 19 jobs
2025-11-01 00:45:54 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 19 = ∑19/20, new result: VAL_ACC: 69.880000
2025-11-01 00:46:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 18 = ∑18/20, waiting for 19 jobs, finished 1 job
2025-11-01 00:46:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 18 = ∑18/20, waiting for 18 jobs
2025-11-01 00:46:05 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 18 = ∑18/20, new result: VAL_ACC: 70.340000
2025-11-01 00:46:15 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 17 = ∑17/20, waiting for 18 jobs, finished 1 job
2025-11-01 00:46:16 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 17 = ∑17/20, waiting for 17 jobs
2025-11-01 00:46:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 17 = ∑17/20, new result: VAL_ACC: 70.750000
2025-11-01 00:46:27 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 16 = ∑16/20, waiting for 17 jobs, finished 1 job
2025-11-01 00:46:27 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 16 = ∑16/20, waiting for 16 jobs
2025-11-01 00:46:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 16 = ∑16/20, new result: VAL_ACC: 70.380000
2025-11-01 00:46:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 15 = ∑15/20, waiting for 16 jobs, finished 1 job
2025-11-01 00:46:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 15 = ∑15/20, waiting for 15 jobs
2025-11-01 00:46:42 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 15 = ∑15/20, new result: VAL_ACC: 70.540000
2025-11-01 00:46:42 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 15 = ∑15/20, new result: VAL_ACC: 71.380000
2025-11-01 00:46:42 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 15 = ∑15/20, new result: VAL_ACC: 70.090000
2025-11-01 00:46:42 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 15 = ∑15/20, new result: VAL_ACC: 70.640000
2025-11-01 00:46:42 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.22, running 15 = ∑15/20, new result: VAL_ACC: 70.790000
2025-11-01 00:47:23 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 10 = ∑10/20, waiting for 15 jobs, finished 5 jobs
2025-11-01 00:47:23 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 10 = ∑10/20, waiting for 10 jobs
2025-11-01 00:47:27 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 10 = ∑10/20, new result: VAL_ACC: 70.690000
2025-11-01 00:47:27 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 10 = ∑10/20, new result: VAL_ACC: 70.830000
2025-11-01 00:47:27 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 10 = ∑10/20, new result: VAL_ACC: 70.460000
2025-11-01 00:47:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 10 = ∑10/20, new result: VAL_ACC: 70.940000
2025-11-01 00:47:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 10 = ∑10/20, new result: VAL_ACC: 70.410000
2025-11-01 00:47:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 10 = ∑10/20, new result: VAL_ACC: 70.640000
2025-11-01 00:47:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 10 = ∑10/20, new result: VAL_ACC: 70.990000
2025-11-01 00:47:29 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 10 = ∑10/20, new result: VAL_ACC: 70.720000
2025-11-01 00:47:29 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 10 = ∑10/20, new result: VAL_ACC: 70.230000
2025-11-01 00:48:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 1 = ∑1/20, waiting for 10 jobs, finished 9 jobs
2025-11-01 00:48:56 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 1 = ∑1/20, waiting for 1 job
2025-11-01 00:48:57 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 1 = ∑1/20, new result: VAL_ACC: 70.870000
2025-11-01 00:49:11 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, waiting for 1 job, finished 1 job
2025-11-01 00:51:22 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, getting new HP set #1/20
2025-11-01 00:51:23 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, getting new HP set #2/20
2025-11-01 00:51:23 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, getting new HP set #3/20
2025-11-01 00:51:23 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, getting new HP set #4/20
2025-11-01 00:51:23 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, getting new HP set #5/20
2025-11-01 00:51:24 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, getting new HP set #6/20
2025-11-01 00:51:24 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, getting new HP set #7/20
2025-11-01 00:51:24 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, getting new HP set #8/20
2025-11-01 00:51:25 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, getting new HP set #9/20
2025-11-01 00:51:25 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, getting new HP set #10/20
2025-11-01 00:51:25 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, getting new HP set #11/20
2025-11-01 00:51:25 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, getting new HP set #12/20
2025-11-01 00:51:26 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, getting new HP set #13/20
2025-11-01 00:51:27 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, getting new HP set #14/20
2025-11-01 00:51:27 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, getting new HP set #15/20
2025-11-01 00:51:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, getting new HP set #16/20
2025-11-01 00:51:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, getting new HP set #17/20
2025-11-01 00:51:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, getting new HP set #18/20
2025-11-01 00:51:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, getting new HP set #19/20
2025-11-01 00:51:29 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, getting new HP set #20/20
2025-11-01 00:51:29 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, requested 20 jobs, got 20, 6.84 s/job
2025-11-01 00:51:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, eval #1/20 start
2025-11-01 00:51:32 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, eval #2/20 start
2025-11-01 00:51:34 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, eval #3/20 start
2025-11-01 00:51:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, eval #4/20 start
2025-11-01 00:51:36 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, eval #5/20 start
2025-11-01 00:51:36 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, eval #6/20 start
2025-11-01 00:51:37 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, eval #7/20 start
2025-11-01 00:52:11 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, eval #8/20 start
2025-11-01 00:52:12 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, eval #9/20 start
2025-11-01 00:52:13 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, eval #10/20 start
2025-11-01 00:52:13 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, eval #11/20 start
2025-11-01 00:52:15 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, eval #12/20 start
2025-11-01 00:52:16 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, eval #13/20 start
2025-11-01 00:52:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, eval #14/20 start
2025-11-01 00:52:18 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, eval #15/20 start
2025-11-01 00:52:19 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, eval #16/20 start
2025-11-01 00:52:19 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, eval #17/20 start
2025-11-01 00:52:20 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, eval #18/20 start
2025-11-01 00:52:21 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, eval #19/20 start
2025-11-01 00:52:22 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, eval #20/20 start
2025-11-01 00:52:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, starting new job
2025-11-01 00:52:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, pending 3 = ∑3/20, started new job
2025-11-01 00:52:32 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, pending 3 = ∑3/20, starting new job
2025-11-01 00:52:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running/unknown 3/1 = ∑4/20, started new job
2025-11-01 00:52:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running/unknown 3/1 = ∑4/20, starting new job
2025-11-01 00:52:40 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running/unknown 4/2 = ∑6/20, started new job
2025-11-01 00:52:45 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running/pending/unknown 4/2/1 = ∑7/20, started new job
2025-11-01 00:52:50 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running/pending/unknown 5/2/1 = ∑8/20, started new job
2025-11-01 00:52:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running/unknown 8/2 = ∑10/20, started new job
2025-11-01 00:53:01 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running/pending/unknown 8/2/3 = ∑13/20, started new job
2025-11-01 00:53:06 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running/pending/unknown 8/5/3 = ∑16/20, started new job
2025-11-01 00:53:10 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running/pending 16/1 = ∑17/20, started new job
2025-11-01 00:53:15 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running/unknown 17/2 = ∑19/20, started new job
2025-11-01 00:53:20 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running/pending/unknown 17/2/1 = ∑20/20, started new job
2025-11-01 00:53:21 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running/pending/unknown 17/2/1 = ∑20/20, waiting for 20 jobs
2025-11-01 00:53:25 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running/pending 17/3 = ∑20/20, waiting for 20 jobs
2025-11-01 00:53:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 20 = ∑20/20, waiting for 20 jobs
2025-11-01 01:23:37 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 20 = ∑20/20, new result: VAL_ACC: 70.630000
2025-11-01 01:23:49 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 19 = ∑19/20, waiting for 20 jobs, finished 1 job
2025-11-01 01:23:49 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 19 = ∑19/20, waiting for 19 jobs
2025-11-01 01:24:02 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 19 = ∑19/20, new result: VAL_ACC: 70.600000
2025-11-01 01:24:13 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 18 = ∑18/20, waiting for 19 jobs, finished 1 job
2025-11-01 01:24:13 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 18 = ∑18/20, waiting for 18 jobs
2025-11-01 01:24:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 18 = ∑18/20, new result: VAL_ACC: 70.250000
2025-11-01 01:24:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 17 = ∑17/20, waiting for 18 jobs, finished 1 job
2025-11-01 01:24:40 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 17 = ∑17/20, waiting for 17 jobs
2025-11-01 01:26:32 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 17 = ∑17/20, new result: VAL_ACC: 71.090000
2025-11-01 01:26:43 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 16 = ∑16/20, waiting for 17 jobs, finished 1 job
2025-11-01 01:26:44 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 16 = ∑16/20, waiting for 16 jobs
2025-11-01 01:26:44 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 16 = ∑16/20, new result: VAL_ACC: 71.050000
2025-11-01 01:26:56 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 15 = ∑15/20, waiting for 16 jobs, finished 1 job
2025-11-01 01:26:56 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 15 = ∑15/20, waiting for 15 jobs
2025-11-01 01:27:21 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 15 = ∑15/20, new result: VAL_ACC: 70.940000
2025-11-01 01:27:33 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 14 = ∑14/20, waiting for 15 jobs, finished 1 job
2025-11-01 01:27:33 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 14 = ∑14/20, waiting for 14 jobs
2025-11-01 01:27:34 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 14 = ∑14/20, new result: VAL_ACC: 70.680000
2025-11-01 01:27:45 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 13 = ∑13/20, waiting for 14 jobs, finished 1 job
2025-11-01 01:27:45 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 13 = ∑13/20, waiting for 13 jobs
2025-11-01 01:28:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 13 = ∑13/20, new result: VAL_ACC: 71.080000
2025-11-01 01:28:41 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 12 = ∑12/20, waiting for 13 jobs, finished 1 job
2025-11-01 01:28:41 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 12 = ∑12/20, waiting for 12 jobs
2025-11-01 01:28:43 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 12 = ∑12/20, new result: VAL_ACC: 70.420000
2025-11-01 01:28:43 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 12 = ∑12/20, new result: VAL_ACC: 70.700000
2025-11-01 01:28:43 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 12 = ∑12/20, new result: VAL_ACC: 70.230000
2025-11-01 01:29:10 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 9 = ∑9/20, waiting for 12 jobs, finished 3 jobs
2025-11-01 01:29:11 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 9 = ∑9/20, waiting for 9 jobs
2025-11-01 01:29:13 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 9 = ∑9/20, new result: VAL_ACC: 70.320000
2025-11-01 01:29:13 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 9 = ∑9/20, new result: VAL_ACC: 70.500000
2025-11-01 01:29:13 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 9 = ∑9/20, new result: VAL_ACC: 70.920000
2025-11-01 01:29:13 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 9 = ∑9/20, new result: VAL_ACC: 71.240000
2025-11-01 01:29:14 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.38, running 9 = ∑9/20, new result: VAL_ACC: 71.560000
2025-11-01 01:29:59 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 4 = ∑4/20, waiting for 9 jobs, finished 5 jobs
2025-11-01 01:29:59 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 4 = ∑4/20, waiting for 4 jobs
2025-11-01 01:30:01 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 4 = ∑4/20, new result: VAL_ACC: 70.620000
2025-11-01 01:30:01 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 4 = ∑4/20, new result: VAL_ACC: 70.990000
2025-11-01 01:30:01 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 4 = ∑4/20, new result: VAL_ACC: 70.700000
2025-11-01 01:30:03 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 4 = ∑4/20, new result: VAL_ACC: 70.810000
2025-11-01 01:30:37 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, waiting for 4 jobs, finished 4 jobs
2025-11-01 01:33:25 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #1/20
2025-11-01 01:33:25 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #2/20
2025-11-01 01:33:27 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #3/20
2025-11-01 01:33:27 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #4/20
2025-11-01 01:33:27 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #5/20
2025-11-01 01:33:27 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #6/20
2025-11-01 01:33:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #7/20
2025-11-01 01:33:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #8/20
2025-11-01 01:33:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #9/20
2025-11-01 01:33:29 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #10/20
2025-11-01 01:33:29 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #11/20
2025-11-01 01:33:29 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #12/20
2025-11-01 01:33:29 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #13/20
2025-11-01 01:33:30 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #14/20
2025-11-01 01:33:30 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #15/20
2025-11-01 01:33:30 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #16/20
2025-11-01 01:33:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #17/20
2025-11-01 01:33:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #18/20
2025-11-01 01:33:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #19/20
2025-11-01 01:33:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #20/20
2025-11-01 01:33:32 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, requested 20 jobs, got 20, 8.69 s/job
2025-11-01 01:33:34 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #1/20 start
2025-11-01 01:33:36 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #2/20 start
2025-11-01 01:33:37 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #3/20 start
2025-11-01 01:33:37 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #4/20 start
2025-11-01 01:33:38 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #5/20 start
2025-11-01 01:33:40 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #6/20 start
2025-11-01 01:33:41 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #7/20 start
2025-11-01 01:33:42 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #8/20 start
2025-11-01 01:33:43 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #9/20 start
2025-11-01 01:33:43 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #10/20 start
2025-11-01 01:33:45 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #11/20 start
2025-11-01 01:33:47 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #12/20 start
2025-11-01 01:33:48 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #13/20 start
2025-11-01 01:33:50 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #14/20 start
2025-11-01 01:33:52 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #15/20 start
2025-11-01 01:33:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #16/20 start
2025-11-01 01:33:56 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #17/20 start
2025-11-01 01:33:56 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #18/20 start
2025-11-01 01:33:58 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #19/20 start
2025-11-01 01:34:00 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #20/20 start
2025-11-01 01:34:07 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, starting new job
2025-11-01 01:34:09 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, pending 1 = ∑1/20, started new job
2025-11-01 01:34:09 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, pending 1 = ∑1/20, starting new job
2025-11-01 01:34:19 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 1/3 = ∑4/20, started new job
2025-11-01 01:34:20 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 1/3 = ∑4/20, starting new job
2025-11-01 01:34:20 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 1/3 = ∑4/20, starting new job
2025-11-01 01:34:23 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 4/2 = ∑6/20, started new job
2025-11-01 01:34:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending/unknown 4/2/1 = ∑7/20, started new job
2025-11-01 01:34:34 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending/unknown 4/3/1 = ∑8/20, started new job
2025-11-01 01:34:38 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 8/1 = ∑9/20, started new job
2025-11-01 01:34:48 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 9/1 = ∑10/20, started new job
2025-11-01 01:34:53 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending/unknown 9/1/1 = ∑11/20, started new job
2025-11-01 01:34:59 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending/unknown 9/2/3 = ∑14/20, started new job
2025-11-01 01:35:03 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 14/1 = ∑15/20, started new job
2025-11-01 01:35:08 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 15/1 = ∑16/20, started new job
2025-11-01 01:35:18 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending/unknown 15/1/1 = ∑17/20, started new job
2025-11-01 01:35:23 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 17/2 = ∑19/20, started new job
2025-11-01 01:35:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending/unknown 17/2/1 = ∑20/20, started new job
2025-11-01 01:35:30 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending/unknown 17/2/1 = ∑20/20, waiting for 20 jobs
2025-11-01 01:35:30 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 17/3 = ∑20/20, waiting for 20 jobs
2025-11-01 01:35:41 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 20 = ∑20/20, waiting for 20 jobs
2025-11-01 02:07:14 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 20 = ∑20/20, new result: VAL_ACC: 70.820000
2025-11-01 02:07:26 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 19 = ∑19/20, waiting for 20 jobs, finished 1 job
2025-11-01 02:07:27 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 19 = ∑19/20, waiting for 19 jobs
2025-11-01 02:08:23 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 19 = ∑19/20, new result: VAL_ACC: 71.310000
2025-11-01 02:08:36 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 18 = ∑18/20, waiting for 19 jobs, finished 1 job
2025-11-01 02:08:36 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 18 = ∑18/20, waiting for 18 jobs
2025-11-01 02:08:58 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 18 = ∑18/20, new result: VAL_ACC: 71.140000
2025-11-01 02:09:10 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 17 = ∑17/20, waiting for 18 jobs, finished 1 job
2025-11-01 02:09:10 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 17 = ∑17/20, waiting for 17 jobs
2025-11-01 02:09:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 17 = ∑17/20, new result: VAL_ACC: 70.830000
2025-11-01 02:10:07 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 16 = ∑16/20, waiting for 17 jobs, finished 1 job
2025-11-01 02:10:07 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 16 = ∑16/20, waiting for 16 jobs
2025-11-01 02:10:27 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 16 = ∑16/20, new result: VAL_ACC: 70.910000
2025-11-01 02:10:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 15 = ∑15/20, waiting for 16 jobs, finished 1 job
2025-11-01 02:10:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 15 = ∑15/20, waiting for 15 jobs
2025-11-01 02:11:36 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 15 = ∑15/20, new result: VAL_ACC: 70.620000
2025-11-01 02:11:49 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 14 = ∑14/20, waiting for 15 jobs, finished 1 job
2025-11-01 02:11:50 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 14 = ∑14/20, waiting for 14 jobs
2025-11-01 02:11:52 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 14 = ∑14/20, new result: VAL_ACC: 70.660000
2025-11-01 02:11:52 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 14 = ∑14/20, new result: VAL_ACC: 70.430000
2025-11-01 02:11:52 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 14 = ∑14/20, new result: VAL_ACC: 70.720000
2025-11-01 02:11:52 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 14 = ∑14/20, new result: VAL_ACC: 71.000000
2025-11-01 02:12:34 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 10 = ∑10/20, waiting for 14 jobs, finished 4 jobs
2025-11-01 02:12:34 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 10 = ∑10/20, waiting for 10 jobs
2025-11-01 02:12:36 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 10 = ∑10/20, new result: VAL_ACC: 70.760000
2025-11-01 02:12:36 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 10 = ∑10/20, new result: VAL_ACC: 70.770000
2025-11-01 02:12:36 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 10 = ∑10/20, new result: VAL_ACC: 70.950000
2025-11-01 02:13:05 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 7 = ∑7/20, waiting for 10 jobs, finished 3 jobs
2025-11-01 02:13:05 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 7 = ∑7/20, waiting for 7 jobs
2025-11-01 02:13:07 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 7 = ∑7/20, new result: VAL_ACC: 70.970000
2025-11-01 02:13:07 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 7 = ∑7/20, new result: VAL_ACC: 70.560000
2025-11-01 02:13:26 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 5 = ∑5/20, waiting for 7 jobs, finished 2 jobs
2025-11-01 02:13:27 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 5 = ∑5/20, waiting for 5 jobs
2025-11-01 02:13:29 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 5 = ∑5/20, new result: VAL_ACC: 71.050000
2025-11-01 02:13:29 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 5 = ∑5/20, new result: VAL_ACC: 70.590000
2025-11-01 02:13:29 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 5 = ∑5/20, new result: VAL_ACC: 71.120000
2025-11-01 02:13:30 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 5 = ∑5/20, new result: VAL_ACC: 71.070000
2025-11-01 02:13:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 5 = ∑5/20, new result: VAL_ACC: 71.330000
2025-11-01 02:14:19 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, waiting for 5 jobs, finished 5 jobs
2025-11-01 02:17:19 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #1/20
2025-11-01 02:17:20 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #2/20
2025-11-01 02:17:20 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #3/20
2025-11-01 02:17:20 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #4/20
2025-11-01 02:17:20 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #5/20
2025-11-01 02:17:21 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #6/20
2025-11-01 02:17:21 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #7/20
2025-11-01 02:17:21 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #8/20
2025-11-01 02:17:22 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #9/20
2025-11-01 02:17:22 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #10/20
2025-11-01 02:17:22 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #11/20
2025-11-01 02:17:22 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #12/20
2025-11-01 02:17:23 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #13/20
2025-11-01 02:17:23 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #14/20
2025-11-01 02:17:24 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #15/20
2025-11-01 02:17:26 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #16/20
2025-11-01 02:17:26 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #17/20
2025-11-01 02:17:26 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #18/20
2025-11-01 02:17:27 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #19/20
2025-11-01 02:17:27 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #20/20
2025-11-01 02:17:27 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, requested 20 jobs, got 20, 9.38 s/job
2025-11-01 02:17:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #1/20 start
2025-11-01 02:17:30 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #2/20 start
2025-11-01 02:17:32 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #3/20 start
2025-11-01 02:17:33 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #4/20 start
2025-11-01 02:17:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #5/20 start
2025-11-01 02:17:37 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #6/20 start
2025-11-01 02:17:38 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #7/20 start
2025-11-01 02:17:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #8/20 start
2025-11-01 02:17:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #9/20 start
2025-11-01 02:17:40 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #10/20 start
2025-11-01 02:17:42 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #11/20 start
2025-11-01 02:17:43 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #12/20 start
2025-11-01 02:17:45 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #13/20 start
2025-11-01 02:17:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #14/20 start
2025-11-01 02:17:47 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #15/20 start
2025-11-01 02:17:48 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #16/20 start
2025-11-01 02:17:50 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #17/20 start
2025-11-01 02:17:50 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #18/20 start
2025-11-01 02:17:51 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #19/20 start
2025-11-01 02:17:52 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #20/20 start
2025-11-01 02:17:59 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, starting new job
2025-11-01 02:18:02 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 2 = ∑2/20, started new job
2025-11-01 02:18:03 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 2 = ∑2/20, starting new job
2025-11-01 02:18:11 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 2/2 = ∑4/20, started new job
2025-11-01 02:18:12 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 2/2 = ∑4/20, starting new job
2025-11-01 02:18:16 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending/unknown 2/2/3 = ∑7/20, started new job
2025-11-01 02:18:20 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 7/1 = ∑8/20, started new job
2025-11-01 02:18:30 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending/unknown 7/1/1 = ∑9/20, started new job
2025-11-01 02:18:36 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending/unknown 7/2/2 = ∑11/20, started new job
2025-11-01 02:18:40 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 11/1 = ∑12/20, started new job
2025-11-01 02:18:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending/unknown 11/1/2 = ∑14/20, started new job
2025-11-01 02:18:50 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending/unknown 11/3/1 = ∑15/20, started new job
2025-11-01 02:18:56 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending/unknown 11/4/2 = ∑17/20, started new job
2025-11-01 02:19:00 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 17/1 = ∑18/20, started new job
2025-11-01 02:19:10 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 18/1 = ∑19/20, started new job
2025-11-01 02:19:20 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 19/1 = ∑20/20, started new job
2025-11-01 02:19:22 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 19/1 = ∑20/20, waiting for 20 jobs
2025-11-01 02:19:23 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 19/1 = ∑20/20, waiting for 20 jobs
2025-11-01 02:19:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 20 = ∑20/20, waiting for 20 jobs
2025-11-01 02:37:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 20 = ∑20/20, new result: VAL_ACC: 70.110000
2025-11-01 02:37:53 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 19 = ∑19/20, waiting for 20 jobs, finished 1 job
2025-11-01 02:37:53 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 19 = ∑19/20, waiting for 19 jobs
2025-11-01 02:38:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 19 = ∑19/20, new result: VAL_ACC: 69.560000
2025-11-01 02:38:49 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 18 = ∑18/20, waiting for 19 jobs, finished 1 job
2025-11-01 02:38:49 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 18 = ∑18/20, waiting for 18 jobs
2025-11-01 02:39:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 18 = ∑18/20, new result: VAL_ACC: 69.760000
2025-11-01 02:39:59 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 17 = ∑17/20, waiting for 18 jobs, finished 1 job
2025-11-01 02:39:59 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 17 = ∑17/20, waiting for 17 jobs
2025-11-01 02:40:59 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 17 = ∑17/20, new result: VAL_ACC: 70.220000
2025-11-01 02:41:13 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 16 = ∑16/20, waiting for 17 jobs, finished 1 job
2025-11-01 02:41:13 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 16 = ∑16/20, waiting for 16 jobs
2025-11-01 02:41:14 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 16 = ∑16/20, new result: VAL_ACC: 70.680000
2025-11-01 02:41:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 15 = ∑15/20, waiting for 16 jobs, finished 1 job
2025-11-01 02:41:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 15 = ∑15/20, waiting for 15 jobs
2025-11-01 02:53:40 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 15 = ∑15/20, new result: VAL_ACC: 69.200000
2025-11-01 02:53:54 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 14 = ∑14/20, waiting for 15 jobs, finished 1 job
2025-11-01 02:53:54 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 14 = ∑14/20, waiting for 14 jobs
2025-11-01 02:54:21 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 14 = ∑14/20, new result: VAL_ACC: 69.390000
2025-11-01 02:54:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 13 = ∑13/20, waiting for 14 jobs, finished 1 job
2025-11-01 02:54:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 13 = ∑13/20, waiting for 13 jobs
2025-11-01 02:55:29 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 13 = ∑13/20, new result: VAL_ACC: 69.250000
2025-11-01 02:55:42 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 12 = ∑12/20, waiting for 13 jobs, finished 1 job
2025-11-01 02:55:43 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 12 = ∑12/20, waiting for 12 jobs
2025-11-01 02:55:44 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 12 = ∑12/20, new result: VAL_ACC: 69.340000
2025-11-01 02:55:57 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 11 = ∑11/20, waiting for 12 jobs, finished 1 job
2025-11-01 02:55:58 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 11 = ∑11/20, waiting for 11 jobs
2025-11-01 02:56:24 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 11 = ∑11/20, new result: VAL_ACC: 69.720000
2025-11-01 02:56:38 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 10 = ∑10/20, waiting for 11 jobs, finished 1 job
2025-11-01 02:56:38 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 10 = ∑10/20, waiting for 10 jobs
2025-11-01 02:56:40 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 10 = ∑10/20, new result: VAL_ACC: 69.250000
2025-11-01 02:56:40 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 10 = ∑10/20, new result: VAL_ACC: 69.110000
2025-11-01 02:57:00 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 8 = ∑8/20, waiting for 10 jobs, finished 2 jobs
2025-11-01 02:57:00 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 8 = ∑8/20, waiting for 8 jobs
2025-11-01 02:57:41 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 8 = ∑8/20, new result: VAL_ACC: 69.480000
2025-11-01 02:57:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 7 = ∑7/20, waiting for 8 jobs, finished 1 job
2025-11-01 02:57:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 7 = ∑7/20, waiting for 7 jobs
2025-11-01 03:05:22 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 7 = ∑7/20, new result: VAL_ACC: 60.320000
2025-11-01 03:05:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 6 = ∑6/20, waiting for 7 jobs, finished 1 job
2025-11-01 03:05:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 6 = ∑6/20, waiting for 6 jobs
2025-11-01 03:08:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 6 = ∑6/20, new result: VAL_ACC: 60.520000
2025-11-01 03:08:45 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 5 = ∑5/20, waiting for 6 jobs, finished 1 job
2025-11-01 03:08:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 5 = ∑5/20, waiting for 5 jobs
2025-11-01 03:08:47 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 5 = ∑5/20, new result: VAL_ACC: 69.570000
2025-11-01 03:09:02 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 4 = ∑4/20, waiting for 5 jobs, finished 1 job
2025-11-01 03:09:02 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 4 = ∑4/20, waiting for 4 jobs
2025-11-01 03:09:29 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 4 = ∑4/20, new result: VAL_ACC: 70.140000
2025-11-01 03:09:43 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 3 = ∑3/20, waiting for 4 jobs, finished 1 job
2025-11-01 03:09:43 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 3 = ∑3/20, waiting for 3 jobs
2025-11-01 03:11:36 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 3 = ∑3/20, new result: VAL_ACC: 69.540000
2025-11-01 03:11:50 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 2 = ∑2/20, waiting for 3 jobs, finished 1 job
2025-11-01 03:11:50 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 2 = ∑2/20, waiting for 2 jobs
2025-11-01 03:13:30 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 2 = ∑2/20, new result: VAL_ACC: 69.410000
2025-11-01 03:13:44 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 1 = ∑1/20, waiting for 2 jobs, finished 1 job
2025-11-01 03:13:44 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 1 = ∑1/20, waiting for 1 job
2025-11-01 03:14:26 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 1 = ∑1/20, new result: VAL_ACC: 69.920000
2025-11-01 03:14:41 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, waiting for 1 job, finished 1 job
2025-11-01 03:17:00 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #1/20
2025-11-01 03:17:01 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #2/20
2025-11-01 03:17:02 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #3/20
2025-11-01 03:17:02 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #4/20
2025-11-01 03:17:03 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #5/20
2025-11-01 03:17:03 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #6/20
2025-11-01 03:17:03 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #7/20
2025-11-01 03:17:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #8/20
2025-11-01 03:17:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #9/20
2025-11-01 03:17:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #10/20
2025-11-01 03:17:05 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #11/20
2025-11-01 03:17:05 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #12/20
2025-11-01 03:17:05 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #13/20
2025-11-01 03:17:05 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #14/20
2025-11-01 03:17:06 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #15/20
2025-11-01 03:17:06 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #16/20
2025-11-01 03:17:06 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #17/20
2025-11-01 03:17:08 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #18/20
2025-11-01 03:17:08 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #19/20
2025-11-01 03:17:08 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #20/20
2025-11-01 03:17:09 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, requested 20 jobs, got 20, 7.33 s/job
2025-11-01 03:17:10 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #1/20 start
2025-11-01 03:17:12 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #2/20 start
2025-11-01 03:17:14 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #3/20 start
2025-11-01 03:17:16 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #4/20 start
2025-11-01 03:17:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #5/20 start
2025-11-01 03:17:18 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #6/20 start
2025-11-01 03:17:20 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #7/20 start
2025-11-01 03:17:21 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #8/20 start
2025-11-01 03:17:22 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #9/20 start
2025-11-01 03:17:23 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #10/20 start
2025-11-01 03:17:24 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #11/20 start
2025-11-01 03:17:25 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #12/20 start
2025-11-01 03:17:26 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #13/20 start
2025-11-01 03:17:27 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #14/20 start
2025-11-01 03:17:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #15/20 start
2025-11-01 03:17:29 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #16/20 start
2025-11-01 03:17:30 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #17/20 start
2025-11-01 03:17:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #18/20 start
2025-11-01 03:17:33 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #19/20 start
2025-11-01 03:17:34 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #20/20 start
2025-11-01 03:17:41 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, starting new job
2025-11-01 03:17:43 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 1 = ∑1/20, started new job
2025-11-01 03:17:44 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 1 = ∑1/20, starting new job
2025-11-01 03:17:47 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 1/1 = ∑2/20, started new job
2025-11-01 03:17:48 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 1/1 = ∑2/20, starting new job
2025-11-01 03:17:53 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending/unknown 1/1/2 = ∑4/20, started new job
2025-11-01 03:17:54 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending/unknown 1/1/2 = ∑4/20, starting new job
2025-11-01 03:17:58 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending/unknown 1/3/3 = ∑7/20, started new job
2025-11-01 03:18:02 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 7/1 = ∑8/20, started new job
2025-11-01 03:18:07 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending/unknown 7/1/1 = ∑9/20, started new job
2025-11-01 03:18:12 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 9/1 = ∑10/20, started new job
2025-11-01 03:18:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending/unknown 9/1/1 = ∑11/20, started new job
2025-11-01 03:18:18 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending/unknown 9/1/2 = ∑12/20, started new job
2025-11-01 03:18:22 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 12/1 = ∑13/20, started new job
2025-11-01 03:18:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 12/2 = ∑14/20, started new job
2025-11-01 03:18:32 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending/unknown 12/2/1 = ∑15/20, started new job
2025-11-01 03:18:38 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending/unknown 12/3/2 = ∑17/20, started new job
2025-11-01 03:18:38 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending/unknown 12/3/3 = ∑18/20, started new job
2025-11-01 03:18:43 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 18/2 = ∑20/20, started new job
2025-11-01 03:18:45 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 18/2 = ∑20/20, waiting for 20 jobs
2025-11-01 03:19:20 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 20 = ∑20/20, waiting for 20 jobs
2025-11-01 03:54:32 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 20 = ∑20/20, new result: VAL_ACC: 70.520000
2025-11-01 03:54:47 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 19 = ∑19/20, waiting for 20 jobs, finished 1 job
2025-11-01 03:54:48 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 19 = ∑19/20, waiting for 19 jobs
2025-11-01 03:55:48 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 19 = ∑19/20, new result: VAL_ACC: 70.630000
2025-11-01 03:56:03 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 18 = ∑18/20, waiting for 19 jobs, finished 1 job
2025-11-01 03:56:03 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 18 = ∑18/20, waiting for 18 jobs
2025-11-01 03:56:06 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 18 = ∑18/20, new result: VAL_ACC: 70.860000
2025-11-01 03:56:06 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 18 = ∑18/20, new result: VAL_ACC: 70.140000
2025-11-01 03:56:06 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 18 = ∑18/20, new result: VAL_ACC: 70.500000
2025-11-01 03:56:06 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 18 = ∑18/20, new result: VAL_ACC: 70.450000
2025-11-01 03:56:50 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 14 = ∑14/20, waiting for 18 jobs, finished 4 jobs
2025-11-01 03:56:51 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 14 = ∑14/20, waiting for 14 jobs
2025-11-01 03:56:54 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 14 = ∑14/20, new result: VAL_ACC: 70.190000
2025-11-01 03:56:54 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 14 = ∑14/20, new result: VAL_ACC: 70.380000
2025-11-01 03:56:54 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 14 = ∑14/20, new result: VAL_ACC: 70.610000
2025-11-01 03:56:54 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 14 = ∑14/20, new result: VAL_ACC: 70.700000
2025-11-01 03:56:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 14 = ∑14/20, new result: VAL_ACC: 70.190000
2025-11-01 03:56:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 14 = ∑14/20, new result: VAL_ACC: 70.380000
2025-11-01 03:58:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 8 = ∑8/20, waiting for 14 jobs, finished 6 jobs
2025-11-01 03:58:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 8 = ∑8/20, waiting for 8 jobs
2025-11-01 03:58:08 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 8 = ∑8/20, new result: VAL_ACC: 70.610000
2025-11-01 03:58:08 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 8 = ∑8/20, new result: VAL_ACC: 70.670000
2025-11-01 03:58:08 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 8 = ∑8/20, new result: VAL_ACC: 70.500000
2025-11-01 03:58:08 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 8 = ∑8/20, new result: VAL_ACC: 70.480000
2025-11-01 03:58:08 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 8 = ∑8/20, new result: VAL_ACC: 70.340000
2025-11-01 03:58:09 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 8 = ∑8/20, new result: VAL_ACC: 70.190000
2025-11-01 03:59:15 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 2 = ∑2/20, waiting for 8 jobs, finished 6 jobs
2025-11-01 03:59:15 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 2 = ∑2/20, waiting for 2 jobs
2025-11-01 04:00:19 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 2 = ∑2/20, new result: VAL_ACC: 70.380000
2025-11-01 04:00:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 1 = ∑1/20, waiting for 2 jobs, finished 1 job
2025-11-01 04:00:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 1 = ∑1/20, waiting for 1 job
2025-11-01 04:00:41 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 1 = ∑1/20, new result: VAL_ACC: 70.180000
2025-11-01 04:00:57 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, waiting for 1 job, finished 1 job
2025-11-01 04:03:38 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #1/20
2025-11-01 04:03:38 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #2/20
2025-11-01 04:03:38 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #3/20
2025-11-01 04:03:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #4/20
2025-11-01 04:03:40 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #5/20
2025-11-01 04:03:40 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #6/20
2025-11-01 04:03:42 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #7/20
2025-11-01 04:03:42 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #8/20
2025-11-01 04:03:43 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #9/20
2025-11-01 04:03:43 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #10/20
2025-11-01 04:03:44 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #11/20
2025-11-01 04:03:45 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #12/20
2025-11-01 04:03:45 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #13/20
2025-11-01 04:03:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #14/20
2025-11-01 04:03:47 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #15/20
2025-11-01 04:03:47 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #16/20
2025-11-01 04:03:47 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #17/20
2025-11-01 04:03:48 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #18/20
2025-11-01 04:03:48 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #19/20
2025-11-01 04:03:48 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #20/20
2025-11-01 04:03:48 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, requested 20 jobs, got 20, 8.52 s/job
2025-11-01 04:03:50 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #1/20 start
2025-11-01 04:03:51 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #2/20 start
2025-11-01 04:03:53 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #3/20 start
2025-11-01 04:03:54 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #4/20 start
2025-11-01 04:03:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #5/20 start
2025-11-01 04:03:57 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #6/20 start
2025-11-01 04:03:57 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #7/20 start
2025-11-01 04:04:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #8/20 start
2025-11-01 04:04:10 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #9/20 start
2025-11-01 04:04:12 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #10/20 start
2025-11-01 04:04:14 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #11/20 start
2025-11-01 04:04:16 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #12/20 start
2025-11-01 04:04:18 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #13/20 start
2025-11-01 04:04:20 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #14/20 start
2025-11-01 04:04:21 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #15/20 start
2025-11-01 04:04:22 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #16/20 start
2025-11-01 04:04:23 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #17/20 start
2025-11-01 04:04:24 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #18/20 start
2025-11-01 04:04:26 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #19/20 start
2025-11-01 04:04:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #20/20 start
2025-11-01 04:04:36 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, starting new job
2025-11-01 04:04:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, pending 3 = ∑3/20, started new job
2025-11-01 04:04:41 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 3 = ∑3/20, starting new job
2025-11-01 04:04:43 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 3/1 = ∑4/20, started new job
2025-11-01 04:04:44 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 3/1 = ∑4/20, starting new job
2025-11-01 04:04:48 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending/unknown 3/1/2 = ∑6/20, started new job
2025-11-01 04:04:54 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending/unknown 3/3/3 = ∑9/20, started new job
2025-11-01 04:04:59 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 9/3 = ∑12/20, started new job
2025-11-01 04:05:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 12/3 = ∑15/20, started new job
2025-11-01 04:05:09 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 15/3 = ∑18/20, started new job
2025-11-01 04:05:14 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 18/2 = ∑20/20, started new job
2025-11-01 04:05:15 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 18/2 = ∑20/20, waiting for 20 jobs
2025-11-01 04:05:18 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 20 = ∑20/20, waiting for 20 jobs
2025-11-01 04:28:56 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 20 = ∑20/20, new result: VAL_ACC: 68.720000
2025-11-01 04:29:13 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 19 = ∑19/20, waiting for 20 jobs, finished 1 job
2025-11-01 04:29:13 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 19 = ∑19/20, waiting for 19 jobs
2025-11-01 04:39:03 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 19 = ∑19/20, new result: VAL_ACC: 69.170000
2025-11-01 04:39:19 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 18 = ∑18/20, waiting for 19 jobs, finished 1 job
2025-11-01 04:39:20 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 18 = ∑18/20, waiting for 18 jobs
2025-11-01 04:40:24 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 18 = ∑18/20, new result: VAL_ACC: 68.800000
2025-11-01 04:40:41 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 17 = ∑17/20, waiting for 18 jobs, finished 1 job
2025-11-01 04:40:41 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 17 = ∑17/20, waiting for 17 jobs
2025-11-01 04:40:47 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 17 = ∑17/20, new result: VAL_ACC: 69.080000
2025-11-01 04:41:03 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 16 = ∑16/20, waiting for 17 jobs, finished 1 job
2025-11-01 04:41:03 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 16 = ∑16/20, waiting for 16 jobs
2025-11-01 04:41:52 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 16 = ∑16/20, new result: VAL_ACC: 69.310000
2025-11-01 04:42:09 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 15 = ∑15/20, waiting for 16 jobs, finished 1 job
2025-11-01 04:42:09 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 15 = ∑15/20, waiting for 15 jobs
2025-11-01 04:42:10 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 15 = ∑15/20, new result: VAL_ACC: 69.440000
2025-11-01 04:42:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 14 = ∑14/20, waiting for 15 jobs, finished 1 job
2025-11-01 04:42:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 14 = ∑14/20, waiting for 14 jobs
2025-11-01 04:42:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 14 = ∑14/20, new result: VAL_ACC: 69.450000
2025-11-01 04:42:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 14 = ∑14/20, new result: VAL_ACC: 70.300000
2025-11-01 04:42:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 14 = ∑14/20, new result: VAL_ACC: 69.310000
2025-11-01 04:42:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 14 = ∑14/20, new result: VAL_ACC: 69.170000
2025-11-01 04:43:18 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 10 = ∑10/20, waiting for 14 jobs, finished 4 jobs
2025-11-01 04:43:18 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 10 = ∑10/20, waiting for 10 jobs
2025-11-01 04:43:22 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 10 = ∑10/20, new result: VAL_ACC: 69.510000
2025-11-01 04:43:22 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 10 = ∑10/20, new result: VAL_ACC: 68.950000
2025-11-01 04:43:22 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 10 = ∑10/20, new result: VAL_ACC: 69.470000
2025-11-01 04:43:22 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 10 = ∑10/20, new result: VAL_ACC: 69.080000
2025-11-01 04:43:22 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 10 = ∑10/20, new result: VAL_ACC: 69.300000
2025-11-01 04:43:23 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 10 = ∑10/20, new result: VAL_ACC: 69.020000
2025-11-01 04:44:34 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 4 = ∑4/20, waiting for 10 jobs, finished 6 jobs
2025-11-01 04:44:34 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 4 = ∑4/20, waiting for 4 jobs
2025-11-01 04:44:36 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 4 = ∑4/20, new result: VAL_ACC: 69.290000
2025-11-01 04:44:36 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 4 = ∑4/20, new result: VAL_ACC: 69.640000
2025-11-01 04:45:08 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 2 = ∑2/20, waiting for 4 jobs, finished 2 jobs
2025-11-01 04:45:08 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 2 = ∑2/20, waiting for 2 jobs
2025-11-01 04:46:09 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 2 = ∑2/20, new result: VAL_ACC: 69.570000
2025-11-01 04:46:27 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 1 = ∑1/20, waiting for 2 jobs, finished 1 job
2025-11-01 04:46:27 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 1 = ∑1/20, waiting for 1 job
2025-11-01 05:02:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 1 = ∑1/20, new result: VAL_ACC: 69.120000
2025-11-01 05:02:34 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, waiting for 1 job, finished 1 job
2025-11-01 05:05:56 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #1/20
2025-11-01 05:05:58 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #2/20
2025-11-01 05:05:58 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #3/20
2025-11-01 05:05:58 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #4/20
2025-11-01 05:05:59 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #5/20
2025-11-01 05:05:59 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #6/20
2025-11-01 05:05:59 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #7/20
2025-11-01 05:06:00 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #8/20
2025-11-01 05:06:00 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #9/20
2025-11-01 05:06:00 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #10/20
2025-11-01 05:06:01 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #11/20
2025-11-01 05:06:01 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #12/20
2025-11-01 05:06:02 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #13/20
2025-11-01 05:06:02 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #14/20
2025-11-01 05:06:02 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #15/20
2025-11-01 05:06:03 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #16/20
2025-11-01 05:06:03 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #17/20
2025-11-01 05:06:03 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #18/20
2025-11-01 05:06:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #19/20
2025-11-01 05:06:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #20/20
2025-11-01 05:06:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, requested 20 jobs, got 20, 10.40 s/job
2025-11-01 05:06:07 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #1/20 start
2025-11-01 05:06:09 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #2/20 start
2025-11-01 05:06:10 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #3/20 start
2025-11-01 05:06:11 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #4/20 start
2025-11-01 05:06:12 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #5/20 start
2025-11-01 05:06:13 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #6/20 start
2025-11-01 05:06:14 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #7/20 start
2025-11-01 05:06:15 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #8/20 start
2025-11-01 05:06:16 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #9/20 start
2025-11-01 05:06:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #10/20 start
2025-11-01 05:06:18 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #11/20 start
2025-11-01 05:06:19 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #12/20 start
2025-11-01 05:06:21 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #13/20 start
2025-11-01 05:06:22 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #14/20 start
2025-11-01 05:06:23 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #15/20 start
2025-11-01 05:06:25 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #16/20 start
2025-11-01 05:06:27 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #17/20 start
2025-11-01 05:06:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #18/20 start
2025-11-01 05:06:29 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #19/20 start
2025-11-01 05:06:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #20/20 start
2025-11-01 05:06:43 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, starting new job
2025-11-01 05:06:47 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 3 = ∑3/20, starting new job
2025-11-01 05:06:47 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 3 = ∑3/20, started new job
2025-11-01 05:06:49 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 3 = ∑3/20, starting new job
2025-11-01 05:06:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 3/1 = ∑4/20, started new job
2025-11-01 05:06:56 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 3/1 = ∑4/20, starting new job
2025-11-01 05:07:06 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 4/1 = ∑5/20, started new job
2025-11-01 05:07:16 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 5/2 = ∑7/20, started new job
2025-11-01 05:07:21 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending/unknown 5/2/3 = ∑10/20, started new job
2025-11-01 05:07:25 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 10/1 = ∑11/20, started new job
2025-11-01 05:07:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending/unknown 10/1/1 = ∑12/20, started new job
2025-11-01 05:07:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 12/2 = ∑14/20, started new job
2025-11-01 05:07:51 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending/unknown 12/2/2 = ∑16/20, started new job
2025-11-01 05:07:56 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending/unknown 12/4/3 = ∑19/20, started new job
2025-11-01 05:08:00 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending/unknown 12/7/1 = ∑20/20, started new job
2025-11-01 05:08:02 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending/unknown 12/7/1 = ∑20/20, waiting for 20 jobs
2025-11-01 05:08:03 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 12/8 = ∑20/20, waiting for 20 jobs
2025-11-01 05:08:06 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 20 = ∑20/20, waiting for 20 jobs
2025-11-01 05:30:06 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 20 = ∑20/20, new result: VAL_ACC: 68.200000
2025-11-01 05:30:25 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 19 = ∑19/20, waiting for 20 jobs, finished 1 job
2025-11-01 05:30:25 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 19 = ∑19/20, waiting for 19 jobs
2025-11-01 05:33:16 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 19 = ∑19/20, new result: VAL_ACC: 68.410000
2025-11-01 05:33:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 18 = ∑18/20, waiting for 19 jobs, finished 1 job
2025-11-01 05:33:36 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 18 = ∑18/20, waiting for 18 jobs
2025-11-01 05:33:37 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 18 = ∑18/20, new result: VAL_ACC: 67.900000
2025-11-01 05:33:57 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 17 = ∑17/20, waiting for 18 jobs, finished 1 job
2025-11-01 05:33:58 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 17 = ∑17/20, waiting for 17 jobs
2025-11-01 05:35:32 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 17 = ∑17/20, new result: VAL_ACC: 69.460000
2025-11-01 05:35:54 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 16 = ∑16/20, waiting for 17 jobs, finished 1 job
2025-11-01 05:35:54 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 16 = ∑16/20, waiting for 16 jobs
2025-11-01 05:35:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 16 = ∑16/20, new result: VAL_ACC: 69.370000
2025-11-01 05:36:14 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 15 = ∑15/20, waiting for 16 jobs, finished 1 job
2025-11-01 05:36:14 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 15 = ∑15/20, waiting for 15 jobs
2025-11-01 05:36:16 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 15 = ∑15/20, new result: VAL_ACC: 68.790000
2025-11-01 05:36:34 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 14 = ∑14/20, waiting for 15 jobs, finished 1 job
2025-11-01 05:36:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 14 = ∑14/20, waiting for 14 jobs
2025-11-01 05:37:09 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 14 = ∑14/20, new result: VAL_ACC: 68.980000
2025-11-01 05:37:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 13 = ∑13/20, waiting for 14 jobs, finished 1 job
2025-11-01 05:37:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 13 = ∑13/20, waiting for 13 jobs
2025-11-01 05:37:54 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 13 = ∑13/20, new result: VAL_ACC: 69.660000
2025-11-01 05:38:13 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 12 = ∑12/20, waiting for 13 jobs, finished 1 job
2025-11-01 05:38:14 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 12 = ∑12/20, waiting for 12 jobs
2025-11-01 05:38:15 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 12 = ∑12/20, new result: VAL_ACC: 69.290000
2025-11-01 05:38:33 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 11 = ∑11/20, waiting for 12 jobs, finished 1 job
2025-11-01 05:38:34 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 11 = ∑11/20, waiting for 11 jobs
2025-11-01 05:39:08 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 11 = ∑11/20, new result: VAL_ACC: 69.650000
2025-11-01 05:39:26 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 10 = ∑10/20, waiting for 11 jobs, finished 1 job
2025-11-01 05:39:26 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 10 = ∑10/20, waiting for 10 jobs
2025-11-01 05:39:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 10 = ∑10/20, new result: VAL_ACC: 69.200000
2025-11-01 05:39:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 9 = ∑9/20, waiting for 10 jobs, finished 1 job
2025-11-01 05:39:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 9 = ∑9/20, waiting for 9 jobs
2025-11-01 05:47:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 9 = ∑9/20, new result: VAL_ACC: 71.150000
2025-11-01 05:47:24 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 8 = ∑8/20, waiting for 9 jobs, finished 1 job
2025-11-01 05:47:24 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 8 = ∑8/20, waiting for 8 jobs
2025-11-01 05:48:07 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 8 = ∑8/20, new result: VAL_ACC: 71.410000
2025-11-01 05:48:27 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 7 = ∑7/20, waiting for 8 jobs, finished 1 job
2025-11-01 05:48:27 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 7 = ∑7/20, waiting for 7 jobs
2025-11-01 05:48:40 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 7 = ∑7/20, new result: VAL_ACC: 70.840000
2025-11-01 05:48:58 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 6 = ∑6/20, waiting for 7 jobs, finished 1 job
2025-11-01 05:48:58 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 6 = ∑6/20, waiting for 6 jobs
2025-11-01 05:48:59 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 6 = ∑6/20, new result: VAL_ACC: 70.830000
2025-11-01 05:49:18 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 5 = ∑5/20, waiting for 6 jobs, finished 1 job
2025-11-01 05:49:19 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 5 = ∑5/20, waiting for 5 jobs
2025-11-01 05:49:20 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 5 = ∑5/20, new result: VAL_ACC: 70.830000
2025-11-01 05:49:20 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 5 = ∑5/20, new result: VAL_ACC: 70.970000
2025-11-01 05:49:47 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 3 = ∑3/20, waiting for 5 jobs, finished 2 jobs
2025-11-01 05:49:48 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 3 = ∑3/20, waiting for 3 jobs
2025-11-01 05:49:49 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 3 = ∑3/20, new result: VAL_ACC: 71.360000
2025-11-01 05:50:07 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 2 = ∑2/20, waiting for 3 jobs, finished 1 job
2025-11-01 05:50:07 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 2 = ∑2/20, waiting for 2 jobs
2025-11-01 05:50:09 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 2 = ∑2/20, new result: VAL_ACC: 70.600000
2025-11-01 05:50:09 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 2 = ∑2/20, new result: VAL_ACC: 70.540000
2025-11-01 05:50:38 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, waiting for 2 jobs, finished 2 jobs
2025-11-01 05:54:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #1/20
2025-11-01 05:54:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #2/20
2025-11-01 05:54:29 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #3/20
2025-11-01 05:54:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #4/20
2025-11-01 05:54:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #5/20
2025-11-01 05:54:32 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #6/20
2025-11-01 05:54:37 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #7/20
2025-11-01 05:54:37 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #8/20
2025-11-01 05:54:38 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #9/20
2025-11-01 05:54:38 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #10/20
2025-11-01 05:54:38 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #11/20
2025-11-01 05:54:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #12/20
2025-11-01 05:54:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #13/20
2025-11-01 05:54:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #14/20
2025-11-01 05:54:40 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #15/20
2025-11-01 05:54:40 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #16/20
2025-11-01 05:54:40 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #17/20
2025-11-01 05:54:41 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #18/20
2025-11-01 05:54:41 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #19/20
2025-11-01 05:54:41 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #20/20
2025-11-01 05:54:42 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, requested 20 jobs, got 20, 12.15 s/job
2025-11-01 05:54:43 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #1/20 start
2025-11-01 05:54:44 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #2/20 start
2025-11-01 05:54:45 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #3/20 start
2025-11-01 05:54:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #4/20 start
2025-11-01 05:54:47 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #5/20 start
2025-11-01 05:54:49 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #6/20 start
2025-11-01 05:54:50 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #7/20 start
2025-11-01 05:54:51 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #8/20 start
2025-11-01 05:54:52 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #9/20 start
2025-11-01 05:54:54 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #10/20 start
2025-11-01 05:54:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #11/20 start
2025-11-01 05:54:56 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #12/20 start
2025-11-01 05:54:57 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #13/20 start
2025-11-01 05:54:58 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #14/20 start
2025-11-01 05:54:59 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #15/20 start
2025-11-01 05:55:00 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #16/20 start
2025-11-01 05:55:02 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #17/20 start
2025-11-01 05:55:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #18/20 start
2025-11-01 05:55:05 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #19/20 start
2025-11-01 05:55:06 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #20/20 start
2025-11-01 05:55:15 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, starting new job
2025-11-01 05:55:18 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 3 = ∑3/20, started new job
2025-11-01 05:55:20 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 3 = ∑3/20, starting new job
2025-11-01 05:55:26 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 3/1 = ∑4/20, started new job
2025-11-01 05:55:27 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 3/1 = ∑4/20, starting new job
2025-11-01 05:55:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending/unknown 3/1/1 = ∑5/20, started new job
2025-11-01 05:55:36 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 5/1 = ∑6/20, started new job
2025-11-01 05:55:41 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 6/1 = ∑7/20, started new job
2025-11-01 05:55:47 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending/unknown 6/1/2 = ∑9/20, started new job
2025-11-01 05:55:53 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending/unknown 6/3/3 = ∑12/20, started new job
2025-11-01 05:55:56 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 12/1 = ∑13/20, started new job
2025-11-01 05:56:01 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending/unknown 12/1/1 = ∑14/20, started new job
2025-11-01 05:56:06 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending/unknown 12/2/1 = ∑15/20, started new job
2025-11-01 05:56:11 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 15/1 = ∑16/20, started new job
2025-11-01 05:56:16 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 16/1 = ∑17/20, started new job
2025-11-01 05:56:21 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending/unknown 16/1/1 = ∑18/20, started new job
2025-11-01 05:56:27 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending/unknown 16/2/2 = ∑20/20, started new job
2025-11-01 05:56:29 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 16/4 = ∑20/20, waiting for 20 jobs
2025-11-01 05:56:38 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 20 = ∑20/20, waiting for 20 jobs
2025-11-01 06:25:07 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 20 = ∑20/20, new result: VAL_ACC: 70.250000
2025-11-01 06:25:30 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 19 = ∑19/20, waiting for 20 jobs, finished 1 job
2025-11-01 06:25:30 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 19 = ∑19/20, waiting for 19 jobs
2025-11-01 06:29:18 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 19 = ∑19/20, new result: VAL_ACC: 70.570000
2025-11-01 06:29:40 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 18 = ∑18/20, waiting for 19 jobs, finished 1 job
2025-11-01 06:29:40 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 18 = ∑18/20, waiting for 18 jobs
2025-11-01 06:29:41 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 18 = ∑18/20, new result: VAL_ACC: 70.780000
2025-11-01 06:30:01 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 17 = ∑17/20, waiting for 18 jobs, finished 1 job
2025-11-01 06:30:02 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 17 = ∑17/20, waiting for 17 jobs
2025-11-01 06:35:32 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 17 = ∑17/20, new result: VAL_ACC: 70.950000
2025-11-01 06:35:52 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 16 = ∑16/20, waiting for 17 jobs, finished 1 job
2025-11-01 06:35:53 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 16 = ∑16/20, waiting for 16 jobs
2025-11-01 06:36:03 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 16 = ∑16/20, new result: VAL_ACC: 68.540000
2025-11-01 06:36:22 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 15 = ∑15/20, waiting for 16 jobs, finished 1 job
2025-11-01 06:36:22 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 15 = ∑15/20, waiting for 15 jobs
2025-11-01 06:36:27 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 15 = ∑15/20, new result: VAL_ACC: 68.650000
2025-11-01 06:36:48 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 14 = ∑14/20, waiting for 15 jobs, finished 1 job
2025-11-01 06:36:48 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 14 = ∑14/20, waiting for 14 jobs
2025-11-01 06:36:49 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 14 = ∑14/20, new result: VAL_ACC: 69.250000
2025-11-01 06:37:09 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 13 = ∑13/20, waiting for 14 jobs, finished 1 job
2025-11-01 06:37:09 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 13 = ∑13/20, waiting for 13 jobs
2025-11-01 06:37:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 13 = ∑13/20, new result: VAL_ACC: 70.290000
2025-11-01 06:37:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 12 = ∑12/20, waiting for 13 jobs, finished 1 job
2025-11-01 06:37:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 12 = ∑12/20, waiting for 12 jobs
2025-11-01 06:37:48 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 12 = ∑12/20, new result: VAL_ACC: 70.960000
2025-11-01 06:38:07 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 11 = ∑11/20, waiting for 12 jobs, finished 1 job
2025-11-01 06:38:07 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 11 = ∑11/20, waiting for 11 jobs
2025-11-01 06:41:33 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 11 = ∑11/20, new result: VAL_ACC: 70.990000
2025-11-01 06:41:52 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 10 = ∑10/20, waiting for 11 jobs, finished 1 job
2025-11-01 06:41:52 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 10 = ∑10/20, waiting for 10 jobs
2025-11-01 06:44:40 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 10 = ∑10/20, new result: VAL_ACC: 68.510000
2025-11-01 06:45:01 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 9 = ∑9/20, waiting for 10 jobs, finished 1 job
2025-11-01 06:45:01 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 9 = ∑9/20, waiting for 9 jobs
2025-11-01 06:46:24 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 9 = ∑9/20, new result: VAL_ACC: 69.110000
2025-11-01 06:46:44 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 8 = ∑8/20, waiting for 9 jobs, finished 1 job
2025-11-01 06:46:45 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 8 = ∑8/20, waiting for 8 jobs
2025-11-01 06:48:09 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 8 = ∑8/20, new result: VAL_ACC: 68.980000
2025-11-01 06:48:30 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 7 = ∑7/20, waiting for 8 jobs, finished 1 job
2025-11-01 06:48:30 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 7 = ∑7/20, waiting for 7 jobs
2025-11-01 06:48:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 7 = ∑7/20, new result: VAL_ACC: 68.660000
2025-11-01 06:48:52 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 6 = ∑6/20, waiting for 7 jobs, finished 1 job
2025-11-01 06:48:52 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 6 = ∑6/20, waiting for 6 jobs
2025-11-01 06:48:53 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 6 = ∑6/20, new result: VAL_ACC: 69.180000
2025-11-01 06:49:13 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 5 = ∑5/20, waiting for 6 jobs, finished 1 job
2025-11-01 06:49:14 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 5 = ∑5/20, waiting for 5 jobs
2025-11-01 06:49:15 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 5 = ∑5/20, new result: VAL_ACC: 69.000000
2025-11-01 06:49:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 4 = ∑4/20, waiting for 5 jobs, finished 1 job
2025-11-01 06:49:36 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 4 = ∑4/20, waiting for 4 jobs
2025-11-01 06:49:37 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 4 = ∑4/20, new result: VAL_ACC: 69.170000
2025-11-01 06:49:57 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 3 = ∑3/20, waiting for 4 jobs, finished 1 job
2025-11-01 06:49:57 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 3 = ∑3/20, waiting for 3 jobs
2025-11-01 06:52:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 3 = ∑3/20, new result: VAL_ACC: 69.260000
2025-11-01 06:52:36 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 2 = ∑2/20, waiting for 3 jobs, finished 1 job
2025-11-01 06:52:36 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 2 = ∑2/20, waiting for 2 jobs
2025-11-01 07:06:21 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 2 = ∑2/20, new result: VAL_ACC: 67.800000
2025-11-01 07:06:42 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 1 = ∑1/20, waiting for 2 jobs, finished 1 job
2025-11-01 07:06:42 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 1 = ∑1/20, waiting for 1 job
2025-11-01 07:09:49 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 1 = ∑1/20, new result: VAL_ACC: 70.990000
2025-11-01 07:10:11 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, waiting for 1 job, finished 1 job
2025-11-01 07:14:42 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #1/20
2025-11-01 07:14:43 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #2/20
2025-11-01 07:14:45 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #3/20
2025-11-01 07:14:45 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #4/20
2025-11-01 07:14:45 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #5/20
2025-11-01 07:14:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #6/20
2025-11-01 07:14:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #7/20
2025-11-01 07:14:47 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #8/20
2025-11-01 07:14:47 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #9/20
2025-11-01 07:14:47 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #10/20
2025-11-01 07:14:48 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #11/20
2025-11-01 07:14:48 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #12/20
2025-11-01 07:14:48 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #13/20
2025-11-01 07:14:49 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #14/20
2025-11-01 07:14:49 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #15/20
2025-11-01 07:14:50 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #16/20
2025-11-01 07:14:50 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #17/20
2025-11-01 07:14:50 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #18/20
2025-11-01 07:14:51 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #19/20
2025-11-01 07:14:51 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #20/20
2025-11-01 07:14:51 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, requested 20 jobs, got 20, 13.99 s/job
2025-11-01 07:14:53 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #1/20 start
2025-11-01 07:14:54 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #2/20 start
2025-11-01 07:14:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #3/20 start
2025-11-01 07:14:56 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #4/20 start
2025-11-01 07:14:57 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #5/20 start
2025-11-01 07:15:00 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #6/20 start
2025-11-01 07:15:01 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #7/20 start
2025-11-01 07:15:02 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #8/20 start
2025-11-01 07:15:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #9/20 start
2025-11-01 07:15:05 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #10/20 start
2025-11-01 07:15:07 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #11/20 start
2025-11-01 07:15:08 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #12/20 start
2025-11-01 07:15:09 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #13/20 start
2025-11-01 07:15:13 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #14/20 start
2025-11-01 07:15:15 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #15/20 start
2025-11-01 07:15:16 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #16/20 start
2025-11-01 07:15:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #17/20 start
2025-11-01 07:15:19 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #18/20 start
2025-11-01 07:15:20 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #19/20 start
2025-11-01 07:15:23 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #20/20 start
2025-11-01 07:15:32 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, starting new job
2025-11-01 07:15:36 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 2 = ∑2/20, started new job
2025-11-01 07:15:37 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 2 = ∑2/20, starting new job
2025-11-01 07:15:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 2/1 = ∑3/20, started new job
2025-11-01 07:15:40 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 2/1 = ∑3/20, starting new job
2025-11-01 07:15:44 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 2/2 = ∑4/20, started new job
2025-11-01 07:15:45 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 2/2 = ∑4/20, starting new job
2025-11-01 07:15:51 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 2/5 = ∑7/20, started new job
2025-11-01 07:15:54 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 7/1 = ∑8/20, started new job
2025-11-01 07:15:59 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 7/2 = ∑9/20, started new job
2025-11-01 07:16:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 7/3 = ∑10/20, started new job
2025-11-01 07:16:14 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 10/1 = ∑11/20, started new job
2025-11-01 07:16:21 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 10/2 = ∑12/20, started new job
2025-11-01 07:16:25 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 10/4 = ∑14/20, started new job
2025-11-01 07:16:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 10/7 = ∑17/20, started new job
2025-11-01 07:16:36 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 17/1 = ∑18/20, started new job
2025-11-01 07:16:45 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 18/1 = ∑19/20, started new job
2025-11-01 07:16:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 19/1 = ∑20/20, started new job
2025-11-01 07:16:57 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 19/1 = ∑20/20, waiting for 20 jobs
2025-11-01 07:17:11 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 20 = ∑20/20, waiting for 20 jobs
2025-11-01 08:14:32 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 20 = ∑20/20, new result: VAL_ACC: 71.290000
2025-11-01 08:14:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 19 = ∑19/20, waiting for 20 jobs, finished 1 job
2025-11-01 08:14:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 19 = ∑19/20, waiting for 19 jobs
2025-11-01 08:17:06 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 19 = ∑19/20, new result: VAL_ACC: 70.980000
2025-11-01 08:17:27 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 18 = ∑18/20, waiting for 19 jobs, finished 1 job
2025-11-01 08:17:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 18 = ∑18/20, waiting for 18 jobs
2025-11-01 08:17:45 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 18 = ∑18/20, new result: VAL_ACC: 71.040000
2025-11-01 08:18:07 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 17 = ∑17/20, waiting for 18 jobs, finished 1 job
2025-11-01 08:18:07 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 17 = ∑17/20, waiting for 17 jobs
2025-11-01 08:18:09 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 17 = ∑17/20, new result: VAL_ACC: 70.810000
2025-11-01 08:18:09 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 17 = ∑17/20, new result: VAL_ACC: 70.720000
2025-11-01 08:18:40 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 15 = ∑15/20, waiting for 17 jobs, finished 2 jobs
2025-11-01 08:18:40 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 15 = ∑15/20, waiting for 15 jobs
2025-11-01 08:18:41 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 15 = ∑15/20, new result: VAL_ACC: 71.110000
2025-11-01 08:19:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 14 = ∑14/20, waiting for 15 jobs, finished 1 job
2025-11-01 08:19:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 14 = ∑14/20, waiting for 14 jobs
2025-11-01 08:19:11 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 14 = ∑14/20, new result: VAL_ACC: 70.730000
2025-11-01 08:19:33 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 13 = ∑13/20, waiting for 14 jobs, finished 1 job
2025-11-01 08:19:33 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 13 = ∑13/20, waiting for 13 jobs
2025-11-01 08:19:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 13 = ∑13/20, new result: VAL_ACC: 70.660000
2025-11-01 08:19:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 13 = ∑13/20, new result: VAL_ACC: 71.020000
2025-11-01 08:20:05 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 11 = ∑11/20, waiting for 13 jobs, finished 2 jobs
2025-11-01 08:20:06 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 11 = ∑11/20, waiting for 11 jobs
2025-11-01 08:21:47 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 11 = ∑11/20, new result: VAL_ACC: 70.940000
2025-11-01 08:22:08 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 10 = ∑10/20, waiting for 11 jobs, finished 1 job
2025-11-01 08:22:08 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 10 = ∑10/20, waiting for 10 jobs
2025-11-01 08:23:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 10 = ∑10/20, new result: VAL_ACC: 70.900000
2025-11-01 08:24:00 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 9 = ∑9/20, waiting for 10 jobs, finished 1 job
2025-11-01 08:24:01 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 9 = ∑9/20, waiting for 9 jobs
2025-11-01 08:24:02 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 9 = ∑9/20, new result: VAL_ACC: 70.770000
2025-11-01 08:24:23 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 8 = ∑8/20, waiting for 9 jobs, finished 1 job
2025-11-01 08:24:24 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 8 = ∑8/20, waiting for 8 jobs
2025-11-01 08:24:25 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 8 = ∑8/20, new result: VAL_ACC: 70.650000
2025-11-01 08:24:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 7 = ∑7/20, waiting for 8 jobs, finished 1 job
2025-11-01 08:24:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 7 = ∑7/20, waiting for 7 jobs
2025-11-01 08:29:59 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 7 = ∑7/20, new result: VAL_ACC: 69.900000
2025-11-01 08:30:21 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 6 = ∑6/20, waiting for 7 jobs, finished 1 job
2025-11-01 08:30:21 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 6 = ∑6/20, waiting for 6 jobs
2025-11-01 08:30:51 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 6 = ∑6/20, new result: VAL_ACC: 70.340000
2025-11-01 08:31:13 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 5 = ∑5/20, waiting for 6 jobs, finished 1 job
2025-11-01 08:31:13 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 5 = ∑5/20, waiting for 5 jobs
2025-11-01 08:31:51 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 5 = ∑5/20, new result: VAL_ACC: 70.510000
2025-11-01 08:32:12 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 4 = ∑4/20, waiting for 5 jobs, finished 1 job
2025-11-01 08:32:13 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 4 = ∑4/20, waiting for 4 jobs
2025-11-01 08:32:14 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 4 = ∑4/20, new result: VAL_ACC: 70.600000
2025-11-01 08:32:34 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 3 = ∑3/20, waiting for 4 jobs, finished 1 job
2025-11-01 08:32:34 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 3 = ∑3/20, waiting for 3 jobs
2025-11-01 08:34:37 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 3 = ∑3/20, new result: VAL_ACC: 71.010000
2025-11-01 08:34:58 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 2 = ∑2/20, waiting for 3 jobs, finished 1 job
2025-11-01 08:34:58 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 2 = ∑2/20, waiting for 2 jobs
2025-11-01 08:35:13 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 2 = ∑2/20, new result: VAL_ACC: 70.610000
2025-11-01 08:35:34 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 1 = ∑1/20, waiting for 2 jobs, finished 1 job
2025-11-01 08:35:34 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 1 = ∑1/20, waiting for 1 job
2025-11-01 08:38:15 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 1 = ∑1/20, new result: VAL_ACC: 70.170000
2025-11-01 08:38:37 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, waiting for 1 job, finished 1 job
2025-11-01 08:43:36 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #1/20
2025-11-01 08:43:37 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #2/20
2025-11-01 08:43:37 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #3/20
2025-11-01 08:43:37 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #4/20
2025-11-01 08:43:38 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #5/20
2025-11-01 08:43:38 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #6/20
2025-11-01 08:43:38 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #7/20
2025-11-01 08:43:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #8/20
2025-11-01 08:43:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #9/20
2025-11-01 08:43:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #10/20
2025-11-01 08:43:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #11/20
2025-11-01 08:43:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #12/20
2025-11-01 08:43:47 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #13/20
2025-11-01 08:43:47 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #14/20
2025-11-01 08:43:49 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #15/20
2025-11-01 08:43:49 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #16/20
2025-11-01 08:43:49 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #17/20
2025-11-01 08:43:50 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #18/20
2025-11-01 08:43:50 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #19/20
2025-11-01 08:43:51 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #20/20
2025-11-01 08:43:51 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, requested 20 jobs, got 20, 15.66 s/job
2025-11-01 08:43:53 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #1/20 start
2025-11-01 08:43:54 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #2/20 start
2025-11-01 08:43:56 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #3/20 start
2025-11-01 08:43:59 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #4/20 start
2025-11-01 08:44:00 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #5/20 start
2025-11-01 08:44:03 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #6/20 start
2025-11-01 08:44:05 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #7/20 start
2025-11-01 08:44:06 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #8/20 start
2025-11-01 08:44:07 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #9/20 start
2025-11-01 08:44:09 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #10/20 start
2025-11-01 08:44:11 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #11/20 start
2025-11-01 08:44:12 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #12/20 start
2025-11-01 08:44:13 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #13/20 start
2025-11-01 08:44:15 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #14/20 start
2025-11-01 08:44:16 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #15/20 start
2025-11-01 08:44:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #16/20 start
2025-11-01 08:44:19 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #17/20 start
2025-11-01 08:44:20 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #18/20 start
2025-11-01 08:44:21 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #19/20 start
2025-11-01 08:44:22 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #20/20 start
2025-11-01 08:44:32 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, starting new job
2025-11-01 08:44:36 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, pending 3 = ∑3/20, started new job
2025-11-01 08:44:38 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 3 = ∑3/20, starting new job
2025-11-01 08:44:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 3/1 = ∑4/20, started new job
2025-11-01 08:44:40 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 3/1 = ∑4/20, starting new job
2025-11-01 08:44:44 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 4/1 = ∑5/20, started new job
2025-11-01 08:44:50 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending/unknown 4/1/2 = ∑7/20, started new job
2025-11-01 08:44:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 7/2 = ∑9/20, started new job
2025-11-01 08:45:01 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 9/3 = ∑12/20, started new job
2025-11-01 08:45:05 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending/unknown 9/3/2 = ∑14/20, started new job
2025-11-01 08:45:06 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending/unknown 9/3/3 = ∑15/20, started new job
2025-11-01 08:45:10 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 15/2 = ∑17/20, started new job
2025-11-01 08:45:11 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 15/3 = ∑18/20, started new job
2025-11-01 08:45:15 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 18/2 = ∑20/20, started new job
2025-11-01 08:45:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 18/2 = ∑20/20, waiting for 20 jobs
2025-11-01 08:45:41 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 20 = ∑20/20, waiting for 20 jobs
2025-11-01 09:28:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 20 = ∑20/20, new result: VAL_ACC: 71.060000
2025-11-01 09:29:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 19 = ∑19/20, waiting for 20 jobs, finished 1 job
2025-11-01 09:29:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 19 = ∑19/20, waiting for 19 jobs
2025-11-01 09:31:21 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 19 = ∑19/20, new result: VAL_ACC: 70.870000
2025-11-01 09:31:43 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 18 = ∑18/20, waiting for 19 jobs, finished 1 job
2025-11-01 09:31:43 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 18 = ∑18/20, waiting for 18 jobs
2025-11-01 09:33:48 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 18 = ∑18/20, new result: VAL_ACC: 70.560000
2025-11-01 09:34:11 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 17 = ∑17/20, waiting for 18 jobs, finished 1 job
2025-11-01 09:34:12 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 17 = ∑17/20, waiting for 17 jobs
2025-11-01 09:34:53 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 17 = ∑17/20, new result: VAL_ACC: 70.890000
2025-11-01 09:35:16 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 16 = ∑16/20, waiting for 17 jobs, finished 1 job
2025-11-01 09:35:16 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 16 = ∑16/20, waiting for 16 jobs
2025-11-01 09:35:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 16 = ∑16/20, new result: VAL_ACC: 70.630000
2025-11-01 09:35:44 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 15 = ∑15/20, waiting for 16 jobs, finished 1 job
2025-11-01 09:35:44 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 15 = ∑15/20, waiting for 15 jobs
2025-11-01 09:35:53 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 15 = ∑15/20, new result: VAL_ACC: 70.880000
2025-11-01 09:36:18 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 14 = ∑14/20, waiting for 15 jobs, finished 1 job
2025-11-01 09:36:19 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 14 = ∑14/20, waiting for 14 jobs
2025-11-01 09:36:20 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 14 = ∑14/20, new result: VAL_ACC: 70.540000
2025-11-01 09:36:44 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 13 = ∑13/20, waiting for 14 jobs, finished 1 job
2025-11-01 09:36:44 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 13 = ∑13/20, waiting for 13 jobs
2025-11-01 09:38:37 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 13 = ∑13/20, new result: VAL_ACC: 71.490000
2025-11-01 09:38:59 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 12 = ∑12/20, waiting for 13 jobs, finished 1 job
2025-11-01 09:39:00 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 12 = ∑12/20, waiting for 12 jobs
2025-11-01 09:39:47 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 12 = ∑12/20, new result: VAL_ACC: 70.900000
2025-11-01 09:40:09 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 11 = ∑11/20, waiting for 12 jobs, finished 1 job
2025-11-01 09:40:09 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 11 = ∑11/20, waiting for 11 jobs
2025-11-01 09:40:18 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 11 = ∑11/20, new result: VAL_ACC: 63.820000
2025-11-01 09:40:40 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 10 = ∑10/20, waiting for 11 jobs, finished 1 job
2025-11-01 09:40:41 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 10 = ∑10/20, waiting for 10 jobs
2025-11-01 09:40:42 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 10 = ∑10/20, new result: VAL_ACC: 62.990000
2025-11-01 09:41:05 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 9 = ∑9/20, waiting for 10 jobs, finished 1 job
2025-11-01 09:41:05 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 9 = ∑9/20, waiting for 9 jobs
2025-11-01 09:41:47 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 9 = ∑9/20, new result: VAL_ACC: 70.960000
2025-11-01 09:42:10 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 8 = ∑8/20, waiting for 9 jobs, finished 1 job
2025-11-01 09:42:11 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 8 = ∑8/20, waiting for 8 jobs
2025-11-01 09:42:41 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 8 = ∑8/20, new result: VAL_ACC: 68.010000
2025-11-01 09:43:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 7 = ∑7/20, waiting for 8 jobs, finished 1 job
2025-11-01 09:43:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 7 = ∑7/20, waiting for 7 jobs
2025-11-01 09:43:18 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 7 = ∑7/20, new result: VAL_ACC: 70.840000
2025-11-01 09:43:20 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 7 = ∑7/20, new result: VAL_ACC: 65.670000
2025-11-01 09:43:50 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 5 = ∑5/20, waiting for 7 jobs, finished 2 jobs
2025-11-01 09:43:50 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 5 = ∑5/20, waiting for 5 jobs
2025-11-01 09:46:03 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 5 = ∑5/20, new result: VAL_ACC: 71.080000
2025-11-01 09:46:26 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 4 = ∑4/20, waiting for 5 jobs, finished 1 job
2025-11-01 09:46:26 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 4 = ∑4/20, waiting for 4 jobs
2025-11-01 09:47:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 4 = ∑4/20, new result: VAL_ACC: 70.990000
2025-11-01 09:48:09 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 3 = ∑3/20, waiting for 4 jobs, finished 1 job
2025-11-01 09:48:10 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 3 = ∑3/20, waiting for 3 jobs
2025-11-01 09:48:34 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 3 = ∑3/20, new result: VAL_ACC: 70.540000
2025-11-01 09:48:59 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 2 = ∑2/20, waiting for 3 jobs, finished 1 job
2025-11-01 09:48:59 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 2 = ∑2/20, waiting for 2 jobs
2025-11-01 09:58:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 2 = ∑2/20, new result: VAL_ACC: 68.600000
2025-11-01 09:58:29 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 1 = ∑1/20, waiting for 2 jobs, finished 1 job
2025-11-01 09:58:30 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 1 = ∑1/20, waiting for 1 job
2025-11-01 10:00:32 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 1 = ∑1/20, new result: VAL_ACC: 70.520000
2025-11-01 10:00:57 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, waiting for 1 job, finished 1 job
2025-11-01 10:06:15 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #1/20
2025-11-01 10:06:16 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #2/20
2025-11-01 10:06:16 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #3/20
2025-11-01 10:06:16 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #4/20
2025-11-01 10:06:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #5/20
2025-11-01 10:06:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #6/20
2025-11-01 10:06:18 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #7/20
2025-11-01 10:06:18 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #8/20
2025-11-01 10:06:18 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #9/20
2025-11-01 10:06:19 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #10/20
2025-11-01 10:06:19 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #11/20
2025-11-01 10:06:20 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #12/20
2025-11-01 10:06:20 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #13/20
2025-11-01 10:06:21 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #14/20
2025-11-01 10:06:21 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #15/20
2025-11-01 10:06:22 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #16/20
2025-11-01 10:06:23 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #17/20
2025-11-01 10:06:23 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #18/20
2025-11-01 10:06:54 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #19/20
2025-11-01 10:11:26 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, requested 20 jobs, got 18, 34.90 s/job
2025-11-01 10:11:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #1/18 start
2025-11-01 10:11:29 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #2/18 start
2025-11-01 10:11:30 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #3/18 start
2025-11-01 10:11:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #4/18 start
2025-11-01 10:11:32 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #5/18 start
2025-11-01 10:11:34 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #6/18 start
2025-11-01 10:11:36 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #7/18 start
2025-11-01 10:11:37 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #8/18 start
2025-11-01 10:11:38 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #9/18 start
2025-11-01 10:11:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #10/18 start
2025-11-01 10:11:41 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #11/18 start
2025-11-01 10:11:42 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #12/18 start
2025-11-01 10:11:43 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #13/18 start
2025-11-01 10:11:44 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #14/18 start
2025-11-01 10:11:45 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #15/18 start
2025-11-01 10:11:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #16/18 start
2025-11-01 10:11:48 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #17/18 start
2025-11-01 10:11:50 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #18/18 start
2025-11-01 10:11:57 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, starting new job
2025-11-01 10:11:58 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, pending 1 = ∑1/20, started new job
2025-11-01 10:12:03 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 1/1 = ∑2/20, started new job
2025-11-01 10:12:05 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 1/1 = ∑2/20, waiting for 2 jobs
2025-11-01 10:12:14 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 2 = ∑2/20, waiting for 2 jobs
2025-11-01 10:19:33 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 2 = ∑2/20, new result: VAL_ACC: 66.240000
2025-11-01 10:19:57 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 1 = ∑1/20, waiting for 2 jobs, finished 1 job
2025-11-01 10:19:57 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 1 = ∑1/20, waiting for 1 job
2025-11-01 11:02:08 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 1 = ∑1/20, new result: VAL_ACC: 71.020000
2025-11-01 11:02:33 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, waiting for 1 job, finished 1 job
2025-11-01 11:07:47 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #1/20
2025-11-01 11:07:58 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #2/20
2025-11-01 11:12:48 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #3/20
2025-11-01 11:12:50 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #4/20
2025-11-01 11:12:53 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, requested 20 jobs, got 3, 205.70 s/job
2025-11-01 11:12:54 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #1/3 start
2025-11-01 11:12:56 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #2/3 start
2025-11-01 11:12:57 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #3/3 start
2025-11-01 11:12:59 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, starting new job
2025-11-01 11:13:01 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, unknown 2 = ∑2/20, started new job
2025-11-01 11:13:07 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, pending/unknown 2/1 = ∑3/20, started new job
2025-11-01 11:13:08 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, pending 3 = ∑3/20, waiting for 3 jobs
2025-11-01 11:13:13 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 3 = ∑3/20, waiting for 3 jobs
2025-11-01 12:15:02 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 3 = ∑3/20, new result: VAL_ACC: 69.480000
2025-11-01 12:15:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 2 = ∑2/20, waiting for 3 jobs, finished 1 job
2025-11-01 12:15:36 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 2 = ∑2/20, waiting for 2 jobs
2025-11-01 12:27:54 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 2 = ∑2/20, new result: VAL_ACC: 69.260000
2025-11-01 12:28:21 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 1 = ∑1/20, waiting for 2 jobs, finished 1 job
2025-11-01 12:28:21 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 1 = ∑1/20, waiting for 1 job
2025-11-01 12:29:20 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 1 = ∑1/20, new result: VAL_ACC: 69.310000
2025-11-01 12:29:45 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, waiting for 1 job, finished 1 job
2025-11-01 12:34:49 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #1/20
2025-11-01 12:34:50 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #2/20
2025-11-01 12:34:50 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #3/20
2025-11-01 12:34:51 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #4/20
2025-11-01 12:34:51 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #5/20
2025-11-01 12:34:51 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #6/20
2025-11-01 12:34:52 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #7/20
2025-11-01 12:34:52 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #8/20
2025-11-01 12:34:53 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #9/20
2025-11-01 12:34:53 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #10/20
2025-11-01 12:34:54 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #11/20
2025-11-01 12:34:54 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #12/20
2025-11-01 12:34:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #13/20
2025-11-01 12:34:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #14/20
2025-11-01 12:34:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #15/20
2025-11-01 12:34:56 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #16/20
2025-11-01 12:34:56 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #17/20
2025-11-01 12:34:57 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #18/20
2025-11-01 12:34:57 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #19/20
2025-11-01 12:34:58 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #20/20
2025-11-01 12:34:58 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, requested 20 jobs, got 20, 15.58 s/job
2025-11-01 12:35:02 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #1/20 start
2025-11-01 12:35:03 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #2/20 start
2025-11-01 12:35:05 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #3/20 start
2025-11-01 12:35:07 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #4/20 start
2025-11-01 12:35:08 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #5/20 start
2025-11-01 12:35:11 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #6/20 start
2025-11-01 12:35:12 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #7/20 start
2025-11-01 12:35:13 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #8/20 start
2025-11-01 12:35:14 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #9/20 start
2025-11-01 12:35:16 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #10/20 start
2025-11-01 12:35:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #11/20 start
2025-11-01 12:35:19 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #12/20 start
2025-11-01 12:35:22 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #13/20 start
2025-11-01 12:35:23 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #14/20 start
2025-11-01 12:35:24 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #15/20 start
2025-11-01 12:35:26 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #16/20 start
2025-11-01 12:35:27 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #17/20 start
2025-11-01 12:35:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #18/20 start
2025-11-01 12:35:30 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #19/20 start
2025-11-01 12:35:32 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #20/20 start
2025-11-01 12:35:43 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, starting new job
2025-11-01 12:36:02 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, pending 3 = ∑3/20, started new job
2025-11-01 12:36:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, pending 3 = ∑3/20, starting new job
2025-11-01 12:36:11 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 3/1 = ∑4/20, started new job
2025-11-01 12:36:11 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 3/1 = ∑4/20, starting new job
2025-11-01 12:36:21 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 3/2 = ∑5/20, started new job
2025-11-01 12:36:26 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 5/1 = ∑6/20, started new job
2025-11-01 12:36:37 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 5/4 = ∑9/20, started new job
2025-11-01 12:36:41 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 9/1 = ∑10/20, started new job
2025-11-01 12:36:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 10/1 = ∑11/20, started new job
2025-11-01 12:36:56 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 10/3 = ∑13/20, started new job
2025-11-01 12:37:01 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 10/4 = ∑14/20, started new job
2025-11-01 12:37:11 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 14/1 = ∑15/20, started new job
2025-11-01 12:37:21 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending/unknown 14/1/1 = ∑16/20, started new job
2025-11-01 12:37:26 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 16/1 = ∑17/20, started new job
2025-11-01 12:37:36 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 16/3 = ∑19/20, started new job
2025-11-01 12:37:38 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 16/3 = ∑19/20, waiting for 19 jobs
2025-11-01 12:37:42 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 19 = ∑19/20, waiting for 19 jobs
2025-11-01 12:42:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 19 = ∑19/20, new result: VAL_ACC: 56.830000
2025-11-01 12:42:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 18 = ∑18/20, waiting for 19 jobs, finished 1 job
2025-11-01 12:42:31 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 18 = ∑18/20, waiting for 18 jobs
2025-11-01 13:17:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 18 = ∑18/20, new result: VAL_ACC: 70.170000
2025-11-01 13:17:56 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 17 = ∑17/20, waiting for 18 jobs, finished 1 job
2025-11-01 13:17:56 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 17 = ∑17/20, waiting for 17 jobs
2025-11-01 13:24:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 17 = ∑17/20, new result: VAL_ACC: 70.470000
2025-11-01 13:24:55 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 16 = ∑16/20, waiting for 17 jobs, finished 1 job
2025-11-01 13:24:56 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 16 = ∑16/20, waiting for 16 jobs
2025-11-01 13:28:29 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 16 = ∑16/20, new result: VAL_ACC: 70.690000
2025-11-01 13:28:56 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 15 = ∑15/20, waiting for 16 jobs, finished 1 job
2025-11-01 13:28:56 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 15 = ∑15/20, waiting for 15 jobs
2025-11-01 13:28:58 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 15 = ∑15/20, new result: VAL_ACC: 71.080000
2025-11-01 13:29:25 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 14 = ∑14/20, waiting for 15 jobs, finished 1 job
2025-11-01 13:29:25 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 14 = ∑14/20, waiting for 14 jobs
2025-11-01 13:30:40 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 14 = ∑14/20, new result: VAL_ACC: 70.020000
2025-11-01 13:31:07 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 13 = ∑13/20, waiting for 14 jobs, finished 1 job
2025-11-01 13:31:07 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 13 = ∑13/20, waiting for 13 jobs
2025-11-01 13:31:08 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 13 = ∑13/20, new result: VAL_ACC: 66.820000
2025-11-01 13:31:35 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 12 = ∑12/20, waiting for 13 jobs, finished 1 job
2025-11-01 13:31:36 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 12 = ∑12/20, waiting for 12 jobs
2025-11-01 13:32:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 12 = ∑12/20, new result: VAL_ACC: 67.110000
2025-11-01 13:32:44 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 11 = ∑11/20, waiting for 12 jobs, finished 1 job
2025-11-01 13:32:44 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 11 = ∑11/20, waiting for 11 jobs
2025-11-01 13:33:19 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 11 = ∑11/20, new result: VAL_ACC: 66.650000
2025-11-01 13:33:48 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 10 = ∑10/20, waiting for 11 jobs, finished 1 job
2025-11-01 13:33:48 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 10 = ∑10/20, waiting for 10 jobs
2025-11-01 13:33:50 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 10 = ∑10/20, new result: VAL_ACC: 70.520000
2025-11-01 13:34:16 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 9 = ∑9/20, waiting for 10 jobs, finished 1 job
2025-11-01 13:34:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 9 = ∑9/20, waiting for 9 jobs
2025-11-01 13:36:45 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 9 = ∑9/20, new result: VAL_ACC: 69.980000
2025-11-01 13:37:12 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 8 = ∑8/20, waiting for 9 jobs, finished 1 job
2025-11-01 13:37:13 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 8 = ∑8/20, waiting for 8 jobs
2025-11-01 13:51:08 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 8 = ∑8/20, new result: VAL_ACC: 70.630000
2025-11-01 13:51:37 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 7 = ∑7/20, waiting for 8 jobs, finished 1 job
2025-11-01 13:51:37 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 7 = ∑7/20, waiting for 7 jobs
2025-11-01 13:51:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 7 = ∑7/20, new result: VAL_ACC: 70.050000
2025-11-01 13:52:12 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 6 = ∑6/20, waiting for 7 jobs, finished 1 job
2025-11-01 13:52:12 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 6 = ∑6/20, waiting for 6 jobs
2025-11-01 13:52:21 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 6 = ∑6/20, new result: VAL_ACC: 70.100000
2025-11-01 13:52:47 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 5 = ∑5/20, waiting for 6 jobs, finished 1 job
2025-11-01 13:52:48 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 5 = ∑5/20, waiting for 5 jobs
2025-11-01 13:52:49 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 5 = ∑5/20, new result: VAL_ACC: 70.690000
2025-11-01 13:53:15 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 4 = ∑4/20, waiting for 5 jobs, finished 1 job
2025-11-01 13:53:15 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 4 = ∑4/20, waiting for 4 jobs
2025-11-01 13:53:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 4 = ∑4/20, new result: VAL_ACC: 70.420000
2025-11-01 13:53:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 3 = ∑3/20, waiting for 4 jobs, finished 1 job
2025-11-01 13:53:46 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 3 = ∑3/20, waiting for 3 jobs
2025-11-01 13:54:12 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 3 = ∑3/20, new result: VAL_ACC: 69.990000
2025-11-01 13:54:49 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/completed 1/1 = ∑2/20, waiting for 3 jobs, finished 1 job
2025-11-01 13:54:49 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/completed 1/1 = ∑2/20, waiting for 2 jobs
2025-11-01 13:54:50 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/completed 1/1 = ∑2/20, new result: VAL_ACC: 70.630000
2025-11-01 13:55:16 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 1 = ∑1/20, waiting for 2 jobs, finished 1 job
2025-11-01 13:55:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 1 = ∑1/20, waiting for 1 job
2025-11-01 13:57:05 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 1 = ∑1/20, new result: VAL_ACC: 69.440000
2025-11-01 13:58:13 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, waiting for 1 job, finished 1 job
2025-11-01 14:04:08 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #1/20
2025-11-01 14:04:08 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #2/20
2025-11-01 14:04:09 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #3/20
2025-11-01 14:04:10 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #4/20
2025-11-01 14:04:11 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #5/20
2025-11-01 14:04:11 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #6/20
2025-11-01 14:04:11 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #7/20
2025-11-01 14:04:12 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #8/20
2025-11-01 14:04:13 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #9/20
2025-11-01 14:04:14 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #10/20
2025-11-01 14:04:14 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #11/20
2025-11-01 14:04:15 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #12/20
2025-11-01 14:04:15 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #13/20
2025-11-01 14:04:16 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #14/20
2025-11-01 14:04:16 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #15/20
2025-11-01 14:04:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #16/20
2025-11-01 14:04:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #17/20
2025-11-01 14:04:18 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #18/20
2025-11-01 14:04:18 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #19/20
2025-11-01 14:04:19 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, getting new HP set #20/20
2025-11-01 14:04:19 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, requested 20 jobs, got 20, 18.23 s/job
2025-11-01 14:04:23 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #1/20 start
2025-11-01 14:04:25 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #2/20 start
2025-11-01 14:04:27 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #3/20 start
2025-11-01 14:04:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #4/20 start
2025-11-01 14:04:29 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #5/20 start
2025-11-01 14:04:36 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #6/20 start
2025-11-01 14:04:37 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #7/20 start
2025-11-01 14:04:39 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #8/20 start
2025-11-01 14:04:41 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #9/20 start
2025-11-01 14:04:42 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #10/20 start
2025-11-01 14:04:44 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #11/20 start
2025-11-01 14:04:50 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #12/20 start
2025-11-01 14:04:51 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #13/20 start
2025-11-01 14:04:53 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #14/20 start
2025-11-01 14:04:54 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #15/20 start
2025-11-01 14:04:56 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #16/20 start
2025-11-01 14:04:57 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #17/20 start
2025-11-01 14:04:59 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #18/20 start
2025-11-01 14:05:01 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #19/20 start
2025-11-01 14:05:02 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, eval #20/20 start
2025-11-01 14:05:14 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, starting new job
2025-11-01 14:05:17 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, pending 1 = ∑1/20, started new job
2025-11-01 14:05:18 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, pending 1 = ∑1/20, starting new job
2025-11-01 14:05:21 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 1/1 = ∑2/20, started new job
2025-11-01 14:05:22 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 1/1 = ∑2/20, starting new job
2025-11-01 14:05:26 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending/unknown 1/1/2 = ∑4/20, started new job
2025-11-01 14:05:28 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 1/3 = ∑4/20, starting new job
2025-11-01 14:05:32 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending/unknown 1/3/2 = ∑6/20, started new job
2025-11-01 14:05:37 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 6/2 = ∑8/20, started new job
2025-11-01 14:05:40 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 9 = ∑9/20, started new job
2025-11-01 14:05:41 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 9/1 = ∑10/20, started new job
2025-11-01 14:05:48 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending/unknown 9/1/3 = ∑13/20, started new job
2025-11-01 14:05:52 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending/unknown 9/4/3 = ∑16/20, started new job
2025-11-01 14:05:57 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 16/3 = ∑19/20, started new job
2025-11-01 14:06:01 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/unknown 19/1 = ∑20/20, started new job
2025-11-01 14:06:03 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running/pending 19/1 = ∑20/20, waiting for 20 jobs
2025-11-01 14:06:13 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 20 = ∑20/20, waiting for 20 jobs
2025-11-01 14:11:44 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 20 = ∑20/20, new result: VAL_ACC: 59.410000
2025-11-01 14:12:13 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 19 = ∑19/20, waiting for 20 jobs, finished 1 job
2025-11-01 14:12:14 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 19 = ∑19/20, waiting for 19 jobs
2025-11-01 14:54:49 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 19 = ∑19/20, new result: VAL_ACC: 70.130000
2025-11-01 14:55:18 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 18 = ∑18/20, waiting for 19 jobs, finished 1 job
2025-11-01 14:55:18 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 18 = ∑18/20, waiting for 18 jobs
2025-11-01 14:55:20 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 18 = ∑18/20, new result: VAL_ACC: 70.210000
2025-11-01 14:55:20 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 18 = ∑18/20, new result: VAL_ACC: 71.070000
2025-11-01 14:56:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 16 = ∑16/20, waiting for 18 jobs, finished 2 jobs
2025-11-01 14:56:04 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 16 = ∑16/20, waiting for 16 jobs
2025-11-01 14:57:25 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 16 = ∑16/20, new result: VAL_ACC: 70.790000
2025-11-01 14:57:51 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 15 = ∑15/20, waiting for 16 jobs, finished 1 job
2025-11-01 14:57:52 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 15 = ∑15/20, waiting for 15 jobs
2025-11-01 14:57:53 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 15 = ∑15/20, new result: VAL_ACC: 70.870000
2025-11-01 14:58:20 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 14 = ∑14/20, waiting for 15 jobs, finished 1 job
2025-11-01 14:58:20 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 14 = ∑14/20, waiting for 14 jobs
2025-11-01 14:58:22 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 14 = ∑14/20, new result: VAL_ACC: 69.780000
2025-11-01 14:58:49 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 13 = ∑13/20, waiting for 14 jobs, finished 1 job
2025-11-01 14:58:50 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 13 = ∑13/20, waiting for 13 jobs
2025-11-01 15:00:13 (127c23cb-d119-4ecc-b801-d8b643248022): SOBOL, best VAL_ACC: 71.56, running 13 = ∑13/20, new result: VAL_ACC: 70.920000
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', '300', '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 | 120 |
| slurm_use_srun | False |
| time | 1440 |
| 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 |
1761919418.7188,20,0,0
1761919446.2211,20,0,0
1761919446.4948,20,1,5
1761919446.6405,20,1,5
1761919446.6595,20,2,10
1761919446.6879,20,2,10
1761919446.7071,20,0,0
1761919446.7858,20,3,15
1761919452.0279,20,3,15
1761919456.9792,20,6,30
1761919457.0542,20,6,30
1761919461.9857,20,8,40
1761919462.0584,20,8,40
1761919466.9917,20,10,50
1761919467.065,20,10,50
1761919487.1583,20,20,100
1761920493.5222,20,20,100
1761920494.085,20,19,95
1761920958.9229,20,19,95
1761920959.5001,20,18,90
1761921044.6418,20,18,90
1761921050.3266,20,17,85
1761921103.7821,20,17,85
1761921107.0559,20,16,80
1761921364.5334,20,16,80
1761921365.1057,20,15,75
1761921492.8096,20,15,75
1761921495.7067,20,14,70
1761921499.9114,20,14,70
1761921500.4844,20,13,65
1761921599.5076,20,13,65
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1761962197.3417,20,8,40
1761962262.5759,20,8,40
1761962274.0512,20,7,35
1761962723.0841,20,7,35
1761962734.7931,20,6,30
1761962912.7627,20,6,30
1761962924.9646,20,4,20
1761962970.5256,20,4,20
1761962982.4624,20,3,15
1761963097.32,20,3,15
1761963109.0965,20,2,10
1761963211.5119,20,2,10
1761963223.7835,20,1,5
1761963267.7919,20,1,5
1761963268.0773,20,0,0
1761963461.3296,20,0,0
1761963462.1205,20,1,5
1761963464.2075,20,1,5
1761963467.2988,20,2,10
1761963468.1566,20,2,10
1761963472.2814,20,4,20
1761963473.9227,20,4,20
1761963477.2987,20,7,35
1761963478.1145,20,7,35
1761963482.295,20,8,40
1761963482.6082,20,8,40
1761963487.3391,20,9,45
1761963487.6513,20,9,45
1761963492.3243,20,10,50
1761963492.6339,20,10,50
1761963497.3427,20,12,60
1761963498.6124,20,12,60
1761963502.3123,20,13,65
1761963502.6228,20,13,65
1761963508.4042,20,14,70
1761963508.7129,20,14,70
1761963512.3223,20,15,75
1761963512.6388,20,15,75
1761963517.3626,20,18,90
1761963518.6742,20,18,90
1761963522.3354,20,20,100
1761965673.5632,20,20,100
1761965686.781,20,19,95
1761965749.5426,20,19,95
1761965762.4424,20,14,70
1761965771.7145,20,14,70
1761965809.8121,20,8,40
1761965822.8583,20,8,40
1761965883.5639,20,2,10
1761966020.975,20,2,10
1761966034.1574,20,1,5
1761966043.2397,20,1,5
1761966056.6113,20,0,0
1761966276.0504,20,0,0
1761966277.4481,20,2,10
1761966280.9195,20,2,10
1761966282.8933,20,4,20
1761966283.7581,20,4,20
1761966287.9069,20,6,30
1761966288.526,20,6,30
1761966292.9069,20,9,45
1761966293.7659,20,9,45
1761966297.9044,20,12,60
1761966298.7692,20,12,60
1761966302.918,20,15,75
1761966303.8059,20,15,75
1761966307.9158,20,18,90
1761966308.7788,20,18,90
1761966312.9149,20,20,100
1761967737.4926,20,20,100
1761967751.8704,20,19,95
1761968344.9126,20,19,95
1761968358.7556,20,18,90
1761968426.2659,20,18,90
1761968440.7037,20,17,85
1761968448.2839,20,17,85
1761968462.0997,20,16,80
1761968514.3456,20,16,80
1761968528.0303,20,14,70
1761968531.5978,20,14,70
1761968547.4149,20,12,60
1761968550.6353,20,12,60
1761968551.2838,20,10,50
1761968555.6642,20,10,50
1761968556.5532,20,9,45
1761968556.7562,20,9,45
1761968597.4782,20,5,25
1761968601.3592,20,5,25
1761968602.4732,20,4,20
1761968604.8753,20,4,20
1761968608.1453,20,3,15
1761968611.0752,20,3,15
1761968673.2544,20,2,10
1761968770.8777,20,2,10
1761968786.4896,20,1,5
1761969738.4138,20,1,5
1761969753.5047,20,0,0
1761970003.2254,20,0,0
1761970004.5996,20,1,5
1761970004.6434,20,2,10
1761970004.9299,20,2,10
1761970005.9444,20,0,0
1761970006.3021,20,3,15
1761970008.5653,20,3,15
1761970015.1629,20,4,20
1761970016.0733,20,4,20
1761970025.1737,20,5,25
1761970026.5264,20,5,25
1761970035.3743,20,7,35
1761970036.03,20,7,35
1761970040.1882,20,10,50
1761970041.108,20,10,50
1761970045.1755,20,11,55
1761970045.5139,20,11,55
1761970055.1836,20,12,60
1761970055.5332,20,12,60
1761970065.2026,20,14,70
1761970065.8562,20,14,70
1761970070.2075,20,16,80
1761970070.8612,20,16,80
1761970075.2122,20,19,95
1761970076.1302,20,19,95
1761970080.2124,20,20,100
1761971407.8741,20,20,100
1761971424.3496,20,19,95
1761971597.4796,20,19,95
1761971614.6494,20,18,90
1761971617.5684,20,18,90
1761971618.3067,20,17,85
1761971733.8086,20,17,85
1761971753.3963,20,15,75
1761971757.2474,20,15,75
1761971773.6049,20,14,70
1761971830.5771,20,14,70
1761971847.0253,20,13,65
1761971875.3855,20,13,65
1761971892.8136,20,11,55
1761971949.6767,20,11,55
1761971965.5657,20,10,50
1761971969.28,20,10,50
1761971984.8109,20,9,45
1761972426.1787,20,9,45
1761972443.5467,20,8,40
1761972489.0976,20,8,40
1761972506.3085,20,7,35
1761972521.4679,20,7,35
1761972537.351,20,5,25
1761972541.2352,20,5,25
1761972557.7253,20,3,15
1761972563.4933,20,3,15
1761972586.8963,20,2,10
1761972590.6143,20,2,10
1761972606.3,20,0,0
1761972914.8124,20,0,0
1761972915.8501,20,1,5
1761972919.7821,20,1,5
1761972926.2356,20,4,20
1761972927.1701,20,4,20
1761972931.2191,20,5,25
1761972931.5949,20,5,25
1761972936.223,20,6,30
1761972936.5659,20,6,30
1761972941.229,20,7,35
1761972941.5876,20,7,35
1761972946.2429,20,9,45
1761972946.911,20,9,45
1761972951.252,20,12,60
1761972952.1958,20,12,60
1761972956.2456,20,13,65
1761972956.6045,20,13,65
1761972961.2553,20,14,70
1761972961.6075,20,14,70
1761972966.2601,20,15,75
1761972966.6097,20,15,75
1761972971.2658,20,16,80
1761972971.6378,20,16,80
1761972976.2667,20,17,85
1761972976.6269,20,17,85
1761972981.2827,20,18,90
1761972981.6401,20,18,90
1761972986.2824,20,20,100
1761974708.6986,20,20,100
1761974729.0429,20,19,95
1761974960.0609,20,19,95
1761974978.9963,20,18,90
1761974983.0898,20,18,90
1761975000.5829,20,17,85
1761975334.3943,20,17,85
1761975351.6269,20,16,80
1761975364.7131,20,16,80
1761975381.1496,20,15,75
1761975389.4381,20,15,75
1761975407.2843,20,14,70
1761975410.9253,20,14,70
1761975411.2436,20,13,65
1761975449.8159,20,13,65
1761975465.4299,20,12,60
1761975469.5299,20,12,60
1761975486.0485,20,11,55
1761975694.6176,20,11,55
1761975711.342,20,10,50
1761975881.8826,20,10,50
1761975899.9918,20,9,45
1761975985.7117,20,9,45
1761976003.493,20,8,40
1761976090.3759,20,8,40
1761976109.2184,20,6,30
1761976113.3473,20,6,30
1761976131.245,20,5,25
1761976135.1828,20,5,25
1761976152.7172,20,4,20
1761976156.7897,20,4,20
1761976174.6553,20,3,15
1761976338.4307,20,3,15
1761976355.1498,20,2,10
1761977182.6577,20,2,10
1761977201.1664,20,1,5
1761977390.7786,20,1,5
1761977408.6814,20,0,0
1761977731.6944,20,0,0
1761977733.8836,20,2,10
1761977736.8974,20,2,10
1761977739.2822,20,3,15
1761977740.2933,20,3,15
1761977744.2536,20,4,20
1761977745.2559,20,4,20
1761977749.269,20,7,35
1761977750.2618,20,7,35
1761977754.2861,20,8,40
1761977754.6609,20,8,40
1761977759.2717,20,9,45
1761977759.6434,20,9,45
1761977764.2765,20,10,50
1761977764.6553,20,10,50
1761977774.2868,20,11,55
1761977774.653,20,11,55
1761977780.3448,20,12,60
1761977780.7338,20,12,60
1761977784.3175,20,14,70
1761977785.033,20,14,70
1761977789.3184,20,17,85
1761977790.329,20,17,85
1761977795.3804,20,18,90
1761977795.7501,20,18,90
1761977804.3238,20,19,95
1761977804.7004,20,19,95
1761977814.759,20,20,100
1761981274.2289,20,20,100
1761981294.0179,20,19,95
1761981427.9653,20,19,95
1761981446.4903,20,18,90
1761981467.131,20,18,90
1761981486.3975,20,15,75
1761981492.7405,20,15,75
1761981519.2694,20,14,70
1761981553.2585,20,14,70
1761981572.0995,20,13,65
1761981576.1682,20,13,65
1761981577.7077,20,11,55
1761981708.5077,20,11,55
1761981727.0055,20,10,50
1761981820.9498,20,10,50
1761981821.299,20,9,45
1761981839.5046,20,8,40
1761981843.8324,20,8,40
1761981862.5464,20,7,35
1761982201.1708,20,7,35
1761982219.9025,20,6,30
1761982253.3444,20,6,30
1761982272.1563,20,5,25
1761982313.3976,20,5,25
1761982331.4863,20,3,15
1761982479.1088,20,3,15
1761982497.4355,20,2,10
1761982514.5348,20,2,10
1761982533.2162,20,1,5
1761982696.666,20,1,5
1761982715.7772,20,0,0
1761983072.7743,20,0,0
1761983073.598,20,1,5
1761983077.6289,20,1,5
1761983078.9797,20,3,15
1761983080.0601,20,3,15
1761983084.0066,20,5,25
1761983084.3925,20,5,25
1761983089.0091,20,7,35
1761983089.7609,20,7,35
1761983094.0334,20,9,45
1761983094.8049,20,9,45
1761983099.0292,20,12,60
1761983100.1667,20,12,60
1761983104.0495,20,15,75
1761983105.7687,20,15,75
1761983109.0428,20,18,90
1761983111.073,20,18,90
1761983114.065,20,20,100
1761985737.0591,20,20,100
1761985756.2696,20,19,95
1761985882.9584,20,19,95
1761985902.0763,20,18,90
1761986030.2872,20,18,90
1761986050.5503,20,17,85
1761986094.9651,20,17,85
1761986095.3395,20,16,80
1761986115.1123,20,15,75
1761986155.6339,20,15,75
1761986177.5288,20,13,65
1761986318.6732,20,13,65
1761986338.5485,20,12,60
1761986389.5385,20,12,60
1761986408.2704,20,11,55
1761986419.7039,20,11,55
1761986439.3248,20,9,45
1761986508.7446,20,9,45
1761986509.1168,20,8,40
1761986562.8758,20,8,40
1761986583.1928,20,7,35
1761986602.7329,20,7,35
1761986608.2184,20,5,25
1761986765.0461,20,5,25
1761986785.0347,20,4,20
1761986859.9969,20,4,20
1761986865.9164,20,3,15
1761986916.6464,20,3,15
1761986937.8523,20,2,10
1761987485.7401,20,2,10
1761987508.2063,20,1,5
1761987633.8286,20,1,5
1761987655.7831,20,0,0
1761988316.6795,20,0,0
1761988317.8834,20,1,5
1761988318.311,20,1,5
1761988323.2051,20,2,10
1761988775.0478,20,2,10
1761988796.074,20,1,5
1761991330.6163,20,1,5
1761991352.4234,20,0,0
1761991978.4943,20,0,0
1761991979.6665,20,1,5
1761991980.6127,20,1,5
1761991986.2279,20,3,15
1761995703.8694,20,3,15
1761995704.2539,20,2,10
1761996476.0066,20,2,10
1761996499.5431,20,1,5
1761996562.4468,20,1,5
1761996584.2227,20,0,0
1761996943.4734,20,0,0
1761996960.2213,20,3,15
1761996963.8272,20,3,15
1761996970.2223,20,4,20
1761996971.4316,20,4,20
1761996980.2333,20,5,25
1761996980.6681,20,5,25
1761996985.2321,20,6,30
1761996985.6859,20,6,30
1761996995.2516,20,9,45
1761996996.4333,20,9,45
1761997000.2618,20,10,50
1761997000.7015,20,10,50
1761997005.2539,20,11,55
1761997005.7026,20,11,55
1761997015.2909,20,13,65
1761997016.1411,20,13,65
1761997020.2979,20,14,70
1761997020.7374,20,14,70
1761997030.2833,20,15,75
1761997030.723,20,15,75
1761997040.295,20,17,85
1761997040.7482,20,17,85
1761997045.3153,20,18,90
1761997045.7721,20,18,90
1761997055.3057,20,20,100
1761997109.3476,20,20,100
1761997110.3041,20,19,95
1761997326.3743,20,19,95
1761997349.757,20,18,90
1761999450.4099,20,18,90
1761999474.7101,20,17,85
1761999870.3421,20,17,85
1761999894.3183,20,16,80
1762000111.6208,20,16,80
1762000135.1463,20,15,75
1762000139.8204,20,15,75
1762000140.2337,20,14,70
1762000242.4583,20,14,70
1762000265.5907,20,12,60
1762000338.8103,20,12,60
1762000339.2148,20,11,55
1762000401.5682,20,11,55
1762000426.8428,20,9,45
1762000606.8213,20,9,45
1762000631.2155,20,8,40
1762001470.2114,20,8,40
1762001495.8055,20,7,35
1762001508.384,20,7,35
1762001531.0836,20,6,30
1762001543.4521,20,6,30
1762001565.998,20,4,20
1762001571.1627,20,4,20
1762001593.9014,20,3,15
1762001654.2893,20,3,15
1762001687.7383,20,1,5
1762001827.1146,20,1,5
1762001891.8471,20,0,0
1762002314.0953,20,0,0
1762002315.4156,20,1,5
1762002317.8294,20,1,5
1762002320.362,20,2,10
1762002321.6779,20,2,10
1762002325.3566,20,4,20
1762002327.862,20,4,20
1762002330.3933,20,6,30
1762002331.3214,20,6,30
1762002335.3897,20,9,45
1762002340.8114,20,9,45
1762002345.8252,20,13,65
1762002347.0969,20,13,65
1762002350.3922,20,16,80
1762002351.647,20,16,80
1762002355.396,20,19,95
1762002356.6641,20,19,95
1762002360.3971,20,20,100
1762002706.6088,20,20,100
1762002732.2187,20,19,95
1762005291.678,20,19,95
1762005316.6719,20,16,80
1762005446.2759,20,16,80
1762005447.2809,20,15,75
1762005474.1895,20,15,75
1762005475.3509,20,14,70
1762005475.7554,20,14,70
1762005498.8151,20,13,65
1762005615.0463,20,13,65
This logs the CPU and RAM usage of the main worker process.
timestamp,ram_usage_mb,cpu_usage_percent
1761919418,807.8046875,12.6
1761919487,855.859375,12.3
1761919547,849.76953125,12.2
1761919607,849.73046875,12.2
1761919667,849.73046875,12.1
1761919727,856.20703125,12.1
1761919787,856.24609375,12.4
1761919847,856.2421875,12.2
1761919907,856.25,12.2
1761919967,856.23046875,12.1
1761920027,856.24609375,12.2
1761920087,856.29296875,12.4
1761920147,856.28125,12.3
1761920207,856.27734375,13.2
1761920267,856.31640625,12.4
1761920327,856.3515625,12.2
1761920387,856.33203125,12.8
1761920447,856.3828125,12.3
1761920507,858.91796875,12.5
1761920567,858.91015625,12.2
1761920627,858.93359375,13.5
1761920687,858.91015625,12.3
1761920747,858.90234375,12.3
1761920807,858.90234375,12.5
1761920867,858.9375,12.3
1761920927,858.90234375,12.2
1761920987,859.296875,12.4
1761921050,859.26953125,12.7
1761921110,859.609375,12.1
1761921170,859.6171875,12.6
1761921230,859.62109375,12.4
1761921290,859.62109375,12.1
1761921350,859.6328125,12.5
1761921410,859.86328125,12.5
1761921470,859.83203125,12
1761921530,860.51171875,12.6
1761921590,860.515625,11.9
1761921650,860.609375,12
1761921710,860.609375,11.9
1761921770,860.62890625,12.3
1761921830,860.61328125,12.1
1761921890,860.61328125,12
1761921950,860.62890625,12
1761922010,860.61328125,11.8
1761922070,860.95703125,11.8
1761922130,860.95703125,11.7
1761922190,860.9453125,11.8
1761922250,860.9765625,11.9
1761922310,860.984375,11.9
1761922370,861.2734375,11.7
1761922430,861.2734375,11.7
1761922490,861.3671875,11.9
1761922550,861.4609375,11.6
1761922610,861.53515625,13.2
1761922670,861.63671875,11.6
1761922730,861.63671875,11.5
1761922790,861.7734375,11.3
1761922850,861.765625,11.6
1761922910,861.765625,11.5
1761922970,861.765625,11.7
1761923030,861.765625,11.4
1761923090,861.765625,11.6
1761923150,861.765625,11.5
1761923210,861.765625,12.6
1761923270,861.765625,12.6
1761923330,862.265625,13.3
1761923390,862.265625,11.7
1761923450,862.265625,11.5
1761923510,862.265625,11.7
1761923570,862.265625,11.8
1761923630,862.265625,11.5
1761923690,862.265625,11.2
1761923750,862.265625,11.2
1761923810,862.265625,11.6
1761923870,862.265625,11.5
1761923978,879.83203125,12.9
1761924038,885.44140625,11.6
1761924098,885.42578125,11.5
1761924158,891.5703125,11.5
1761924218,891.5390625,11.5
1761924278,891.53515625,11.4
1761924338,891.60546875,11.5
1761924398,891.65625,11.4
1761924458,891.671875,11.6
1761924518,891.73046875,11.4
1761924578,891.76953125,11.4
1761924638,891.828125,11.4
1761924698,891.8125,11.2
1761924758,891.859375,11.5
1761924818,891.88671875,11.6
1761924878,891.96484375,11.5
1761924938,892.0078125,11.6
1761924998,892.0078125,11.4
1761925058,892.06640625,11.6
1761925118,892.09375,11.4
1761925178,892.12890625,11.5
1761925238,892.66796875,11.3
1761925298,892.70703125,11.5
1761925358,909.73046875,11.5
1761925418,923.25390625,11.4
1761925478,927.7734375,11.4
1761925538,928.81640625,11.2
1761925598,928.8046875,11.4
1761925658,928.84765625,11.3
1761925718,928.8203125,11.5
1761925778,928.84375,11.4
1761925838,928.8203125,11.5
1761925898,928.84375,11.4
1761925958,928.85546875,11.5
1761926018,928.84375,11.6
1761926078,928.921875,11.1
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1761926198,928.98046875,11.5
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VAL_ACC (goal: maximize)
Best value: 71.56
Achieved at:
- run_time = 2142
- epochs = 140
- lr = 0.000981972524827
- batch_size = 64
- hidden_size = 2677
- dropout = 0.32865080716015
- num_dense_layers = 1
- filter = 128
- num_conv_layers = 5
Parameter statistics
| Parameter | Min | Max | Mean | Std Dev | Count |
|---|
| run_time | 249 | 4898 | 2569.3808 | 885.5154 | 386 |
| VAL_ACC | 43.57 | 71.56 | 68.3074 | 3.9213 | 386 |
| epochs | 20 | 300 | 186.2257 | 69.7517 | 421 |
| lr | 0.0001 | 0.001 | 0.0008 | 0.0002 | 421 |
| batch_size | 64 | 1024 | 186.076 | 280.2795 | 421 |
| hidden_size | 512 | 4096 | 2752.1544 | 838.2884 | 421 |
| dropout | 0 | 0.5 | 0.3778 | 0.1099 | 421 |
| num_dense_layers | 1 | 2 | 1.209 | 0.4066 | 421 |
| filter | 16 | 128 | 123.3444 | 14.5544 | 421 |
| num_conv_layers | 5 | 7 | 5.4893 | 0.6633 | 421 |
Show SLURM-Job-ID (if it exists)
submitit INFO (2025-10-31 15:04:09,058) - Starting with JobEnvironment(job_id=1205101, hostname=c93, local_rank=0(1), node=0(1), global_rank=0(1))
submitit INFO (2025-10-31 15:04:09,059) - Loading pickle: /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/runs/mnist_mono/2/single_runs/1205101/1205101_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": 137, "lr": 0.0009792506732977926, "batch_size": 156, "hidden_size": 2285, "dropout": 0.28016804065555334, "num_dense_layers": 1, "filter": 49, "num_conv_layers": 5}
Debug-Infos:
========
DEBUG INFOS START:
Program-Code: python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 137 --learning_rate 0.00097925067329779261 --batch_size 156 --hidden_size 2285 --dropout 0.28016804065555334091 --num_dense_layers 1 --filter 49 --num_conv_layers 5
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: 1205101
Status-Change-Time: 1761910410.0
Size: 19255 Bytes
Permissions: -rwxr-xr-x
Owner: s3811141
Last access: 1761919450.0
Last modification: 1761906808.0
Hostname: c93
========
DEBUG INFOS END
python3 /data/horse/ws/s3811141-omniopt_mnist_test_call/omniopt/.tests/mnist/train --epochs 137 --learning_rate 0.00097925067329779261 --batch_size 156 --hidden_size 2285 --dropout 0.28016804065555334091 --num_dense_layers 1 --filter 49 --num_conv_layers 5
stdout:
Hyperparameters
╭──────────────────┬───────────────────────╮
│ Parameter │ Value │
├──────────────────┼───────────────────────┤
│ Epochs │ 137 │
│ Num Dense Layers │ 1 │
│ Batch size │ 156 │
│ Learning rate │ 0.0009792506732977926 │
│ Hidden size │ 2285 │
│ Dropout │ 0.28016804065555334 │
│ Optimizer │ adam │
│ Momentum │ 0.9 │
│ Weight Decay │ 0.0001 │
│ Activation │ relu │
│ Init Method │ kaiming │
│ Seed │ None │
│ Conv Filters │ 49 │
│ Num Conv Layers │ 5 │
│ Conv Kernel │ 3 │
│ Conv Stride │ 1 │
│ Conv Padding │ 1 │
╰──────────────────┴───────────────────────╯
Model Summary
╭─────────────────┬─────────────────┬─────────╮
│ Layer │ Output Shape │ Param # │
├─────────────────┼─────────────────┼─────────┤
│ conv::conv0 │ [1, 49, 32, 32] │ 1372 │
│ conv::bn0 │ [1, 49, 32, 32] │ 98 │
│ conv::act_conv0 │ [1, 49, 32, 32] │ 0 │
│ conv::conv1 │ [1, 49, 32, 32] │ 21658 │
│ conv::bn1 │ [1, 49, 32, 32] │ 98 │
│ conv::act_conv1 │ [1, 49, 32, 32] │ 0 │
│ conv::pool1 │ [1, 49, 16, 16] │ 0 │
│ conv::conv2 │ [1, 49, 16, 16] │ 21658 │
│ conv::bn2 │ [1, 49, 16, 16] │ 98 │
│ conv::act_conv2 │ [1, 49, 16, 16] │ 0 │
│ conv::conv3 │ [1, 49, 16, 16] │ 21658 │
│ conv::bn3 │ [1, 49, 16, 16] │ 98 │
│ conv::act_conv3 │ [1, 49, 16, 16] │ 0 │
│ conv::pool2 │ [1, 49, 8, 8] │ 0 │
│ conv::conv4 │ [1, 49, 8, 8] │ 21658 │
│ conv::bn4 │ [1, 49, 8, 8] │ 98 │
│ conv::act_conv4 │ [1, 49, 8, 8] │ 0 │
│ dense::fc0 │ [1, 2285] │ 7168045 │
│ dense::act0 │ [1, 2285] │ 0 │
│ dense::dropout0 │ [1, 2285] │ 0 │
│ dense::output │ [1, 100] │ 228600 │
│ Total │ - │ 7485139 │
╰─────────────────┴─────────────────┴─────────╯
──────────────────────────── Epoch 1/137 - Training ────────────────────────────
Epoch-Loss: 1205.1989
─────────────────────────── Epoch 1/137 - Validation ───────────────────────────
╔══ Epoch 1/137 Summary ══╗
║ Validation Loss: 3.0366 ║
║ Accuracy: 24.93% ║
╚═════════════════════════╝
──────────────────────────── Epoch 2/137 - Training ────────────────────────────
Epoch-Loss: 974.5690
─────────────────────────── Epoch 2/137 - Validation ───────────────────────────
╔══ Epoch 2/137 Summary ══╗
║ Validation Loss: 2.6078 ║
║ Accuracy: 33.09% ║
╚═════════════════════════╝
──────────────────────────── Epoch 3/137 - Training ────────────────────────────
Epoch-Loss: 865.2957
─────────────────────────── Epoch 3/137 - Validation ───────────────────────────
╔══ Epoch 3/137 Summary ══╗
║ Validation Loss: 2.5674 ║
║ Accuracy: 33.72% ║
╚═════════════════════════╝
──────────────────────────── Epoch 4/137 - Training ────────────────────────────
Epoch-Loss: 801.3919
─────────────────────────── Epoch 4/137 - Validation ───────────────────────────
╔══ Epoch 4/137 Summary ══╗
║ Validation Loss: 2.2225 ║
║ Accuracy: 40.89% ║
╚═════════════════════════╝
──────────────────────────── Epoch 5/137 - Training ────────────────────────────
Epoch-Loss: 749.0921
─────────────────────────── Epoch 5/137 - Validation ───────────────────────────
╔══ Epoch 5/137 Summary ══╗
║ Validation Loss: 2.1881 ║
║ Accuracy: 42.33% ║
╚═════════════════════════╝
──────────────────────────── Epoch 6/137 - Training ────────────────────────────
Epoch-Loss: 711.4362
─────────────────────────── Epoch 6/137 - Validation ───────────────────────────
╔══ Epoch 6/137 Summary ══╗
║ Validation Loss: 2.0562 ║
║ Accuracy: 45.39% ║
╚═════════════════════════╝
──────────────────────────── Epoch 7/137 - Training ────────────────────────────
Epoch-Loss: 675.3353
─────────────────────────── Epoch 7/137 - Validation ───────────────────────────
╔══ Epoch 7/137 Summary ══╗
║ Validation Loss: 1.9802 ║
║ Accuracy: 46.84% ║
╚═════════════════════════╝
──────────────────────────── Epoch 8/137 - Training ────────────────────────────
Epoch-Loss: 653.6666
─────────────────────────── Epoch 8/137 - Validation ───────────────────────────
╔══ Epoch 8/137 Summary ══╗
║ Validation Loss: 1.9477 ║
║ Accuracy: 48.08% ║
╚═════════════════════════╝
──────────────────────────── Epoch 9/137 - Training ────────────────────────────
Epoch-Loss: 631.4858
─────────────────────────── Epoch 9/137 - Validation ───────────────────────────
╔══ Epoch 9/137 Summary ══╗
║ Validation Loss: 1.8567 ║
║ Accuracy: 50.05% ║
╚═════════════════════════╝
─────────────────────────── Epoch 10/137 - Training ────────────────────────────
Epoch-Loss: 608.9586
────────────────────────── Epoch 10/137 - Validation ───────────────────────────
╔═ Epoch 10/137 Summary ══╗
║ Validation Loss: 1.9313 ║
║ Accuracy: 49.32% ║
╚═════════════════════════╝
─────────────────────────── Epoch 11/137 - Training ────────────────────────────
Epoch-Loss: 594.7990
────────────────────────── Epoch 11/137 - Validation ───────────────────────────
╔═ Epoch 11/137 Summary ══╗
║ Validation Loss: 1.8205 ║
║ Accuracy: 50.56% ║
╚═════════════════════════╝
─────────────────────────── Epoch 12/137 - Training ────────────────────────────
Epoch-Loss: 577.7907
────────────────────────── Epoch 12/137 - Validation ───────────────────────────
╔═ Epoch 12/137 Summary ══╗
║ Validation Loss: 1.8163 ║
║ Accuracy: 50.59% ║
╚═════════════════════════╝
─────────────────────────── Epoch 13/137 - Training ────────────────────────────
Epoch-Loss: 561.1261
────────────────────────── Epoch 13/137 - Validation ───────────────────────────
╔═ Epoch 13/137 Summary ══╗
║ Validation Loss: 1.7701 ║
║ Accuracy: 52.08% ║
╚═════════════════════════╝
─────────────────────────── Epoch 14/137 - Training ────────────────────────────
Epoch-Loss: 550.1468
────────────────────────── Epoch 14/137 - Validation ───────────────────────────
╔═ Epoch 14/137 Summary ══╗
║ Validation Loss: 1.6838 ║
║ Accuracy: 54.11% ║
╚═════════════════════════╝
─────────────────────────── Epoch 15/137 - Training ────────────────────────────
Epoch-Loss: 538.9441
────────────────────────── Epoch 15/137 - Validation ───────────────────────────
╔═ Epoch 15/137 Summary ══╗
║ Validation Loss: 1.7174 ║
║ Accuracy: 53.17% ║
╚═════════════════════════╝
─────────────────────────── Epoch 16/137 - Training ────────────────────────────
Epoch-Loss: 529.4189
────────────────────────── Epoch 16/137 - Validation ───────────────────────────
╔═ Epoch 16/137 Summary ══╗
║ Validation Loss: 1.7949 ║
║ Accuracy: 52.08% ║
╚═════════════════════════╝
─────────────────────────── Epoch 17/137 - Training ────────────────────────────
Epoch-Loss: 517.3839
────────────────────────── Epoch 17/137 - Validation ───────────────────────────
╔═ Epoch 17/137 Summary ══╗
║ Validation Loss: 1.6868 ║
║ Accuracy: 54.63% ║
╚═════════════════════════╝
─────────────────────────── Epoch 18/137 - Training ────────────────────────────
Epoch-Loss: 508.9138
────────────────────────── Epoch 18/137 - Validation ───────────────────────────
╔═ Epoch 18/137 Summary ══╗
║ Validation Loss: 1.6939 ║
║ Accuracy: 54.68% ║
╚═════════════════════════╝
─────────────────────────── Epoch 19/137 - Training ────────────────────────────
Epoch-Loss: 500.3567
────────────────────────── Epoch 19/137 - Validation ───────────────────────────
╔═ Epoch 19/137 Summary ══╗
║ Validation Loss: 1.6473 ║
║ Accuracy: 55.01% ║
╚═════════════════════════╝
─────────────────────────── Epoch 20/137 - Training ────────────────────────────
Epoch-Loss: 492.4355
────────────────────────── Epoch 20/137 - Validation ───────────────────────────
╔═ Epoch 20/137 Summary ══╗
║ Validation Loss: 1.7291 ║
║ Accuracy: 53.84% ║
╚═════════════════════════╝
─────────────────────────── Epoch 21/137 - Training ────────────────────────────
Epoch-Loss: 483.6163
────────────────────────── Epoch 21/137 - Validation ───────────────────────────
╔═ Epoch 21/137 Summary ══╗
║ Validation Loss: 1.7249 ║
║ Accuracy: 53.88% ║
╚═════════════════════════╝
─────────────────────────── Epoch 22/137 - Training ────────────────────────────
Epoch-Loss: 477.4168
────────────────────────── Epoch 22/137 - Validation ───────────────────────────
╔═ Epoch 22/137 Summary ══╗
║ Validation Loss: 1.6632 ║
║ Accuracy: 55.60% ║
╚═════════════════════════╝
─────────────────────────── Epoch 23/137 - Training ────────────────────────────
Epoch-Loss: 469.2535
────────────────────────── Epoch 23/137 - Validation ───────────────────────────
╔═ Epoch 23/137 Summary ══╗
║ Validation Loss: 1.6087 ║
║ Accuracy: 56.39% ║
╚═════════════════════════╝
─────────────────────────── Epoch 24/137 - Training ────────────────────────────
Epoch-Loss: 462.1354
────────────────────────── Epoch 24/137 - Validation ───────────────────────────
╔═ Epoch 24/137 Summary ══╗
║ Validation Loss: 1.5599 ║
║ Accuracy: 57.33% ║
╚═════════════════════════╝
─────────────────────────── Epoch 25/137 - Training ────────────────────────────
Epoch-Loss: 456.9553
────────────────────────── Epoch 25/137 - Validation ───────────────────────────
╔═ Epoch 25/137 Summary ══╗
║ Validation Loss: 1.8199 ║
║ Accuracy: 52.85% ║
╚═════════════════════════╝
─────────────────────────── Epoch 26/137 - Training ────────────────────────────
Epoch-Loss: 452.1211
────────────────────────── Epoch 26/137 - Validation ───────────────────────────
╔═ Epoch 26/137 Summary ══╗
║ Validation Loss: 1.5737 ║
║ Accuracy: 57.32% ║
╚═════════════════════════╝
─────────────────────────── Epoch 27/137 - Training ────────────────────────────
Epoch-Loss: 448.5129
────────────────────────── Epoch 27/137 - Validation ───────────────────────────
╔═ Epoch 27/137 Summary ══╗
║ Validation Loss: 1.5933 ║
║ Accuracy: 57.62% ║
╚═════════════════════════╝
─────────────────────────── Epoch 28/137 - Training ────────────────────────────
Epoch-Loss: 439.7047
────────────────────────── Epoch 28/137 - Validation ───────────────────────────
╔═ Epoch 28/137 Summary ══╗
║ Validation Loss: 1.5445 ║
║ Accuracy: 58.34% ║
╚═════════════════════════╝
─────────────────────────── Epoch 29/137 - Training ────────────────────────────
Epoch-Loss: 436.0724
────────────────────────── Epoch 29/137 - Validation ───────────────────────────
╔═ Epoch 29/137 Summary ══╗
║ Validation Loss: 1.5832 ║
║ Accuracy: 57.25% ║
╚═════════════════════════╝
─────────────────────────── Epoch 30/137 - Training ────────────────────────────
Epoch-Loss: 432.7618
────────────────────────── Epoch 30/137 - Validation ───────────────────────────
╔═ Epoch 30/137 Summary ══╗
║ Validation Loss: 1.5849 ║
║ Accuracy: 57.22% ║
╚═════════════════════════╝
─────────────────────────── Epoch 31/137 - Training ────────────────────────────
Epoch-Loss: 384.0292
────────────────────────── Epoch 31/137 - Validation ───────────────────────────
╔═ Epoch 31/137 Summary ══╗
║ Validation Loss: 1.4313 ║
║ Accuracy: 60.61% ║
╚═════════════════════════╝
─────────────────────────── Epoch 32/137 - Training ────────────────────────────
Epoch-Loss: 367.1518
────────────────────────── Epoch 32/137 - Validation ───────────────────────────
╔═ Epoch 32/137 Summary ══╗
║ Validation Loss: 1.4223 ║
║ Accuracy: 61.16% ║
╚═════════════════════════╝
─────────────────────────── Epoch 33/137 - Training ────────────────────────────
Epoch-Loss: 361.4818
────────────────────────── Epoch 33/137 - Validation ───────────────────────────
╔═ Epoch 33/137 Summary ══╗
║ Validation Loss: 1.4244 ║
║ Accuracy: 61.28% ║
╚═════════════════════════╝
─────────────────────────── Epoch 34/137 - Training ────────────────────────────
Epoch-Loss: 356.4864
────────────────────────── Epoch 34/137 - Validation ───────────────────────────
╔═ Epoch 34/137 Summary ══╗
║ Validation Loss: 1.4198 ║
║ Accuracy: 61.43% ║
╚═════════════════════════╝
─────────────────────────── Epoch 35/137 - Training ────────────────────────────
Epoch-Loss: 352.7127
────────────────────────── Epoch 35/137 - Validation ───────────────────────────
╔═ Epoch 35/137 Summary ══╗
║ Validation Loss: 1.4117 ║
║ Accuracy: 61.44% ║
╚═════════════════════════╝
─────────────────────────── Epoch 36/137 - Training ────────────────────────────
Epoch-Loss: 348.7639
────────────────────────── Epoch 36/137 - Validation ───────────────────────────
╔═ Epoch 36/137 Summary ══╗
║ Validation Loss: 1.4143 ║
║ Accuracy: 61.65% ║
╚═════════════════════════╝
─────────────────────────── Epoch 37/137 - Training ────────────────────────────
Epoch-Loss: 347.1741
────────────────────────── Epoch 37/137 - Validation ───────────────────────────
╔═ Epoch 37/137 Summary ══╗
║ Validation Loss: 1.4125 ║
║ Accuracy: 61.62% ║
╚═════════════════════════╝
─────────────────────────── Epoch 38/137 - Training ────────────────────────────
Epoch-Loss: 341.6663
────────────────────────── Epoch 38/137 - Validation ───────────────────────────
╔═ Epoch 38/137 Summary ══╗
║ Validation Loss: 1.4039 ║
║ Accuracy: 61.88% ║
╚═════════════════════════╝
─────────────────────────── Epoch 39/137 - Training ────────────────────────────
Epoch-Loss: 340.2318
────────────────────────── Epoch 39/137 - Validation ───────────────────────────
╔═ Epoch 39/137 Summary ══╗
║ Validation Loss: 1.4072 ║
║ Accuracy: 61.96% ║
╚═════════════════════════╝
─────────────────────────── Epoch 40/137 - Training ────────────────────────────
Epoch-Loss: 339.6578
────────────────────────── Epoch 40/137 - Validation ───────────────────────────
╔═ Epoch 40/137 Summary ══╗
║ Validation Loss: 1.4050 ║
║ Accuracy: 61.63% ║
╚═════════════════════════╝
─────────────────────────── Epoch 41/137 - Training ────────────────────────────
Epoch-Loss: 334.9623
────────────────────────── Epoch 41/137 - Validation ───────────────────────────
╔═ Epoch 41/137 Summary ══╗
║ Validation Loss: 1.4044 ║
║ Accuracy: 61.89% ║
╚═════════════════════════╝
─────────────────────────── Epoch 42/137 - Training ────────────────────────────
Epoch-Loss: 334.0733
────────────────────────── Epoch 42/137 - Validation ───────────────────────────
╔═ Epoch 42/137 Summary ══╗
║ Validation Loss: 1.4026 ║
║ Accuracy: 62.01% ║
╚═════════════════════════╝
─────────────────────────── Epoch 43/137 - Training ────────────────────────────
Epoch-Loss: 333.0352
────────────────────────── Epoch 43/137 - Validation ───────────────────────────
╔═ Epoch 43/137 Summary ══╗
║ Validation Loss: 1.4014 ║
║ Accuracy: 61.88% ║
╚═════════════════════════╝
─────────────────────────── Epoch 44/137 - Training ────────────────────────────
Epoch-Loss: 327.8350
────────────────────────── Epoch 44/137 - Validation ───────────────────────────
╔═ Epoch 44/137 Summary ══╗
║ Validation Loss: 1.4094 ║
║ Accuracy: 61.89% ║
╚═════════════════════════╝
─────────────────────────── Epoch 45/137 - Training ────────────────────────────
Epoch-Loss: 327.9124
────────────────────────── Epoch 45/137 - Validation ───────────────────────────
╔═ Epoch 45/137 Summary ══╗
║ Validation Loss: 1.3972 ║
║ Accuracy: 61.92% ║
╚═════════════════════════╝
─────────────────────────── Epoch 46/137 - Training ────────────────────────────
Epoch-Loss: 324.9241
────────────────────────── Epoch 46/137 - Validation ───────────────────────────
╔═ Epoch 46/137 Summary ══╗
║ Validation Loss: 1.4033 ║
║ Accuracy: 61.98% ║
╚═════════════════════════╝
─────────────────────────── Epoch 47/137 - Training ────────────────────────────
Epoch-Loss: 322.0280
────────────────────────── Epoch 47/137 - Validation ───────────────────────────
╔═ Epoch 47/137 Summary ══╗
║ Validation Loss: 1.4080 ║
║ Accuracy: 61.69% ║
╚═════════════════════════╝
─────────────────────────── Epoch 48/137 - Training ────────────────────────────
Epoch-Loss: 323.0381
────────────────────────── Epoch 48/137 - Validation ───────────────────────────
╔═ Epoch 48/137 Summary ══╗
║ Validation Loss: 1.3971 ║
║ Accuracy: 62.02% ║
╚═════════════════════════╝
─────────────────────────── Epoch 49/137 - Training ────────────────────────────
Epoch-Loss: 318.1134
────────────────────────── Epoch 49/137 - Validation ───────────────────────────
╔═ Epoch 49/137 Summary ══╗
║ Validation Loss: 1.3994 ║
║ Accuracy: 62.02% ║
╚═════════════════════════╝
─────────────────────────── Epoch 50/137 - Training ────────────────────────────
Epoch-Loss: 317.0238
────────────────────────── Epoch 50/137 - Validation ───────────────────────────
╔═ Epoch 50/137 Summary ══╗
║ Validation Loss: 1.3970 ║
║ Accuracy: 62.16% ║
╚═════════════════════════╝
─────────────────────────── Epoch 51/137 - Training ────────────────────────────
Epoch-Loss: 312.5500
────────────────────────── Epoch 51/137 - Validation ───────────────────────────
╔═ Epoch 51/137 Summary ══╗
║ Validation Loss: 1.4031 ║
║ Accuracy: 62.08% ║
╚═════════════════════════╝
─────────────────────────── Epoch 52/137 - Training ────────────────────────────
Epoch-Loss: 314.4675
────────────────────────── Epoch 52/137 - Validation ───────────────────────────
╔═ Epoch 52/137 Summary ══╗
║ Validation Loss: 1.4022 ║
║ Accuracy: 62.01% ║
╚═════════════════════════╝
─────────────────────────── Epoch 53/137 - Training ────────────────────────────
Epoch-Loss: 311.1006
────────────────────────── Epoch 53/137 - Validation ───────────────────────────
╔═ Epoch 53/137 Summary ══╗
║ Validation Loss: 1.3939 ║
║ Accuracy: 62.38% ║
╚═════════════════════════╝
─────────────────────────── Epoch 54/137 - Training ────────────────────────────
Epoch-Loss: 310.7068
────────────────────────── Epoch 54/137 - Validation ───────────────────────────
╔═ Epoch 54/137 Summary ══╗
║ Validation Loss: 1.3922 ║
║ Accuracy: 62.21% ║
╚═════════════════════════╝
─────────────────────────── Epoch 55/137 - Training ────────────────────────────
Epoch-Loss: 307.8408
────────────────────────── Epoch 55/137 - Validation ───────────────────────────
╔═ Epoch 55/137 Summary ══╗
║ Validation Loss: 1.4026 ║
║ Accuracy: 62.35% ║
╚═════════════════════════╝
─────────────────────────── Epoch 56/137 - Training ────────────────────────────
Epoch-Loss: 306.3413
────────────────────────── Epoch 56/137 - Validation ───────────────────────────
╔═ Epoch 56/137 Summary ══╗
║ Validation Loss: 1.4029 ║
║ Accuracy: 62.34% ║
╚═════════════════════════╝
─────────────────────────── Epoch 57/137 - Training ────────────────────────────
Epoch-Loss: 304.0355
────────────────────────── Epoch 57/137 - Validation ───────────────────────────
╔═ Epoch 57/137 Summary ══╗
║ Validation Loss: 1.3911 ║
║ Accuracy: 62.38% ║
╚═════════════════════════╝
─────────────────────────── Epoch 58/137 - Training ────────────────────────────
Epoch-Loss: 301.9699
────────────────────────── Epoch 58/137 - Validation ───────────────────────────
╔═ Epoch 58/137 Summary ══╗
║ Validation Loss: 1.3942 ║
║ Accuracy: 62.91% ║
╚═════════════════════════╝
─────────────────────────── Epoch 59/137 - Training ────────────────────────────
Epoch-Loss: 301.4880
────────────────────────── Epoch 59/137 - Validation ───────────────────────────
╔═ Epoch 59/137 Summary ══╗
║ Validation Loss: 1.3907 ║
║ Accuracy: 62.58% ║
╚═════════════════════════╝
─────────────────────────── Epoch 60/137 - Training ────────────────────────────
Epoch-Loss: 300.0900
────────────────────────── Epoch 60/137 - Validation ───────────────────────────
╔═ Epoch 60/137 Summary ══╗
║ Validation Loss: 1.3986 ║
║ Accuracy: 62.41% ║
╚═════════════════════════╝
─────────────────────────── Epoch 61/137 - Training ────────────────────────────
Epoch-Loss: 291.1938
────────────────────────── Epoch 61/137 - Validation ───────────────────────────
╔═ Epoch 61/137 Summary ══╗
║ Validation Loss: 1.3856 ║
║ Accuracy: 62.65% ║
╚═════════════════════════╝
─────────────────────────── Epoch 62/137 - Training ────────────────────────────
Epoch-Loss: 289.2841
────────────────────────── Epoch 62/137 - Validation ───────────────────────────
╔═ Epoch 62/137 Summary ══╗
║ Validation Loss: 1.3818 ║
║ Accuracy: 62.59% ║
╚═════════════════════════╝
─────────────────────────── Epoch 63/137 - Training ────────────────────────────
Epoch-Loss: 289.3275
────────────────────────── Epoch 63/137 - Validation ───────────────────────────
╔═ Epoch 63/137 Summary ══╗
║ Validation Loss: 1.3832 ║
║ Accuracy: 62.70% ║
╚═════════════════════════╝
─────────────────────────── Epoch 64/137 - Training ────────────────────────────
Epoch-Loss: 289.8438
────────────────────────── Epoch 64/137 - Validation ───────────────────────────
╔═ Epoch 64/137 Summary ══╗
║ Validation Loss: 1.3892 ║
║ Accuracy: 62.59% ║
╚═════════════════════════╝
─────────────────────────── Epoch 65/137 - Training ────────────────────────────
Epoch-Loss: 287.6091
────────────────────────── Epoch 65/137 - Validation ───────────────────────────
╔═ Epoch 65/137 Summary ══╗
║ Validation Loss: 1.3861 ║
║ Accuracy: 62.75% ║
╚═════════════════════════╝
─────────────────────────── Epoch 66/137 - Training ────────────────────────────
Epoch-Loss: 288.2812
────────────────────────── Epoch 66/137 - Validation ───────────────────────────
╔═ Epoch 66/137 Summary ══╗
║ Validation Loss: 1.3847 ║
║ Accuracy: 62.69% ║
╚═════════════════════════╝
─────────────────────────── Epoch 67/137 - Training ────────────────────────────
Epoch-Loss: 286.9757
────────────────────────── Epoch 67/137 - Validation ───────────────────────────
╔═ Epoch 67/137 Summary ══╗
║ Validation Loss: 1.3852 ║
║ Accuracy: 62.69% ║
╚═════════════════════════╝
─────────────────────────── Epoch 68/137 - Training ────────────────────────────
Epoch-Loss: 288.9608
────────────────────────── Epoch 68/137 - Validation ───────────────────────────
╔═ Epoch 68/137 Summary ══╗
║ Validation Loss: 1.3837 ║
║ Accuracy: 62.74% ║
╚═════════════════════════╝
─────────────────────────── Epoch 69/137 - Training ────────────────────────────
Epoch-Loss: 287.2954
────────────────────────── Epoch 69/137 - Validation ───────────────────────────
╔═ Epoch 69/137 Summary ══╗
║ Validation Loss: 1.3837 ║
║ Accuracy: 62.68% ║
╚═════════════════════════╝
─────────────────────────── Epoch 70/137 - Training ────────────────────────────
Epoch-Loss: 284.5414
────────────────────────── Epoch 70/137 - Validation ───────────────────────────
╔═ Epoch 70/137 Summary ══╗
║ Validation Loss: 1.3890 ║
║ Accuracy: 62.70% ║
╚═════════════════════════╝
─────────────────────────── Epoch 71/137 - Training ────────────────────────────
Epoch-Loss: 285.9007
────────────────────────── Epoch 71/137 - Validation ───────────────────────────
╔═ Epoch 71/137 Summary ══╗
║ Validation Loss: 1.3841 ║
║ Accuracy: 62.84% ║
╚═════════════════════════╝
─────────────────────────── Epoch 72/137 - Training ────────────────────────────
Epoch-Loss: 287.0506
────────────────────────── Epoch 72/137 - Validation ───────────────────────────
╔═ Epoch 72/137 Summary ══╗
║ Validation Loss: 1.3876 ║
║ Accuracy: 62.59% ║
╚═════════════════════════╝
─────────────────────────── Epoch 73/137 - Training ────────────────────────────
Epoch-Loss: 285.1766
────────────────────────── Epoch 73/137 - Validation ───────────────────────────
╔═ Epoch 73/137 Summary ══╗
║ Validation Loss: 1.3832 ║
║ Accuracy: 62.81% ║
╚═════════════════════════╝
─────────────────────────── Epoch 74/137 - Training ────────────────────────────
Epoch-Loss: 282.9728
────────────────────────── Epoch 74/137 - Validation ───────────────────────────
╔═ Epoch 74/137 Summary ══╗
║ Validation Loss: 1.3861 ║
║ Accuracy: 62.61% ║
╚═════════════════════════╝
─────────────────────────── Epoch 75/137 - Training ────────────────────────────
Epoch-Loss: 284.2289
────────────────────────── Epoch 75/137 - Validation ───────────────────────────
╔═ Epoch 75/137 Summary ══╗
║ Validation Loss: 1.3824 ║
║ Accuracy: 62.76% ║
╚═════════════════════════╝
─────────────────────────── Epoch 76/137 - Training ────────────────────────────
Epoch-Loss: 284.2285
────────────────────────── Epoch 76/137 - Validation ───────────────────────────
╔═ Epoch 76/137 Summary ══╗
║ Validation Loss: 1.3863 ║
║ Accuracy: 62.64% ║
╚═════════════════════════╝
─────────────────────────── Epoch 77/137 - Training ────────────────────────────
Epoch-Loss: 283.8855
────────────────────────── Epoch 77/137 - Validation ───────────────────────────
╔═ Epoch 77/137 Summary ══╗
║ Validation Loss: 1.3846 ║
║ Accuracy: 62.65% ║
╚═════════════════════════╝
─────────────────────────── Epoch 78/137 - Training ────────────────────────────
Epoch-Loss: 282.9997
────────────────────────── Epoch 78/137 - Validation ───────────────────────────
╔═ Epoch 78/137 Summary ══╗
║ Validation Loss: 1.3831 ║
║ Accuracy: 62.80% ║
╚═════════════════════════╝
─────────────────────────── Epoch 79/137 - Training ────────────────────────────
Epoch-Loss: 284.3001
────────────────────────── Epoch 79/137 - Validation ───────────────────────────
╔═ Epoch 79/137 Summary ══╗
║ Validation Loss: 1.3827 ║
║ Accuracy: 62.77% ║
╚═════════════════════════╝
─────────────────────────── Epoch 80/137 - Training ────────────────────────────
Epoch-Loss: 284.8013
────────────────────────── Epoch 80/137 - Validation ───────────────────────────
╔═ Epoch 80/137 Summary ══╗
║ Validation Loss: 1.3820 ║
║ Accuracy: 62.80% ║
╚═════════════════════════╝
─────────────────────────── Epoch 81/137 - Training ────────────────────────────
Epoch-Loss: 283.8976
────────────────────────── Epoch 81/137 - Validation ───────────────────────────
╔═ Epoch 81/137 Summary ══╗
║ Validation Loss: 1.3838 ║
║ Accuracy: 62.61% ║
╚═════════════════════════╝
─────────────────────────── Epoch 82/137 - Training ────────────────────────────
Epoch-Loss: 282.1944
────────────────────────── Epoch 82/137 - Validation ───────────────────────────
╔═ Epoch 82/137 Summary ══╗
║ Validation Loss: 1.3832 ║
║ Accuracy: 62.89% ║
╚═════════════════════════╝
─────────────────────────── Epoch 83/137 - Training ────────────────────────────
Epoch-Loss: 280.9514
────────────────────────── Epoch 83/137 - Validation ───────────────────────────
╔═ Epoch 83/137 Summary ══╗
║ Validation Loss: 1.3848 ║
║ Accuracy: 62.78% ║
╚═════════════════════════╝
─────────────────────────── Epoch 84/137 - Training ────────────────────────────
Epoch-Loss: 284.0250
────────────────────────── Epoch 84/137 - Validation ───────────────────────────
╔═ Epoch 84/137 Summary ══╗
║ Validation Loss: 1.3826 ║
║ Accuracy: 63.07% ║
╚═════════════════════════╝
─────────────────────────── Epoch 85/137 - Training ────────────────────────────
Epoch-Loss: 281.2117
────────────────────────── Epoch 85/137 - Validation ───────────────────────────
╔═ Epoch 85/137 Summary ══╗
║ Validation Loss: 1.3846 ║
║ Accuracy: 62.77% ║
╚═════════════════════════╝
─────────────────────────── Epoch 86/137 - Training ────────────────────────────
Epoch-Loss: 281.7995
────────────────────────── Epoch 86/137 - Validation ───────────────────────────
╔═ Epoch 86/137 Summary ══╗
║ Validation Loss: 1.3848 ║
║ Accuracy: 62.98% ║
╚═════════════════════════╝
─────────────────────────── Epoch 87/137 - Training ────────────────────────────
Epoch-Loss: 282.2893
────────────────────────── Epoch 87/137 - Validation ───────────────────────────
╔═ Epoch 87/137 Summary ══╗
║ Validation Loss: 1.3853 ║
║ Accuracy: 62.83% ║
╚═════════════════════════╝
─────────────────────────── Epoch 88/137 - Training ────────────────────────────
Epoch-Loss: 281.8202
────────────────────────── Epoch 88/137 - Validation ───────────────────────────
╔═ Epoch 88/137 Summary ══╗
║ Validation Loss: 1.3824 ║
║ Accuracy: 62.95% ║
╚═════════════════════════╝
─────────────────────────── Epoch 89/137 - Training ────────────────────────────
Epoch-Loss: 281.2617
────────────────────────── Epoch 89/137 - Validation ───────────────────────────
╔═ Epoch 89/137 Summary ══╗
║ Validation Loss: 1.3831 ║
║ Accuracy: 62.85% ║
╚═════════════════════════╝
─────────────────────────── Epoch 90/137 - Training ────────────────────────────
Epoch-Loss: 282.2576
────────────────────────── Epoch 90/137 - Validation ───────────────────────────
╔═ Epoch 90/137 Summary ══╗
║ Validation Loss: 1.3793 ║
║ Accuracy: 63.02% ║
╚═════════════════════════╝
─────────────────────────── Epoch 91/137 - Training ────────────────────────────
Epoch-Loss: 279.4359
────────────────────────── Epoch 91/137 - Validation ───────────────────────────
╔═ Epoch 91/137 Summary ══╗
║ Validation Loss: 1.3818 ║
║ Accuracy: 62.85% ║
╚═════════════════════════╝
─────────────────────────── Epoch 92/137 - Training ────────────────────────────
Epoch-Loss: 278.7292
────────────────────────── Epoch 92/137 - Validation ───────────────────────────
╔═ Epoch 92/137 Summary ══╗
║ Validation Loss: 1.3812 ║
║ Accuracy: 62.87% ║
╚═════════════════════════╝
─────────────────────────── Epoch 93/137 - Training ────────────────────────────
Epoch-Loss: 281.3486
────────────────────────── Epoch 93/137 - Validation ───────────────────────────
╔═ Epoch 93/137 Summary ══╗
║ Validation Loss: 1.3787 ║
║ Accuracy: 62.80% ║
╚═════════════════════════╝
─────────────────────────── Epoch 94/137 - Training ────────────────────────────
Epoch-Loss: 280.0671
────────────────────────── Epoch 94/137 - Validation ───────────────────────────
╔═ Epoch 94/137 Summary ══╗
║ Validation Loss: 1.3836 ║
║ Accuracy: 62.82% ║
╚═════════════════════════╝
─────────────────────────── Epoch 95/137 - Training ────────────────────────────
Epoch-Loss: 279.8772
────────────────────────── Epoch 95/137 - Validation ───────────────────────────
╔═ Epoch 95/137 Summary ══╗
║ Validation Loss: 1.3796 ║
║ Accuracy: 62.94% ║
╚═════════════════════════╝
─────────────────────────── Epoch 96/137 - Training ────────────────────────────
Epoch-Loss: 279.1908
────────────────────────── Epoch 96/137 - Validation ───────────────────────────
╔═ Epoch 96/137 Summary ══╗
║ Validation Loss: 1.3821 ║
║ Accuracy: 62.82% ║
╚═════════════════════════╝
─────────────────────────── Epoch 97/137 - Training ────────────────────────────
Epoch-Loss: 279.2941
────────────────────────── Epoch 97/137 - Validation ───────────────────────────
╔═ Epoch 97/137 Summary ══╗
║ Validation Loss: 1.3836 ║
║ Accuracy: 62.86% ║
╚═════════════════════════╝
─────────────────────────── Epoch 98/137 - Training ────────────────────────────
Epoch-Loss: 279.7676
────────────────────────── Epoch 98/137 - Validation ───────────────────────────
╔═ Epoch 98/137 Summary ══╗
║ Validation Loss: 1.3802 ║
║ Accuracy: 62.88% ║
╚═════════════════════════╝
─────────────────────────── Epoch 99/137 - Training ────────────────────────────
Epoch-Loss: 279.9686
────────────────────────── Epoch 99/137 - Validation ───────────────────────────
╔═ Epoch 99/137 Summary ══╗
║ Validation Loss: 1.3832 ║
║ Accuracy: 62.88% ║
╚═════════════════════════╝
─────────────────────────── Epoch 100/137 - Training ───────────────────────────
Epoch-Loss: 277.9478
────────────────────────── Epoch 100/137 - Validation ──────────────────────────
╔═ Epoch 100/137 Summary ═╗
║ Validation Loss: 1.3813 ║
║ Accuracy: 62.84% ║
╚═════════════════════════╝
─────────────────────────── Epoch 101/137 - Training ───────────────────────────
Epoch-Loss: 280.0325
────────────────────────── Epoch 101/137 - Validation ──────────────────────────
╔═ Epoch 101/137 Summary ═╗
║ Validation Loss: 1.3807 ║
║ Accuracy: 62.93% ║
╚═════════════════════════╝
─────────────────────────── Epoch 102/137 - Training ───────────────────────────
Epoch-Loss: 278.7748
────────────────────────── Epoch 102/137 - Validation ──────────────────────────
╔═ Epoch 102/137 Summary ═╗
║ Validation Loss: 1.3815 ║
║ Accuracy: 63.07% ║
╚═════════════════════════╝
─────────────────────────── Epoch 103/137 - Training ───────────────────────────
Epoch-Loss: 277.9785
────────────────────────── Epoch 103/137 - Validation ──────────────────────────
╔═ Epoch 103/137 Summary ═╗
║ Validation Loss: 1.3811 ║
║ Accuracy: 62.92% ║
╚═════════════════════════╝
─────────────────────────── Epoch 104/137 - Training ───────────────────────────
Epoch-Loss: 280.1632
────────────────────────── Epoch 104/137 - Validation ──────────────────────────
╔═ Epoch 104/137 Summary ═╗
║ Validation Loss: 1.3826 ║
║ Accuracy: 62.98% ║
╚═════════════════════════╝
─────────────────────────── Epoch 105/137 - Training ───────────────────────────
Epoch-Loss: 279.4371
────────────────────────── Epoch 105/137 - Validation ──────────────────────────
╔═ Epoch 105/137 Summary ═╗
║ Validation Loss: 1.3848 ║
║ Accuracy: 62.90% ║
╚═════════════════════════╝
─────────────────────────── Epoch 106/137 - Training ───────────────────────────
Epoch-Loss: 279.7615
────────────────────────── Epoch 106/137 - Validation ──────────────────────────
╔═ Epoch 106/137 Summary ═╗
║ Validation Loss: 1.3776 ║
║ Accuracy: 62.98% ║
╚═════════════════════════╝
─────────────────────────── Epoch 107/137 - Training ───────────────────────────
Epoch-Loss: 278.4789
────────────────────────── Epoch 107/137 - Validation ──────────────────────────
╔═ Epoch 107/137 Summary ═╗
║ Validation Loss: 1.3809 ║
║ Accuracy: 62.94% ║
╚═════════════════════════╝
─────────────────────────── Epoch 108/137 - Training ───────────────────────────
Epoch-Loss: 280.9931
────────────────────────── Epoch 108/137 - Validation ──────────────────────────
╔═ Epoch 108/137 Summary ═╗
║ Validation Loss: 1.3793 ║
║ Accuracy: 62.97% ║
╚═════════════════════════╝
─────────────────────────── Epoch 109/137 - Training ───────────────────────────
Epoch-Loss: 279.8100
────────────────────────── Epoch 109/137 - Validation ──────────────────────────
╔═ Epoch 109/137 Summary ═╗
║ Validation Loss: 1.3827 ║
║ Accuracy: 62.92% ║
╚═════════════════════════╝
─────────────────────────── Epoch 110/137 - Training ───────────────────────────
Epoch-Loss: 279.5861
────────────────────────── Epoch 110/137 - Validation ──────────────────────────
╔═ Epoch 110/137 Summary ═╗
║ Validation Loss: 1.3831 ║
║ Accuracy: 62.78% ║
╚═════════════════════════╝
─────────────────────────── Epoch 111/137 - Training ───────────────────────────
Epoch-Loss: 281.2415
────────────────────────── Epoch 111/137 - Validation ──────────────────────────
╔═ Epoch 111/137 Summary ═╗
║ Validation Loss: 1.3820 ║
║ Accuracy: 62.86% ║
╚═════════════════════════╝
─────────────────────────── Epoch 112/137 - Training ───────────────────────────
Epoch-Loss: 278.0929
────────────────────────── Epoch 112/137 - Validation ──────────────────────────
╔═ Epoch 112/137 Summary ═╗
║ Validation Loss: 1.3853 ║
║ Accuracy: 62.92% ║
╚═════════════════════════╝
─────────────────────────── Epoch 113/137 - Training ───────────────────────────
Epoch-Loss: 278.9290
────────────────────────── Epoch 113/137 - Validation ──────────────────────────
╔═ Epoch 113/137 Summary ═╗
║ Validation Loss: 1.3789 ║
║ Accuracy: 62.98% ║
╚═════════════════════════╝
─────────────────────────── Epoch 114/137 - Training ───────────────────────────
Epoch-Loss: 278.8266
────────────────────────── Epoch 114/137 - Validation ──────────────────────────
╔═ Epoch 114/137 Summary ═╗
║ Validation Loss: 1.3822 ║
║ Accuracy: 62.87% ║
╚═════════════════════════╝
─────────────────────────── Epoch 115/137 - Training ───────────────────────────
Epoch-Loss: 280.8993
────────────────────────── Epoch 115/137 - Validation ──────────────────────────
╔═ Epoch 115/137 Summary ═╗
║ Validation Loss: 1.3859 ║
║ Accuracy: 62.94% ║
╚═════════════════════════╝
─────────────────────────── Epoch 116/137 - Training ───────────────────────────
Epoch-Loss: 277.9550
────────────────────────── Epoch 116/137 - Validation ──────────────────────────
╔═ Epoch 116/137 Summary ═╗
║ Validation Loss: 1.3854 ║
║ Accuracy: 62.83% ║
╚═════════════════════════╝
─────────────────────────── Epoch 117/137 - Training ───────────────────────────
Epoch-Loss: 277.2556
────────────────────────── Epoch 117/137 - Validation ──────────────────────────
╔═ Epoch 117/137 Summary ═╗
║ Validation Loss: 1.3822 ║
║ Accuracy: 62.87% ║
╚═════════════════════════╝
─────────────────────────── Epoch 118/137 - Training ───────────────────────────
Epoch-Loss: 280.0439
────────────────────────── Epoch 118/137 - Validation ──────────────────────────
╔═ Epoch 118/137 Summary ═╗
║ Validation Loss: 1.3811 ║
║ Accuracy: 62.81% ║
╚═════════════════════════╝
─────────────────────────── Epoch 119/137 - Training ───────────────────────────
Epoch-Loss: 277.6602
────────────────────────── Epoch 119/137 - Validation ──────────────────────────
╔═ Epoch 119/137 Summary ═╗
║ Validation Loss: 1.3830 ║
║ Accuracy: 62.85% ║
╚═════════════════════════╝
─────────────────────────── Epoch 120/137 - Training ───────────────────────────
Epoch-Loss: 280.3741
────────────────────────── Epoch 120/137 - Validation ──────────────────────────
╔═ Epoch 120/137 Summary ═╗
║ Validation Loss: 1.3840 ║
║ Accuracy: 62.94% ║
╚═════════════════════════╝
─────────────────────────── Epoch 121/137 - Training ───────────────────────────
Epoch-Loss: 279.0567
────────────────────────── Epoch 121/137 - Validation ──────────────────────────
╔═ Epoch 121/137 Summary ═╗
║ Validation Loss: 1.3821 ║
║ Accuracy: 62.87% ║
╚═════════════════════════╝
─────────────────────────── Epoch 122/137 - Training ───────────────────────────
Epoch-Loss: 279.6274
────────────────────────── Epoch 122/137 - Validation ──────────────────────────
╔═ Epoch 122/137 Summary ═╗
║ Validation Loss: 1.3795 ║
║ Accuracy: 62.81% ║
╚═════════════════════════╝
─────────────────────────── Epoch 123/137 - Training ───────────────────────────
Epoch-Loss: 279.6142
────────────────────────── Epoch 123/137 - Validation ──────────────────────────
╔═ Epoch 123/137 Summary ═╗
║ Validation Loss: 1.3809 ║
║ Accuracy: 62.88% ║
╚═════════════════════════╝
─────────────────────────── Epoch 124/137 - Training ───────────────────────────
Epoch-Loss: 278.9749
────────────────────────── Epoch 124/137 - Validation ──────────────────────────
╔═ Epoch 124/137 Summary ═╗
║ Validation Loss: 1.3833 ║
║ Accuracy: 62.87% ║
╚═════════════════════════╝
─────────────────────────── Epoch 125/137 - Training ───────────────────────────
Epoch-Loss: 279.0552
────────────────────────── Epoch 125/137 - Validation ──────────────────────────
╔═ Epoch 125/137 Summary ═╗
║ Validation Loss: 1.3812 ║
║ Accuracy: 62.97% ║
╚═════════════════════════╝
─────────────────────────── Epoch 126/137 - Training ───────────────────────────
Epoch-Loss: 279.8402
────────────────────────── Epoch 126/137 - Validation ──────────────────────────
╔═ Epoch 126/137 Summary ═╗
║ Validation Loss: 1.3801 ║
║ Accuracy: 63.12% ║
╚═════════════════════════╝
─────────────────────────── Epoch 127/137 - Training ───────────────────────────
Epoch-Loss: 279.7925
────────────────────────── Epoch 127/137 - Validation ──────────────────────────
╔═ Epoch 127/137 Summary ═╗
║ Validation Loss: 1.3828 ║
║ Accuracy: 62.82% ║
╚═════════════════════════╝
─────────────────────────── Epoch 128/137 - Training ───────────────────────────
Epoch-Loss: 279.2967
────────────────────────── Epoch 128/137 - Validation ──────────────────────────
╔═ Epoch 128/137 Summary ═╗
║ Validation Loss: 1.3818 ║
║ Accuracy: 62.86% ║
╚═════════════════════════╝
─────────────────────────── Epoch 129/137 - Training ───────────────────────────
Epoch-Loss: 279.4259
────────────────────────── Epoch 129/137 - Validation ──────────────────────────
╔═ Epoch 129/137 Summary ═╗
║ Validation Loss: 1.3794 ║
║ Accuracy: 62.91% ║
╚═════════════════════════╝
─────────────────────────── Epoch 130/137 - Training ───────────────────────────
Epoch-Loss: 277.5841
────────────────────────── Epoch 130/137 - Validation ──────────────────────────
╔═ Epoch 130/137 Summary ═╗
║ Validation Loss: 1.3795 ║
║ Accuracy: 62.93% ║
╚═════════════════════════╝
─────────────────────────── Epoch 131/137 - Training ───────────────────────────
Epoch-Loss: 279.0193
────────────────────────── Epoch 131/137 - Validation ──────────────────────────
╔═ Epoch 131/137 Summary ═╗
║ Validation Loss: 1.3817 ║
║ Accuracy: 62.99% ║
╚═════════════════════════╝
─────────────────────────── Epoch 132/137 - Training ───────────────────────────
Epoch-Loss: 279.2967
────────────────────────── Epoch 132/137 - Validation ──────────────────────────
╔═ Epoch 132/137 Summary ═╗
║ Validation Loss: 1.3846 ║
║ Accuracy: 62.82% ║
╚═════════════════════════╝
─────────────────────────── Epoch 133/137 - Training ───────────────────────────
Epoch-Loss: 280.7961
────────────────────────── Epoch 133/137 - Validation ──────────────────────────
╔═ Epoch 133/137 Summary ═╗
║ Validation Loss: 1.3831 ║
║ Accuracy: 62.85% ║
╚═════════════════════════╝
─────────────────────────── Epoch 134/137 - Training ───────────────────────────
Epoch-Loss: 278.5390
────────────────────────── Epoch 134/137 - Validation ──────────────────────────
╔═ Epoch 134/137 Summary ═╗
║ Validation Loss: 1.3801 ║
║ Accuracy: 62.97% ║
╚═════════════════════════╝
─────────────────────────── Epoch 135/137 - Training ───────────────────────────
Epoch-Loss: 279.0554
────────────────────────── Epoch 135/137 - Validation ──────────────────────────
╔═ Epoch 135/137 Summary ═╗
║ Validation Loss: 1.3837 ║
║ Accuracy: 62.87% ║
╚═════════════════════════╝
─────────────────────────── Epoch 136/137 - Training ───────────────────────────
Epoch-Loss: 278.4543
────────────────────────── Epoch 136/137 - Validation ──────────────────────────
╔═ Epoch 136/137 Summary ═╗
║ Validation Loss: 1.3824 ║
║ Accuracy: 62.85% ║
╚═════════════════════════╝
─────────────────────────── Epoch 137/137 - Training ───────────────────────────
Epoch-Loss: 277.8851
────────────────────────── Epoch 137/137 - Validation ──────────────────────────
╔═ Epoch 137/137 Summary ═╗
║ Validation Loss: 1.3803 ║
║ Accuracy: 62.93% ║
╚═════════════════════════╝
VAL_LOSS: 1.3803089004296523
VAL_ACC: 62.93
RUNTIME: 1636.961
NORMALIZED_RUNTIME: 22.736
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': 62.93}
Final-results: {'VAL_ACC': 62.93}
EXIT_CODE: 0
submitit INFO (2025-10-31 15:31:43,499) - Job completed successfully
submitit INFO (2025-10-31 15:31:43,501) - Exiting after successful completion
