[I 2023-05-17 02:30:20,329] A new study created in memory with name: bins
[I 2023-05-17 02:31:48,083] Trial 0 finished with value: 0.36048880219459534 and parameters: {'embedding_dim': 4, 'step_size': 0.4123206532618726, 'batch_size': 24, 'num_bins': 61, 'bin_strategy': 'uniform', 'num_epochs': 5}. Best is trial 0 with value: 0.36048880219459534.
[I 2023-05-17 02:33:58,528] Trial 1 finished with value: 0.35097000002861023 and parameters: {'embedding_dim': 9, 'step_size': 0.10502105436744279, 'batch_size': 23, 'num_bins': 4, 'bin_strategy': 'uniform', 'num_epochs': 7}. Best is trial 1 with value: 0.35097000002861023.
[I 2023-05-17 02:40:40,921] Trial 2 finished with value: 0.3105776607990265 and parameters: {'embedding_dim': 2, 'step_size': 0.020492680115417352, 'batch_size': 11, 'num_bins': 53, 'bin_strategy': 'uniform', 'num_epochs': 11}. Best is trial 2 with value: 0.3105776607990265.
[I 2023-05-17 02:45:58,507] Trial 3 finished with value: 0.30633899569511414 and parameters: {'embedding_dim': 2, 'step_size': 0.03135775732257745, 'batch_size': 13, 'num_bins': 47, 'bin_strategy': 'uniform', 'num_epochs': 10}. Best is trial 3 with value: 0.30633899569511414.
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 2 are removed. Consider decreasing the number of bins.
warnings.warn(
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 3 are removed. Consider decreasing the number of bins.
warnings.warn(
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 4 are removed. Consider decreasing the number of bins.
warnings.warn(
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 5 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 02:51:06,519] Trial 4 finished with value: 0.32146045565605164 and parameters: {'embedding_dim': 6, 'step_size': 0.011992724522955167, 'batch_size': 20, 'num_bins': 18, 'bin_strategy': 'quantile', 'num_epochs': 15}. Best is trial 3 with value: 0.30633899569511414.
[I 2023-05-17 03:04:29,678] Trial 5 finished with value: 0.3089120388031006 and parameters: {'embedding_dim': 9, 'step_size': 0.032925293631105246, 'batch_size': 5, 'num_bins': 69, 'bin_strategy': 'uniform', 'num_epochs': 10}. Best is trial 3 with value: 0.30633899569511414.
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 0 are removed. Consider decreasing the number of bins.
warnings.warn(
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 2 are removed. Consider decreasing the number of bins.
warnings.warn(
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 3 are removed. Consider decreasing the number of bins.
warnings.warn(
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 4 are removed. Consider decreasing the number of bins.
warnings.warn(
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 5 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 03:08:36,422] Trial 6 pruned.
[I 2023-05-17 03:09:57,126] Trial 7 pruned.
[I 2023-05-17 03:12:11,602] Trial 8 pruned.
[I 2023-05-17 03:18:03,071] Trial 9 finished with value: 0.3057221472263336 and parameters: {'embedding_dim': 4, 'step_size': 0.030012301808980443, 'batch_size': 18, 'num_bins': 15, 'bin_strategy': 'uniform', 'num_epochs': 15}. Best is trial 9 with value: 0.3057221472263336.
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 3 are removed. Consider decreasing the number of bins.
warnings.warn(
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 4 are removed. Consider decreasing the number of bins.
warnings.warn(
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 5 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 03:18:16,684] Trial 10 pruned.
[I 2023-05-17 03:22:39,833] Trial 11 finished with value: 0.30919402837753296 and parameters: {'embedding_dim': 4, 'step_size': 0.04642647300540488, 'batch_size': 14, 'num_bins': 30, 'bin_strategy': 'uniform', 'num_epochs': 9}. Best is trial 9 with value: 0.3057221472263336.
[I 2023-05-17 03:26:09,676] Trial 12 finished with value: 0.3141358494758606 and parameters: {'embedding_dim': 4, 'step_size': 0.08128484055802063, 'batch_size': 16, 'num_bins': 36, 'bin_strategy': 'uniform', 'num_epochs': 8}. Best is trial 9 with value: 0.3057221472263336.
[I 2023-05-17 03:26:54,554] Trial 13 pruned.
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 2 are removed. Consider decreasing the number of bins.
warnings.warn(
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 3 are removed. Consider decreasing the number of bins.
warnings.warn(
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 4 are removed. Consider decreasing the number of bins.
warnings.warn(
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 5 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 03:28:24,068] Trial 14 pruned.
[I 2023-05-17 03:34:47,198] Trial 15 finished with value: 0.3047816753387451 and parameters: {'embedding_dim': 3, 'step_size': 0.044922957549390394, 'batch_size': 14, 'num_bins': 46, 'bin_strategy': 'uniform', 'num_epochs': 13}. Best is trial 15 with value: 0.3047816753387451.
[I 2023-05-17 03:36:42,706] Trial 16 pruned.
[I 2023-05-17 03:42:06,253] Trial 17 finished with value: 0.32851821184158325 and parameters: {'embedding_dim': 7, 'step_size': 0.051868823187409284, 'batch_size': 17, 'num_bins': 80, 'bin_strategy': 'uniform', 'num_epochs': 13}. Best is trial 15 with value: 0.3047816753387451.
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 0 are removed. Consider decreasing the number of bins.
warnings.warn(
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 2 are removed. Consider decreasing the number of bins.
warnings.warn(
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 3 are removed. Consider decreasing the number of bins.
warnings.warn(
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 4 are removed. Consider decreasing the number of bins.
warnings.warn(
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 5 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 03:43:04,642] Trial 18 pruned.
[I 2023-05-17 03:43:24,763] Trial 19 pruned.
[I 2023-05-17 03:48:35,377] Trial 20 finished with value: 0.3056541383266449 and parameters: {'embedding_dim': 10, 'step_size': 0.020693482079285105, 'batch_size': 16, 'num_bins': 38, 'bin_strategy': 'uniform', 'num_epochs': 12}. Best is trial 15 with value: 0.3047816753387451.
[I 2023-05-17 03:53:51,363] Trial 21 finished with value: 0.3041217029094696 and parameters: {'embedding_dim': 10, 'step_size': 0.017182589531927382, 'batch_size': 16, 'num_bins': 40, 'bin_strategy': 'uniform', 'num_epochs': 12}. Best is trial 21 with value: 0.3041217029094696.
[I 2023-05-17 03:59:26,777] Trial 22 finished with value: 0.30423784255981445 and parameters: {'embedding_dim': 10, 'step_size': 0.015889555648010128, 'batch_size': 15, 'num_bins': 44, 'bin_strategy': 'uniform', 'num_epochs': 12}. Best is trial 21 with value: 0.3041217029094696.
[I 2023-05-17 03:59:58,972] Trial 23 pruned.
[I 2023-05-17 04:00:28,524] Trial 24 pruned.
[I 2023-05-17 04:01:15,985] Trial 25 pruned.
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 0 are removed. Consider decreasing the number of bins.
warnings.warn(
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 2 are removed. Consider decreasing the number of bins.
warnings.warn(
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 3 are removed. Consider decreasing the number of bins.
warnings.warn(
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 4 are removed. Consider decreasing the number of bins.
warnings.warn(
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 5 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 04:01:46,624] Trial 26 pruned.
[I 2023-05-17 04:08:06,495] Trial 27 finished with value: 0.30776745080947876 and parameters: {'embedding_dim': 10, 'step_size': 0.02266745511267857, 'batch_size': 15, 'num_bins': 74, 'bin_strategy': 'uniform', 'num_epochs': 14}. Best is trial 21 with value: 0.3041217029094696.
[I 2023-05-17 04:11:50,365] Trial 28 finished with value: 0.30118101835250854 and parameters: {'embedding_dim': 8, 'step_size': 0.013689434707013629, 'batch_size': 23, 'num_bins': 56, 'bin_strategy': 'uniform', 'num_epochs': 12}. Best is trial 28 with value: 0.30118101835250854.
[I 2023-05-17 04:14:59,191] Trial 29 finished with value: 0.29582858085632324 and parameters: {'embedding_dim': 8, 'step_size': 0.013772781946733741, 'batch_size': 25, 'num_bins': 58, 'bin_strategy': 'uniform', 'num_epochs': 11}. Best is trial 29 with value: 0.29582858085632324.
[I 2023-05-17 04:15:16,142] Trial 30 pruned.
[I 2023-05-17 04:18:41,663] Trial 31 finished with value: 0.3001174330711365 and parameters: {'embedding_dim': 9, 'step_size': 0.01600497838064572, 'batch_size': 23, 'num_bins': 58, 'bin_strategy': 'uniform', 'num_epochs': 11}. Best is trial 29 with value: 0.29582858085632324.
[I 2023-05-17 04:18:59,106] Trial 32 pruned.
[I 2023-05-17 04:19:10,543] Trial 33 pruned.
[I 2023-05-17 04:19:27,642] Trial 34 pruned.
[I 2023-05-17 04:22:01,930] Trial 35 finished with value: 0.30076929926872253 and parameters: {'embedding_dim': 9, 'step_size': 0.017679085410782114, 'batch_size': 28, 'num_bins': 50, 'bin_strategy': 'uniform', 'num_epochs': 10}. Best is trial 29 with value: 0.29582858085632324.
[I 2023-05-17 04:24:15,945] Trial 36 finished with value: 0.3045254051685333 and parameters: {'embedding_dim': 9, 'step_size': 0.024278676446518384, 'batch_size': 29, 'num_bins': 52, 'bin_strategy': 'uniform', 'num_epochs': 10}. Best is trial 29 with value: 0.29582858085632324.
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 0 are removed. Consider decreasing the number of bins.
warnings.warn(
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 2 are removed. Consider decreasing the number of bins.
warnings.warn(
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 3 are removed. Consider decreasing the number of bins.
warnings.warn(
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 4 are removed. Consider decreasing the number of bins.
warnings.warn(
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 5 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 04:24:30,824] Trial 37 pruned.
[I 2023-05-17 04:27:24,617] Trial 38 finished with value: 0.3024236261844635 and parameters: {'embedding_dim': 8, 'step_size': 0.018602665611405316, 'batch_size': 25, 'num_bins': 71, 'bin_strategy': 'uniform', 'num_epochs': 10}. Best is trial 29 with value: 0.29582858085632324.
[I 2023-05-17 04:27:48,650] Trial 39 pruned.
[I 2023-05-17 04:28:26,064] Trial 40 pruned.
[I 2023-05-17 04:31:18,026] Trial 41 finished with value: 0.2989811897277832 and parameters: {'embedding_dim': 8, 'step_size': 0.016781120570308682, 'batch_size': 25, 'num_bins': 72, 'bin_strategy': 'uniform', 'num_epochs': 10}. Best is trial 29 with value: 0.29582858085632324.
[I 2023-05-17 04:31:32,313] Trial 42 pruned.
[I 2023-05-17 04:34:19,356] Trial 43 finished with value: 0.3026280105113983 and parameters: {'embedding_dim': 9, 'step_size': 0.025610956679079467, 'batch_size': 26, 'num_bins': 81, 'bin_strategy': 'uniform', 'num_epochs': 10}. Best is trial 29 with value: 0.29582858085632324.
[I 2023-05-17 04:34:52,190] Trial 44 pruned.
[I 2023-05-17 04:37:51,600] Trial 45 finished with value: 0.30039864778518677 and parameters: {'embedding_dim': 9, 'step_size': 0.013926851210708779, 'batch_size': 24, 'num_bins': 69, 'bin_strategy': 'uniform', 'num_epochs': 10}. Best is trial 29 with value: 0.29582858085632324.
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 0 are removed. Consider decreasing the number of bins.
warnings.warn(
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 2 are removed. Consider decreasing the number of bins.
warnings.warn(
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 3 are removed. Consider decreasing the number of bins.
warnings.warn(
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 4 are removed. Consider decreasing the number of bins.
warnings.warn(
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 5 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 04:38:09,223] Trial 46 pruned.
[I 2023-05-17 04:38:25,507] Trial 47 pruned.
[I 2023-05-17 04:38:39,778] Trial 48 pruned.
[I 2023-05-17 04:38:56,972] Trial 49 pruned.
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 0 are removed. Consider decreasing the number of bins.
warnings.warn(
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 2 are removed. Consider decreasing the number of bins.
warnings.warn(
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 3 are removed. Consider decreasing the number of bins.
warnings.warn(
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 4 are removed. Consider decreasing the number of bins.
warnings.warn(
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 5 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 04:39:17,432] Trial 50 pruned.
[I 2023-05-17 04:39:55,277] Trial 51 pruned.
[I 2023-05-17 04:40:41,806] Trial 52 pruned.
[I 2023-05-17 04:41:04,478] Trial 53 pruned.
[I 2023-05-17 04:41:24,107] Trial 54 pruned.
[I 2023-05-17 04:41:41,254] Trial 55 pruned.
[I 2023-05-17 04:41:58,017] Trial 56 pruned.
[I 2023-05-17 04:42:10,630] Trial 57 pruned.
[I 2023-05-17 04:42:26,297] Trial 58 pruned.
[I 2023-05-17 04:42:46,767] Trial 59 pruned.
[I 2023-05-17 04:46:59,616] Trial 60 finished with value: 0.30149054527282715 and parameters: {'embedding_dim': 9, 'step_size': 0.016542823348484607, 'batch_size': 18, 'num_bins': 100, 'bin_strategy': 'uniform', 'num_epochs': 11}. Best is trial 29 with value: 0.29582858085632324.
[I 2023-05-17 04:51:16,197] Trial 61 finished with value: 0.298368364572525 and parameters: {'embedding_dim': 9, 'step_size': 0.016604846417793938, 'batch_size': 18, 'num_bins': 92, 'bin_strategy': 'uniform', 'num_epochs': 11}. Best is trial 29 with value: 0.29582858085632324.
[I 2023-05-17 04:51:34,113] Trial 62 pruned.
[I 2023-05-17 04:51:53,620] Trial 63 pruned.
[I 2023-05-17 05:37:06,903] Trial 64 finished with value: 0.30193400382995605 and parameters: {'embedding_dim': 9, 'step_size': 0.016685807356309056, 'batch_size': 2, 'num_bins': 65, 'bin_strategy': 'uniform', 'num_epochs': 13}. Best is trial 29 with value: 0.29582858085632324.
[I 2023-05-17 05:37:25,002] Trial 65 pruned.
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 0 are removed. Consider decreasing the number of bins.
warnings.warn(
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 2 are removed. Consider decreasing the number of bins.
warnings.warn(
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 3 are removed. Consider decreasing the number of bins.
warnings.warn(
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 4 are removed. Consider decreasing the number of bins.
warnings.warn(
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 5 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 05:37:53,258] Trial 66 pruned.
[I 2023-05-17 05:38:13,413] Trial 67 pruned.
[I 2023-05-17 05:38:35,738] Trial 68 pruned.
[I 2023-05-17 05:39:00,269] Trial 69 pruned.
[I 2023-05-17 05:42:54,379] Trial 70 finished with value: 0.29890763759613037 and parameters: {'embedding_dim': 10, 'step_size': 0.016526218941787352, 'batch_size': 23, 'num_bins': 72, 'bin_strategy': 'uniform', 'num_epochs': 10}. Best is trial 29 with value: 0.29582858085632324.
[I 2023-05-17 05:43:17,916] Trial 71 pruned.
[I 2023-05-17 05:43:42,518] Trial 72 pruned.
[I 2023-05-17 05:44:05,204] Trial 73 pruned.
[I 2023-05-17 05:48:21,735] Trial 74 finished with value: 0.3004951477050781 and parameters: {'embedding_dim': 9, 'step_size': 0.014788329393552348, 'batch_size': 21, 'num_bins': 59, 'bin_strategy': 'uniform', 'num_epochs': 10}. Best is trial 29 with value: 0.29582858085632324.
[I 2023-05-17 05:49:22,809] Trial 75 pruned.
[I 2023-05-17 05:53:11,710] Trial 76 finished with value: 0.30084165930747986 and parameters: {'embedding_dim': 9, 'step_size': 0.015510325380640089, 'batch_size': 21, 'num_bins': 71, 'bin_strategy': 'uniform', 'num_epochs': 9}. Best is trial 29 with value: 0.29582858085632324.
[I 2023-05-17 05:55:50,704] Trial 77 finished with value: 0.3046785593032837 and parameters: {'embedding_dim': 10, 'step_size': 0.024487933212022406, 'batch_size': 26, 'num_bins': 67, 'bin_strategy': 'uniform', 'num_epochs': 10}. Best is trial 29 with value: 0.29582858085632324.
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 0 are removed. Consider decreasing the number of bins.
warnings.warn(
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 2 are removed. Consider decreasing the number of bins.
warnings.warn(
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 3 are removed. Consider decreasing the number of bins.
warnings.warn(
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 4 are removed. Consider decreasing the number of bins.
warnings.warn(
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 5 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 05:56:15,031] Trial 78 pruned.
[I 2023-05-17 05:56:32,604] Trial 79 pruned.
[I 2023-05-17 05:56:52,941] Trial 80 pruned.
[I 2023-05-17 05:59:25,960] Trial 81 finished with value: 0.29877328872680664 and parameters: {'embedding_dim': 9, 'step_size': 0.015665965782853387, 'batch_size': 21, 'num_bins': 70, 'bin_strategy': 'uniform', 'num_epochs': 8}. Best is trial 29 with value: 0.29582858085632324.
[I 2023-05-17 05:59:59,871] Trial 82 pruned.
[I 2023-05-17 06:00:19,755] Trial 83 pruned.
[I 2023-05-17 06:00:42,196] Trial 84 pruned.
[I 2023-05-17 06:01:01,542] Trial 85 pruned.
[I 2023-05-17 06:03:51,558] Trial 86 finished with value: 0.30616626143455505 and parameters: {'embedding_dim': 10, 'step_size': 0.02268770472091906, 'batch_size': 27, 'num_bins': 67, 'bin_strategy': 'uniform', 'num_epochs': 10}. Best is trial 29 with value: 0.29582858085632324.
[I 2023-05-17 06:04:15,445] Trial 87 pruned.
[I 2023-05-17 06:04:34,359] Trial 88 pruned.
[I 2023-05-17 06:08:41,776] Trial 89 finished with value: 0.30008405447006226 and parameters: {'embedding_dim': 9, 'step_size': 0.017192731186566303, 'batch_size': 20, 'num_bins': 83, 'bin_strategy': 'uniform', 'num_epochs': 9}. Best is trial 29 with value: 0.29582858085632324.
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 0 are removed. Consider decreasing the number of bins.
warnings.warn(
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 2 are removed. Consider decreasing the number of bins.
warnings.warn(
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 3 are removed. Consider decreasing the number of bins.
warnings.warn(
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 4 are removed. Consider decreasing the number of bins.
warnings.warn(
/usr/local/lib64/python3.9/site-packages/sklearn/preprocessing/_discretization.py:291: UserWarning: Bins whose width are too small (i.e., <= 1e-8) in feature 5 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 06:09:13,735] Trial 90 pruned.
[I 2023-05-17 06:09:44,235] Trial 91 pruned.
[I 2023-05-17 06:10:05,698] Trial 92 pruned.
[I 2023-05-17 06:11:53,132] Trial 93 pruned.
[I 2023-05-17 06:12:18,070] Trial 94 pruned.
[I 2023-05-17 06:16:39,839] Trial 95 finished with value: 0.2962709665298462 and parameters: {'embedding_dim': 10, 'step_size': 0.01851901416896681, 'batch_size': 21, 'num_bins': 97, 'bin_strategy': 'uniform', 'num_epochs': 10}. Best is trial 29 with value: 0.29582858085632324.
[I 2023-05-17 06:19:44,587] Trial 96 finished with value: 0.29874420166015625 and parameters: {'embedding_dim': 10, 'step_size': 0.016062342363613872, 'batch_size': 21, 'num_bins': 100, 'bin_strategy': 'uniform', 'num_epochs': 7}. Best is trial 29 with value: 0.29582858085632324.
[I 2023-05-17 06:22:57,478] Trial 97 finished with value: 0.303432822227478 and parameters: {'embedding_dim': 10, 'step_size': 0.02685173836114753, 'batch_size': 20, 'num_bins': 100, 'bin_strategy': 'uniform', 'num_epochs': 7}. Best is trial 29 with value: 0.29582858085632324.
[I 2023-05-17 06:25:31,353] Trial 98 finished with value: 0.29946252703666687 and parameters: {'embedding_dim': 10, 'step_size': 0.018564930846237025, 'batch_size': 24, 'num_bins': 93, 'bin_strategy': 'uniform', 'num_epochs': 7}. Best is trial 29 with value: 0.29582858085632324.
[I 2023-05-17 06:28:52,888] Trial 99 finished with value: 0.29889658093452454 and parameters: {'embedding_dim': 10, 'step_size': 0.019834766929900396, 'batch_size': 19, 'num_bins': 97, 'bin_strategy': 'uniform', 'num_epochs': 7}. Best is trial 29 with value: 0.29582858085632324.