[I 2023-05-16 23:36:36,044] A new study created in memory with name: bins
[I 2023-05-16 23:37:23,402] Trial 0 finished with value: 0.5280771877157359 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: 0.5280771877157359.
[I 2023-05-16 23:38:21,498] Trial 1 finished with value: 0.7002097411644254 and parameters: {'embedding_dim': 9, 'step_size': 0.10502105436744279, 'batch_size': 23, 'num_bins': 4, 'bin_strategy': 'uniform', 'num_epochs': 7}. Best is trial 0 with value: 0.5280771877157359.
[I 2023-05-16 23:42:02,363] Trial 2 finished with value: 0.5551966895575728 and parameters: {'embedding_dim': 2, 'step_size': 0.020492680115417352, 'batch_size': 11, 'num_bins': 53, 'bin_strategy': 'uniform', 'num_epochs': 11}. Best is trial 0 with value: 0.5280771877157359.
[I 2023-05-16 23:44:53,104] Trial 3 finished with value: 0.541053027020405 and parameters: {'embedding_dim': 2, 'step_size': 0.03135775732257745, 'batch_size': 13, 'num_bins': 47, 'bin_strategy': 'uniform', 'num_epochs': 10}. Best is trial 0 with value: 0.5280771877157359.
/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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-16 23:47:41,642] Trial 4 finished with value: 0.5161959059594673 and parameters: {'embedding_dim': 6, 'step_size': 0.011992724522955167, 'batch_size': 20, 'num_bins': 18, 'bin_strategy': 'quantile', 'num_epochs': 15}. Best is trial 4 with value: 0.5161959059594673.
[I 2023-05-16 23:55:02,608] Trial 5 finished with value: 0.4970072048574563 and parameters: {'embedding_dim': 9, 'step_size': 0.032925293631105246, 'batch_size': 5, 'num_bins': 69, 'bin_strategy': 'uniform', 'num_epochs': 10}. Best is trial 5 with value: 0.4970072048574563.
/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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-16 23:59:00,824] Trial 6 finished with value: 0.4909980418745024 and parameters: {'embedding_dim': 1, 'step_size': 0.35067764992972184, 'batch_size': 10, 'num_bins': 67, 'bin_strategy': 'quantile', 'num_epochs': 11}. Best is trial 6 with value: 0.4909980418745024.
[I 2023-05-17 00:01:14,977] Trial 7 pruned.
[I 2023-05-17 00:02:29,776] Trial 8 pruned.
[I 2023-05-17 00:03:20,527] Trial 9 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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 00:03:28,015] Trial 10 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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 00:05:20,936] Trial 11 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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 00:05:44,832] Trial 12 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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 00:06:08,219] 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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 00:09:05,756] Trial 14 finished with value: 0.502395642627435 and parameters: {'embedding_dim': 4, 'step_size': 0.05011263930396099, 'batch_size': 15, 'num_bins': 43, 'bin_strategy': 'quantile', 'num_epochs': 12}. Best is trial 6 with value: 0.4909980418745024.
/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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 00:09:42,896] Trial 15 pruned.
[I 2023-05-17 00:10:19,842] Trial 16 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 1 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(
[I 2023-05-17 00:10:39,667] Trial 17 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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 00:10:55,796] Trial 18 pruned.
[I 2023-05-17 00:13:51,299] Trial 19 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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 00:14:16,169] Trial 20 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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 00:14:30,740] Trial 21 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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 00:14:43,525] Trial 22 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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 00:15:03,802] Trial 23 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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 00:15:31,644] Trial 24 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 1 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(
[I 2023-05-17 00:15:44,864] Trial 25 pruned.
[I 2023-05-17 00:18:28,847] Trial 26 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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 00:19:02,639] Trial 27 pruned.
[I 2023-05-17 00:22:31,925] Trial 28 finished with value: 0.5196768477788142 and parameters: {'embedding_dim': 7, 'step_size': 0.14061965231931225, 'batch_size': 11, 'num_bins': 85, 'bin_strategy': 'uniform', 'num_epochs': 11}. Best is trial 6 with value: 0.4909980418745024.
[I 2023-05-17 00:23:55,180] Trial 29 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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 00:24:09,656] Trial 30 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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 00:24:20,135] Trial 31 pruned.
[I 2023-05-17 00:25:03,259] Trial 32 pruned.
[I 2023-05-17 00:26:44,073] Trial 33 finished with value: 0.4875798948549539 and parameters: {'embedding_dim': 6, 'step_size': 0.020684208264680124, 'batch_size': 24, 'num_bins': 11, 'bin_strategy': 'quantile', 'num_epochs': 11}. Best is trial 33 with value: 0.4875798948549539.
[I 2023-05-17 00:26:50,369] Trial 34 pruned.
[I 2023-05-17 00:27:11,599] Trial 35 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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 00:27:19,713] Trial 36 pruned.
[I 2023-05-17 00:27:38,434] Trial 37 pruned.
[I 2023-05-17 00:28:03,184] Trial 38 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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 00:28:10,949] Trial 39 pruned.
[I 2023-05-17 00:28:34,929] Trial 40 pruned.
[I 2023-05-17 00:28:43,881] Trial 41 pruned.
[I 2023-05-17 00:30:51,364] Trial 42 finished with value: 0.4912414844638768 and parameters: {'embedding_dim': 6, 'step_size': 0.02366328080027664, 'batch_size': 25, 'num_bins': 12, 'bin_strategy': 'quantile', 'num_epochs': 14}. Best is trial 33 with value: 0.4875798948549539.
[I 2023-05-17 00:32:38,553] Trial 43 finished with value: 0.4814953574890661 and parameters: {'embedding_dim': 6, 'step_size': 0.02353530079691863, 'batch_size': 30, 'num_bins': 11, 'bin_strategy': 'quantile', 'num_epochs': 14}. Best is trial 43 with value: 0.4814953574890661.
[I 2023-05-17 00:34:18,009] Trial 44 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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 00:34:24,647] Trial 45 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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 00:36:18,448] Trial 46 pruned.
[I 2023-05-17 00:36:56,906] Trial 47 finished with value: 0.49383070805204027 and parameters: {'embedding_dim': 6, 'step_size': 0.025434555654167735, 'batch_size': 30, 'num_bins': 15, 'bin_strategy': 'quantile', 'num_epochs': 5}. Best is trial 43 with value: 0.4814953574890661.
[I 2023-05-17 00:37:04,635] Trial 48 pruned.
[I 2023-05-17 00:37:53,269] Trial 49 finished with value: 0.48899480942348683 and parameters: {'embedding_dim': 6, 'step_size': 0.028209809445833324, 'batch_size': 28, 'num_bins': 15, 'bin_strategy': 'quantile', 'num_epochs': 6}. Best is trial 43 with value: 0.4814953574890661.
[I 2023-05-17 00:38:01,503] Trial 50 pruned.
[I 2023-05-17 00:38:48,458] Trial 51 finished with value: 0.48648655467159996 and parameters: {'embedding_dim': 6, 'step_size': 0.027729848277686826, 'batch_size': 29, 'num_bins': 15, 'bin_strategy': 'quantile', 'num_epochs': 6}. Best is trial 43 with value: 0.4814953574890661.
/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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 00:39:43,237] Trial 52 finished with value: 0.48784862426097797 and parameters: {'embedding_dim': 6, 'step_size': 0.028651818424917735, 'batch_size': 25, 'num_bins': 17, 'bin_strategy': 'quantile', 'num_epochs': 6}. Best is trial 43 with value: 0.4814953574890661.
/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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 00:40:31,815] Trial 53 finished with value: 0.4868366998634225 and parameters: {'embedding_dim': 7, 'step_size': 0.030842284746007004, 'batch_size': 28, 'num_bins': 18, 'bin_strategy': 'quantile', 'num_epochs': 6}. Best is trial 43 with value: 0.4814953574890661.
/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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 00:40:48,258] Trial 54 pruned.
[I 2023-05-17 00:41:08,129] Trial 55 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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 00:41:16,092] Trial 56 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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 00:41:51,479] Trial 57 finished with value: 0.47951060024732495 and parameters: {'embedding_dim': 8, 'step_size': 0.03929383281600887, 'batch_size': 32, 'num_bins': 17, 'bin_strategy': 'quantile', 'num_epochs': 6}. Best is trial 57 with value: 0.47951060024732495.
/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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 00:42:43,233] Trial 58 finished with value: 0.4845081577007928 and parameters: {'embedding_dim': 8, 'step_size': 0.04246678658964534, 'batch_size': 32, 'num_bins': 25, 'bin_strategy': 'quantile', 'num_epochs': 7}. Best is trial 57 with value: 0.47951060024732495.
/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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 00:43:34,879] Trial 59 finished with value: 0.49187994233475485 and parameters: {'embedding_dim': 8, 'step_size': 0.04312872060983268, 'batch_size': 32, 'num_bins': 25, 'bin_strategy': 'quantile', 'num_epochs': 7}. Best is trial 57 with value: 0.47951060024732495.
[I 2023-05-17 00:44:35,589] Trial 60 finished with value: 0.4815114345371291 and parameters: {'embedding_dim': 8, 'step_size': 0.04837698369243848, 'batch_size': 31, 'num_bins': 11, 'bin_strategy': 'quantile', 'num_epochs': 8}. Best is trial 57 with value: 0.47951060024732495.
[I 2023-05-17 00:45:34,500] Trial 61 finished with value: 0.49070868780647986 and parameters: {'embedding_dim': 8, 'step_size': 0.049335977465450875, 'batch_size': 32, 'num_bins': 12, 'bin_strategy': 'quantile', 'num_epochs': 8}. Best is trial 57 with value: 0.47951060024732495.
[I 2023-05-17 00:45:42,276] Trial 62 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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 00:46:20,071] Trial 63 finished with value: 0.491216049016063 and parameters: {'embedding_dim': 7, 'step_size': 0.03515178497648949, 'batch_size': 31, 'num_bins': 19, 'bin_strategy': 'quantile', 'num_epochs': 5}. Best is trial 57 with value: 0.47951060024732495.
[I 2023-05-17 00:47:08,678] Trial 64 finished with value: 0.4849947072261395 and parameters: {'embedding_dim': 8, 'step_size': 0.04805048391692695, 'batch_size': 29, 'num_bins': 11, 'bin_strategy': 'quantile', 'num_epochs': 6}. Best is trial 57 with value: 0.47951060024732495.
/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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 00:47:57,305] 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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 00:48:50,313] Trial 66 finished with value: 0.476914166633194 and parameters: {'embedding_dim': 8, 'step_size': 0.03971654057761182, 'batch_size': 31, 'num_bins': 23, 'bin_strategy': 'quantile', 'num_epochs': 7}. Best is trial 66 with value: 0.476914166633194.
/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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 00:49:13,452] Trial 67 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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 00:50:01,305] Trial 68 finished with value: 0.482084411088513 and parameters: {'embedding_dim': 9, 'step_size': 0.06121422232448351, 'batch_size': 29, 'num_bins': 23, 'bin_strategy': 'quantile', 'num_epochs': 7}. Best is trial 66 with value: 0.476914166633194.
/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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 00:50:54,972] Trial 69 finished with value: 0.4851239628268377 and parameters: {'embedding_dim': 10, 'step_size': 0.06349724505888375, 'batch_size': 31, 'num_bins': 22, 'bin_strategy': 'quantile', 'num_epochs': 7}. Best is trial 66 with value: 0.476914166633194.
/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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 00:51:46,909] Trial 70 finished with value: 0.48660264444334267 and parameters: {'embedding_dim': 9, 'step_size': 0.056829217265857324, 'batch_size': 32, 'num_bins': 26, 'bin_strategy': 'quantile', 'num_epochs': 7}. Best is trial 66 with value: 0.476914166633194.
/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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 00:52:40,173] Trial 71 finished with value: 0.48210371390904005 and parameters: {'embedding_dim': 10, 'step_size': 0.06862730361201547, 'batch_size': 31, 'num_bins': 23, 'bin_strategy': 'quantile', 'num_epochs': 7}. Best is trial 66 with value: 0.476914166633194.
/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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 00:53:13,224] Trial 72 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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 00:54:06,179] Trial 73 finished with value: 0.47648125878431646 and parameters: {'embedding_dim': 8, 'step_size': 0.0527994326893901, 'batch_size': 31, 'num_bins': 23, 'bin_strategy': 'quantile', 'num_epochs': 7}. Best is trial 73 with value: 0.47648125878431646.
/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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 00:54:13,921] Trial 74 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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 00:55:14,666] Trial 75 finished with value: 0.4832143413749891 and parameters: {'embedding_dim': 8, 'step_size': 0.05312163758261429, 'batch_size': 27, 'num_bins': 24, 'bin_strategy': 'quantile', 'num_epochs': 7}. Best is trial 73 with value: 0.47648125878431646.
/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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 00:55:40,298] Trial 76 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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 00:56:43,399] Trial 77 finished with value: 0.48646381124588367 and parameters: {'embedding_dim': 10, 'step_size': 0.06784387379069022, 'batch_size': 30, 'num_bins': 23, 'bin_strategy': 'quantile', 'num_epochs': 8}. Best is trial 73 with value: 0.47648125878431646.
/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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 00:56:52,544] Trial 78 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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 00:58:01,068] Trial 79 finished with value: 0.49141271856808333 and parameters: {'embedding_dim': 9, 'step_size': 0.0831574285124721, 'batch_size': 31, 'num_bins': 19, 'bin_strategy': 'quantile', 'num_epochs': 9}. Best is trial 73 with value: 0.47648125878431646.
/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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 00:58:35,449] Trial 80 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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 00:59:18,893] Trial 81 finished with value: 0.48632571974316574 and parameters: {'embedding_dim': 8, 'step_size': 0.043784056828969076, 'batch_size': 32, 'num_bins': 26, 'bin_strategy': 'quantile', 'num_epochs': 7}. Best is trial 73 with value: 0.47648125878431646.
/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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 01:00:13,887] Trial 82 finished with value: 0.4808140576078414 and parameters: {'embedding_dim': 9, 'step_size': 0.0396166901001848, 'batch_size': 30, 'num_bins': 17, 'bin_strategy': 'quantile', 'num_epochs': 7}. Best is trial 73 with value: 0.47648125878431646.
/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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 01:01:16,749] Trial 83 finished with value: 0.484505758786694 and parameters: {'embedding_dim': 10, 'step_size': 0.035889673059122974, 'batch_size': 30, 'num_bins': 17, 'bin_strategy': 'quantile', 'num_epochs': 8}. Best is trial 73 with value: 0.47648125878431646.
[I 2023-05-17 01:01:24,973] Trial 84 pruned.
[I 2023-05-17 01:02:03,746] Trial 85 pruned.
[I 2023-05-17 01:02:26,934] Trial 86 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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 01:03:17,388] Trial 87 finished with value: 0.4778754175051123 and parameters: {'embedding_dim': 8, 'step_size': 0.05100157729747126, 'batch_size': 28, 'num_bins': 22, 'bin_strategy': 'quantile', 'num_epochs': 6}. Best is trial 73 with value: 0.47648125878431646.
/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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 01:03:59,348] Trial 88 finished with value: 0.47865184479910533 and parameters: {'embedding_dim': 10, 'step_size': 0.046509370024280926, 'batch_size': 28, 'num_bins': 21, 'bin_strategy': 'quantile', 'num_epochs': 5}. Best is trial 73 with value: 0.47648125878431646.
/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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 01:04:42,129] Trial 89 finished with value: 0.48706426403950454 and parameters: {'embedding_dim': 8, 'step_size': 0.044832751812685284, 'batch_size': 28, 'num_bins': 18, 'bin_strategy': 'quantile', 'num_epochs': 5}. Best is trial 73 with value: 0.47648125878431646.
[I 2023-05-17 01:04:50,840] Trial 90 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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 01:05:38,872] Trial 91 finished with value: 0.4764637610283817 and parameters: {'embedding_dim': 10, 'step_size': 0.04717310364019017, 'batch_size': 30, 'num_bins': 22, 'bin_strategy': 'quantile', 'num_epochs': 6}. Best is trial 91 with value: 0.4764637610283817.
[I 2023-05-17 01:06:26,018] Trial 92 finished with value: 0.4725330759763331 and parameters: {'embedding_dim': 10, 'step_size': 0.04746441356701626, 'batch_size': 30, 'num_bins': 13, 'bin_strategy': 'quantile', 'num_epochs': 6}. Best is trial 92 with value: 0.4725330759763331.
[I 2023-05-17 01:06:41,549] Trial 93 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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 01:07:12,239] Trial 94 finished with value: 0.4796635929325749 and parameters: {'embedding_dim': 10, 'step_size': 0.0477274890995249, 'batch_size': 30, 'num_bins': 17, 'bin_strategy': 'quantile', 'num_epochs': 5}. Best is trial 92 with value: 0.4725330759763331.
[I 2023-05-17 01:07:53,602] Trial 95 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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 01:08:37,636] Trial 96 finished with value: 0.4850260604414627 and parameters: {'embedding_dim': 10, 'step_size': 0.046947828609809845, 'batch_size': 26, 'num_bins': 19, 'bin_strategy': 'quantile', 'num_epochs': 5}. Best is trial 92 with value: 0.4725330759763331.
/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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 01:08:51,371] Trial 97 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 1 are removed. Consider decreasing the number of bins.
warnings.warn(
[I 2023-05-17 01:09:30,112] Trial 98 finished with value: 0.4824779956622831 and parameters: {'embedding_dim': 10, 'step_size': 0.04156484777805755, 'batch_size': 30, 'num_bins': 17, 'bin_strategy': 'quantile', 'num_epochs': 5}. Best is trial 92 with value: 0.4725330759763331.
[I 2023-05-17 01:09:54,902] Trial 99 pruned.