2021-09-16:17:25:43,112 INFO [iwn.py:43] Loading bengali language synsets... 2021-09-16:17:25:56,34 WARNING [utils.py:429] using automatically assigned random_state=1570809799 2021-09-16:17:25:56,66 INFO [splitting.py:60] done splitting triples to groups of sizes [267045, 38830, 38831] /srv/home/bhattacharyya/anaconda3/lib/python3.7/site-packages/sklearn/ensemble/weight_boosting.py:29: DeprecationWarning: numpy.core.umath_tests is an internal NumPy module and should not be imported. It will be removed in a future NumPy release. from numpy.core.umath_tests import inner1d /srv/home/bhattacharyya/anaconda3/lib/python3.7/site-packages/sklearn/ensemble/gradient_boosting.py:34: DeprecationWarning: `np.bool` is a deprecated alias for the builtin `bool`. To silence this warning, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations from ._gradient_boosting import predict_stages /srv/home/bhattacharyya/anaconda3/lib/python3.7/site-packages/sklearn/ensemble/gradient_boosting.py:34: DeprecationWarning: `np.bool` is a deprecated alias for the builtin `bool`. To silence this warning, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations from ._gradient_boosting import predict_stages [I 2021-09-16 17:25:56,801] A new study created in memory with name: no-name-a93622a0-e597-4afe-b4b1-373c77259791 2021-09-16:17:25:56,846 INFO [hpo.py:622] Using model: 2021-09-16:17:25:56,847 INFO [hpo.py:626] Using loss: 2021-09-16:17:25:56,847 INFO [hpo.py:637] Using regularizer: 2021-09-16:17:25:56,847 INFO [hpo.py:641] Using optimizer: 2021-09-16:17:25:56,847 INFO [hpo.py:645] Using training loop: 2021-09-16:17:25:56,847 INFO [hpo.py:651] Using negative sampler: 2021-09-16:17:25:56,847 INFO [hpo.py:662] Using evaluator: 2021-09-16:17:25:56,847 INFO [hpo.py:666] Attempting to maximize adjusted_arithmetic_mean_rank_index 2021-09-16:17:25:56,847 INFO [hpo.py:668] Filter validation triples when testing: True /srv/home/bhattacharyya/anaconda3/lib/python3.7/site-packages/optuna/distributions.py:563: UserWarning: The distribution is specified by [32, 4000] and step=100, but the range is not divisible by `step`. It will be replaced by [32, 3932]. low=low, old_high=old_high, high=high, step=step 2021-09-16:17:25:56,851 WARNING [api.py:823] No random seed is specified. Setting to 325143478. Training epochs on cuda: 0%| | 0/10 [00:00 Saved checkpoint after having finished epoch 10. Training epochs on cuda: 100%|██████████| 10/10 [02:49<00:00, 44.64s/epoch, loss=0.00201, prev_loss=0.002] Training epochs on cuda: 100%|██████████| 10/10 [02:49<00:00, 16.92s/epoch, loss=0.00201, prev_loss=0.002] 2021-09-16:17:28:51,299 INFO [training_loop.py:1092] => loading checkpoint '/tmp/tmpf0ls_5rl' 2021-09-16:17:28:51,422 INFO [training_loop.py:1135] => loaded checkpoint '/tmp/tmpf0ls_5rl' stopped after having finished epoch 10 Evaluating on cuda: 0%| | 0.00/38.8k [00:00 Saved checkpoint after having finished epoch 10. Training epochs on cuda: 100%|██████████| 10/10 [02:41<00:00, 44.11s/epoch, loss=0.000495, prev_loss=0.000493] Training epochs on cuda: 100%|██████████| 10/10 [02:41<00:00, 16.14s/epoch, loss=0.000495, prev_loss=0.000493] 2021-09-16:17:33:51,958 INFO [training_loop.py:1092] => loading checkpoint '/tmp/tmp68potrz9' 2021-09-16:17:33:52,58 INFO [training_loop.py:1135] => loaded checkpoint '/tmp/tmp68potrz9' stopped after having finished epoch 10 Evaluating on cuda: 0%| | 0.00/38.8k [00:00 Saved checkpoint after having finished epoch 10. Training epochs on cuda: 100%|██████████| 10/10 [02:44<00:00, 44.66s/epoch, loss=0.000735, prev_loss=0.000732] Training epochs on cuda: 100%|██████████| 10/10 [02:44<00:00, 16.42s/epoch, loss=0.000735, prev_loss=0.000732] 2021-09-16:17:38:55,230 INFO [training_loop.py:1092] => loading checkpoint '/tmp/tmpesz20md2' 2021-09-16:17:38:55,432 INFO [training_loop.py:1135] => loaded checkpoint '/tmp/tmpesz20md2' stopped after having finished epoch 10 Evaluating on cuda: 0%| | 0.00/38.8k [00:00 Saved checkpoint after having finished epoch 10. Training epochs on cuda: 100%|██████████| 10/10 [02:51<00:00, 45.22s/epoch, loss=0.00167, prev_loss=0.00166] Training epochs on cuda: 100%|██████████| 10/10 [02:51<00:00, 17.12s/epoch, loss=0.00167, prev_loss=0.00166] 2021-09-16:17:44:05,636 INFO [training_loop.py:1092] => loading checkpoint '/tmp/tmpf8to_9dz' 2021-09-16:17:44:05,744 INFO [training_loop.py:1135] => loaded checkpoint '/tmp/tmpf8to_9dz' stopped after having finished epoch 10 Evaluating on cuda: 0%| | 0.00/38.8k [00:00 Saved checkpoint after having finished epoch 10. Training epochs on cuda: 100%|██████████| 10/10 [03:48<00:00, 50.66s/epoch, loss=0.000821, prev_loss=0.000817] Training epochs on cuda: 100%|██████████| 10/10 [03:48<00:00, 22.82s/epoch, loss=0.000821, prev_loss=0.000817] 2021-09-16:17:50:13,222 INFO [training_loop.py:1092] => loading checkpoint '/tmp/tmp0fbxej8h' 2021-09-16:17:50:13,319 INFO [training_loop.py:1135] => loaded checkpoint '/tmp/tmp0fbxej8h' stopped after having finished epoch 10 Evaluating on cuda: 0%| | 0.00/38.8k [00:00 Saved checkpoint after having finished epoch 10. Training epochs on cuda: 100%|██████████| 10/10 [06:10<00:00, 64.74s/epoch, loss=0.0356, prev_loss=0.0356] Training epochs on cuda: 100%|██████████| 10/10 [06:10<00:00, 37.03s/epoch, loss=0.0356, prev_loss=0.0356] 2021-09-16:17:58:42,493 INFO [training_loop.py:1092] => loading checkpoint '/tmp/tmpamendkre' 2021-09-16:17:58:42,603 INFO [training_loop.py:1135] => loaded checkpoint '/tmp/tmpamendkre' stopped after having finished epoch 10 Evaluating on cuda: 0%| | 0.00/38.8k [00:00 Saved checkpoint after having finished epoch 10. Training epochs on cuda: 100%|██████████| 10/10 [02:43<00:00, 44.39s/epoch, loss=0.000259, prev_loss=0.000258] Training epochs on cuda: 100%|██████████| 10/10 [02:43<00:00, 16.39s/epoch, loss=0.000259, prev_loss=0.000258] 2021-09-16:18:03:45,136 INFO [training_loop.py:1092] => loading checkpoint '/tmp/tmpbgxmblje' 2021-09-16:18:03:45,259 INFO [training_loop.py:1135] => loaded checkpoint '/tmp/tmpbgxmblje' stopped after having finished epoch 10 Evaluating on cuda: 0%| | 0.00/38.8k [00:00 Saved checkpoint after having finished epoch 10. Training epochs on cuda: 100%|██████████| 10/10 [02:47<00:00, 44.78s/epoch, loss=0.000479, prev_loss=0.000774] Training epochs on cuda: 100%|██████████| 10/10 [02:47<00:00, 16.76s/epoch, loss=0.000479, prev_loss=0.000774] 2021-09-16:18:08:52,10 INFO [training_loop.py:1092] => loading checkpoint '/tmp/tmpocu8dob_' 2021-09-16:18:08:52,232 INFO [training_loop.py:1135] => loaded checkpoint '/tmp/tmpocu8dob_' stopped after having finished epoch 10 Evaluating on cuda: 0%| | 0.00/38.8k [00:00 Saved checkpoint after having finished epoch 10. Training epochs on cuda: 100%|██████████| 10/10 [02:52<00:00, 45.11s/epoch, loss=0.00367, prev_loss=0.0039] Training epochs on cuda: 100%|██████████| 10/10 [02:52<00:00, 17.28s/epoch, loss=0.00367, prev_loss=0.0039] 2021-09-16:18:14:05,641 INFO [training_loop.py:1092] => loading checkpoint '/tmp/tmpnjejlehs' 2021-09-16:18:14:05,761 INFO [training_loop.py:1135] => loaded checkpoint '/tmp/tmpnjejlehs' stopped after having finished epoch 10 Evaluating on cuda: 0%| | 0.00/38.8k [00:00 Saved checkpoint after having finished epoch 10. Training epochs on cuda: 100%|██████████| 10/10 [03:08<00:00, 46.75s/epoch, loss=0.00209, prev_loss=0.00209] Training epochs on cuda: 100%|██████████| 10/10 [03:08<00:00, 18.87s/epoch, loss=0.00209, prev_loss=0.00209] 2021-09-16:18:19:33,501 INFO [training_loop.py:1092] => loading checkpoint '/tmp/tmpg1ld490j' 2021-09-16:18:19:33,599 INFO [training_loop.py:1135] => loaded checkpoint '/tmp/tmpg1ld490j' stopped after having finished epoch 10 Evaluating on cuda: 0%| | 0.00/38.8k [00:00 Saved checkpoint after having finished epoch 10. Training epochs on cuda: 100%|██████████| 10/10 [17:50<00:00, 135.04s/epoch, loss=1.85, prev_loss=1.85] Training epochs on cuda: 100%|██████████| 10/10 [17:50<00:00, 107.05s/epoch, loss=1.85, prev_loss=1.85] 2021-09-16:18:39:43,4 INFO [training_loop.py:1092] => loading checkpoint '/tmp/tmpck5b6t1d' 2021-09-16:18:39:43,116 INFO [training_loop.py:1135] => loaded checkpoint '/tmp/tmpck5b6t1d' stopped after having finished epoch 10 Evaluating on cuda: 0%| | 0.00/38.8k [00:00 Saved checkpoint after having finished epoch 10. Training epochs on cuda: 100%|██████████| 10/10 [17:57<00:00, 135.53s/epoch, loss=4.58, prev_loss=4.53] Training epochs on cuda: 100%|██████████| 10/10 [17:57<00:00, 107.77s/epoch, loss=4.58, prev_loss=4.53] 2021-09-16:19:00:00,10 INFO [training_loop.py:1092] => loading checkpoint '/tmp/tmpe0icfzj_' 2021-09-16:19:00:00,135 INFO [training_loop.py:1135] => loaded checkpoint '/tmp/tmpe0icfzj_' stopped after having finished epoch 10 Evaluating on cuda: 0%| | 0.00/38.8k [00:00 Saved checkpoint after having finished epoch 10. Training epochs on cuda: 100%|██████████| 10/10 [18:11<00:00, 137.46s/epoch, loss=4.05, prev_loss=4.03] Training epochs on cuda: 100%|██████████| 10/10 [18:11<00:00, 109.14s/epoch, loss=4.05, prev_loss=4.03] 2021-09-16:19:20:30,566 INFO [training_loop.py:1092] => loading checkpoint '/tmp/tmpt3izt5hb' 2021-09-16:19:20:30,685 INFO [training_loop.py:1135] => loaded checkpoint '/tmp/tmpt3izt5hb' stopped after having finished epoch 10 Evaluating on cuda: 0%| | 0.00/38.8k [00:00 Saved checkpoint after having finished epoch 10. Training epochs on cuda: 100%|██████████| 10/10 [03:34<00:00, 49.28s/epoch, loss=0.00335, prev_loss=0.00393] Training epochs on cuda: 100%|██████████| 10/10 [03:34<00:00, 21.44s/epoch, loss=0.00335, prev_loss=0.00393] 2021-09-16:19:26:24,378 INFO [training_loop.py:1092] => loading checkpoint '/tmp/tmp4r7az2tq' 2021-09-16:19:26:24,499 INFO [training_loop.py:1135] => loaded checkpoint '/tmp/tmp4r7az2tq' stopped after having finished epoch 10 Evaluating on cuda: 0%| | 0.00/38.8k [00:00 Saved checkpoint after having finished epoch 10. Training epochs on cuda: 100%|██████████| 10/10 [03:47<00:00, 50.74s/epoch, loss=0.00174, prev_loss=0.00172] Training epochs on cuda: 100%|██████████| 10/10 [03:47<00:00, 22.73s/epoch, loss=0.00174, prev_loss=0.00172] 2021-09-16:19:32:30,905 INFO [training_loop.py:1092] => loading checkpoint '/tmp/tmpu8lbxp1e' 2021-09-16:19:32:31,26 INFO [training_loop.py:1135] => loaded checkpoint '/tmp/tmpu8lbxp1e' stopped after having finished epoch 10 Evaluating on cuda: 0%| | 0.00/38.8k [00:00 Saved checkpoint after having finished epoch 10. Training epochs on cuda: 100%|██████████| 10/10 [03:26<00:00, 48.48s/epoch, loss=0.00112, prev_loss=0.00111] Training epochs on cuda: 100%|██████████| 10/10 [03:26<00:00, 20.64s/epoch, loss=0.00112, prev_loss=0.00111] 2021-09-16:19:38:16,470 INFO [training_loop.py:1092] => loading checkpoint '/tmp/tmpr90pkoup' 2021-09-16:19:38:16,577 INFO [training_loop.py:1135] => loaded checkpoint '/tmp/tmpr90pkoup' stopped after having finished epoch 10 Evaluating on cuda: 0%| | 0.00/38.8k [00:00 Saved checkpoint after having finished epoch 10. Training epochs on cuda: 100%|██████████| 10/10 [04:01<00:00, 52.06s/epoch, loss=0.000868, prev_loss=0.000865] Training epochs on cuda: 100%|██████████| 10/10 [04:01<00:00, 24.18s/epoch, loss=0.000868, prev_loss=0.000865] 2021-09-16:19:44:37,753 INFO [training_loop.py:1092] => loading checkpoint '/tmp/tmpho3avl10' 2021-09-16:19:44:37,868 INFO [training_loop.py:1135] => loaded checkpoint '/tmp/tmpho3avl10' stopped after having finished epoch 10 Evaluating on cuda: 0%| | 0.00/38.8k [00:00 Saved checkpoint after having finished epoch 10. Training epochs on cuda: 100%|██████████| 10/10 [03:28<00:00, 48.55s/epoch, loss=0.00769, prev_loss=0.00767] Training epochs on cuda: 100%|██████████| 10/10 [03:28<00:00, 20.81s/epoch, loss=0.00769, prev_loss=0.00767] 2021-09-16:19:50:24,946 INFO [training_loop.py:1092] => loading checkpoint '/tmp/tmpcfm6jh_o' 2021-09-16:19:50:25,53 INFO [training_loop.py:1135] => loaded checkpoint '/tmp/tmpcfm6jh_o' stopped after having finished epoch 10 Evaluating on cuda: 0%| | 0.00/38.8k [00:00 Saved checkpoint after having finished epoch 10. Training epochs on cuda: 100%|██████████| 10/10 [03:35<00:00, 49.71s/epoch, loss=0.00335, prev_loss=0.00334] Training epochs on cuda: 100%|██████████| 10/10 [03:35<00:00, 21.60s/epoch, loss=0.00335, prev_loss=0.00334] 2021-09-16:19:56:20,169 INFO [training_loop.py:1092] => loading checkpoint '/tmp/tmpxp3y6wci' 2021-09-16:19:56:20,287 INFO [training_loop.py:1135] => loaded checkpoint '/tmp/tmpxp3y6wci' stopped after having finished epoch 10 Evaluating on cuda: 0%| | 0.00/38.8k [00:00 Saved checkpoint after having finished epoch 10. Training epochs on cuda: 100%|██████████| 10/10 [02:49<00:00, 44.94s/epoch, loss=0.00194, prev_loss=0.00193] Training epochs on cuda: 100%|██████████| 10/10 [02:49<00:00, 17.00s/epoch, loss=0.00194, prev_loss=0.00193] 2021-09-16:20:01:29,322 INFO [training_loop.py:1092] => loading checkpoint '/tmp/tmpt6ou394i' 2021-09-16:20:01:29,444 INFO [training_loop.py:1135] => loaded checkpoint '/tmp/tmpt6ou394i' stopped after having finished epoch 10 Evaluating on cuda: 0%| | 0.00/38.8k [00:00 Saved checkpoint after having finished epoch 10. Training epochs on cuda: 100%|██████████| 10/10 [03:00<00:00, 46.07s/epoch, loss=0.00274, prev_loss=0.00273] Training epochs on cuda: 100%|██████████| 10/10 [03:00<00:00, 18.06s/epoch, loss=0.00274, prev_loss=0.00273] 2021-09-16:20:06:48,989 INFO [training_loop.py:1092] => loading checkpoint '/tmp/tmp4q1refxm' 2021-09-16:20:06:49,117 INFO [training_loop.py:1135] => loaded checkpoint '/tmp/tmp4q1refxm' stopped after having finished epoch 10 Evaluating on cuda: 0%| | 0.00/38.8k [00:00 Saved checkpoint after having finished epoch 10. Training epochs on cuda: 100%|██████████| 10/10 [06:19<00:00, 65.91s/epoch, loss=0.117, prev_loss=0.281] Training epochs on cuda: 100%|██████████| 10/10 [06:19<00:00, 37.99s/epoch, loss=0.117, prev_loss=0.281] 2021-09-16:20:15:28,101 INFO [training_loop.py:1092] => loading checkpoint '/tmp/tmpurg7alwh' 2021-09-16:20:15:28,230 INFO [training_loop.py:1135] => loaded checkpoint '/tmp/tmpurg7alwh' stopped after having finished epoch 10 Evaluating on cuda: 0%| | 0.00/38.8k [00:00 Saved checkpoint after having finished epoch 10. Training epochs on cuda: 100%|██████████| 10/10 [18:29<00:00, 139.42s/epoch, loss=8.6, prev_loss=8.26] Training epochs on cuda: 100%|██████████| 10/10 [18:29<00:00, 110.97s/epoch, loss=8.6, prev_loss=8.26] 2021-09-16:20:36:16,886 INFO [training_loop.py:1092] => loading checkpoint '/tmp/tmpp35n57_6' 2021-09-16:20:36:17,18 INFO [training_loop.py:1135] => loaded checkpoint '/tmp/tmpp35n57_6' stopped after having finished epoch 10 Evaluating on cuda: 0%| | 0.00/38.8k [00:00