| 2023-10-17 20:22:26,600 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:22:26,601 Model: "SequenceTagger( | |
| (embeddings): TransformerWordEmbeddings( | |
| (model): ElectraModel( | |
| (embeddings): ElectraEmbeddings( | |
| (word_embeddings): Embedding(32001, 768) | |
| (position_embeddings): Embedding(512, 768) | |
| (token_type_embeddings): Embedding(2, 768) | |
| (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (encoder): ElectraEncoder( | |
| (layer): ModuleList( | |
| (0-11): 12 x ElectraLayer( | |
| (attention): ElectraAttention( | |
| (self): ElectraSelfAttention( | |
| (query): Linear(in_features=768, out_features=768, bias=True) | |
| (key): Linear(in_features=768, out_features=768, bias=True) | |
| (value): Linear(in_features=768, out_features=768, bias=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (output): ElectraSelfOutput( | |
| (dense): Linear(in_features=768, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (intermediate): ElectraIntermediate( | |
| (dense): Linear(in_features=768, out_features=3072, bias=True) | |
| (intermediate_act_fn): GELUActivation() | |
| ) | |
| (output): ElectraOutput( | |
| (dense): Linear(in_features=3072, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| ) | |
| ) | |
| ) | |
| ) | |
| (locked_dropout): LockedDropout(p=0.5) | |
| (linear): Linear(in_features=768, out_features=17, bias=True) | |
| (loss_function): CrossEntropyLoss() | |
| )" | |
| 2023-10-17 20:22:26,601 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:22:26,601 MultiCorpus: 1085 train + 148 dev + 364 test sentences | |
| - NER_HIPE_2022 Corpus: 1085 train + 148 dev + 364 test sentences - /root/.flair/datasets/ner_hipe_2022/v2.1/newseye/sv/with_doc_seperator | |
| 2023-10-17 20:22:26,601 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:22:26,601 Train: 1085 sentences | |
| 2023-10-17 20:22:26,601 (train_with_dev=False, train_with_test=False) | |
| 2023-10-17 20:22:26,601 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:22:26,601 Training Params: | |
| 2023-10-17 20:22:26,601 - learning_rate: "5e-05" | |
| 2023-10-17 20:22:26,601 - mini_batch_size: "4" | |
| 2023-10-17 20:22:26,601 - max_epochs: "10" | |
| 2023-10-17 20:22:26,601 - shuffle: "True" | |
| 2023-10-17 20:22:26,601 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:22:26,601 Plugins: | |
| 2023-10-17 20:22:26,602 - TensorboardLogger | |
| 2023-10-17 20:22:26,602 - LinearScheduler | warmup_fraction: '0.1' | |
| 2023-10-17 20:22:26,602 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:22:26,602 Final evaluation on model from best epoch (best-model.pt) | |
| 2023-10-17 20:22:26,602 - metric: "('micro avg', 'f1-score')" | |
| 2023-10-17 20:22:26,602 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:22:26,602 Computation: | |
| 2023-10-17 20:22:26,602 - compute on device: cuda:0 | |
| 2023-10-17 20:22:26,602 - embedding storage: none | |
| 2023-10-17 20:22:26,602 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:22:26,602 Model training base path: "hmbench-newseye/sv-hmteams/teams-base-historic-multilingual-discriminator-bs4-wsFalse-e10-lr5e-05-poolingfirst-layers-1-crfFalse-4" | |
| 2023-10-17 20:22:26,602 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:22:26,602 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:22:26,602 Logging anything other than scalars to TensorBoard is currently not supported. | |
| 2023-10-17 20:22:28,205 epoch 1 - iter 27/272 - loss 3.40623895 - time (sec): 1.60 - samples/sec: 3386.92 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-17 20:22:29,850 epoch 1 - iter 54/272 - loss 2.64778140 - time (sec): 3.25 - samples/sec: 3205.45 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-17 20:22:31,678 epoch 1 - iter 81/272 - loss 1.89470970 - time (sec): 5.07 - samples/sec: 3228.54 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-17 20:22:33,184 epoch 1 - iter 108/272 - loss 1.55945154 - time (sec): 6.58 - samples/sec: 3243.02 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-17 20:22:34,720 epoch 1 - iter 135/272 - loss 1.32041644 - time (sec): 8.12 - samples/sec: 3280.25 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-17 20:22:36,310 epoch 1 - iter 162/272 - loss 1.17756978 - time (sec): 9.71 - samples/sec: 3206.49 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-17 20:22:37,849 epoch 1 - iter 189/272 - loss 1.04336124 - time (sec): 11.25 - samples/sec: 3227.97 - lr: 0.000035 - momentum: 0.000000 | |
| 2023-10-17 20:22:39,527 epoch 1 - iter 216/272 - loss 0.92669269 - time (sec): 12.92 - samples/sec: 3249.42 - lr: 0.000040 - momentum: 0.000000 | |
| 2023-10-17 20:22:41,040 epoch 1 - iter 243/272 - loss 0.86162728 - time (sec): 14.44 - samples/sec: 3223.74 - lr: 0.000044 - momentum: 0.000000 | |
| 2023-10-17 20:22:42,626 epoch 1 - iter 270/272 - loss 0.79081358 - time (sec): 16.02 - samples/sec: 3238.48 - lr: 0.000049 - momentum: 0.000000 | |
| 2023-10-17 20:22:42,723 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:22:42,723 EPOCH 1 done: loss 0.7899 - lr: 0.000049 | |
| 2023-10-17 20:22:43,970 DEV : loss 0.16378863155841827 - f1-score (micro avg) 0.6164 | |
| 2023-10-17 20:22:43,974 saving best model | |
| 2023-10-17 20:22:44,399 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:22:45,968 epoch 2 - iter 27/272 - loss 0.25767374 - time (sec): 1.57 - samples/sec: 3194.61 - lr: 0.000049 - momentum: 0.000000 | |
| 2023-10-17 20:22:47,585 epoch 2 - iter 54/272 - loss 0.18763097 - time (sec): 3.18 - samples/sec: 3270.50 - lr: 0.000049 - momentum: 0.000000 | |
| 2023-10-17 20:22:49,123 epoch 2 - iter 81/272 - loss 0.17973790 - time (sec): 4.72 - samples/sec: 3435.04 - lr: 0.000048 - momentum: 0.000000 | |
| 2023-10-17 20:22:50,626 epoch 2 - iter 108/272 - loss 0.16187387 - time (sec): 6.22 - samples/sec: 3516.89 - lr: 0.000048 - momentum: 0.000000 | |
| 2023-10-17 20:22:52,065 epoch 2 - iter 135/272 - loss 0.16105113 - time (sec): 7.66 - samples/sec: 3368.57 - lr: 0.000047 - momentum: 0.000000 | |
| 2023-10-17 20:22:53,717 epoch 2 - iter 162/272 - loss 0.15784438 - time (sec): 9.32 - samples/sec: 3373.16 - lr: 0.000047 - momentum: 0.000000 | |
| 2023-10-17 20:22:55,227 epoch 2 - iter 189/272 - loss 0.15170985 - time (sec): 10.83 - samples/sec: 3379.62 - lr: 0.000046 - momentum: 0.000000 | |
| 2023-10-17 20:22:56,786 epoch 2 - iter 216/272 - loss 0.14931401 - time (sec): 12.39 - samples/sec: 3346.42 - lr: 0.000046 - momentum: 0.000000 | |
| 2023-10-17 20:22:58,384 epoch 2 - iter 243/272 - loss 0.14546742 - time (sec): 13.98 - samples/sec: 3377.89 - lr: 0.000045 - momentum: 0.000000 | |
| 2023-10-17 20:22:59,861 epoch 2 - iter 270/272 - loss 0.14667348 - time (sec): 15.46 - samples/sec: 3338.96 - lr: 0.000045 - momentum: 0.000000 | |
| 2023-10-17 20:23:00,006 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:23:00,006 EPOCH 2 done: loss 0.1460 - lr: 0.000045 | |
| 2023-10-17 20:23:01,511 DEV : loss 0.13631020486354828 - f1-score (micro avg) 0.7405 | |
| 2023-10-17 20:23:01,515 saving best model | |
| 2023-10-17 20:23:02,008 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:23:03,542 epoch 3 - iter 27/272 - loss 0.12873334 - time (sec): 1.53 - samples/sec: 3222.01 - lr: 0.000044 - momentum: 0.000000 | |
| 2023-10-17 20:23:05,152 epoch 3 - iter 54/272 - loss 0.09958223 - time (sec): 3.14 - samples/sec: 3055.89 - lr: 0.000043 - momentum: 0.000000 | |
| 2023-10-17 20:23:06,773 epoch 3 - iter 81/272 - loss 0.08615905 - time (sec): 4.76 - samples/sec: 3113.14 - lr: 0.000043 - momentum: 0.000000 | |
| 2023-10-17 20:23:08,467 epoch 3 - iter 108/272 - loss 0.09050520 - time (sec): 6.46 - samples/sec: 3123.51 - lr: 0.000042 - momentum: 0.000000 | |
| 2023-10-17 20:23:10,010 epoch 3 - iter 135/272 - loss 0.10892810 - time (sec): 8.00 - samples/sec: 3119.86 - lr: 0.000042 - momentum: 0.000000 | |
| 2023-10-17 20:23:11,605 epoch 3 - iter 162/272 - loss 0.10570646 - time (sec): 9.59 - samples/sec: 3156.75 - lr: 0.000041 - momentum: 0.000000 | |
| 2023-10-17 20:23:13,179 epoch 3 - iter 189/272 - loss 0.09847848 - time (sec): 11.17 - samples/sec: 3149.61 - lr: 0.000041 - momentum: 0.000000 | |
| 2023-10-17 20:23:14,859 epoch 3 - iter 216/272 - loss 0.09658563 - time (sec): 12.85 - samples/sec: 3226.18 - lr: 0.000040 - momentum: 0.000000 | |
| 2023-10-17 20:23:16,369 epoch 3 - iter 243/272 - loss 0.09713728 - time (sec): 14.36 - samples/sec: 3209.44 - lr: 0.000040 - momentum: 0.000000 | |
| 2023-10-17 20:23:18,084 epoch 3 - iter 270/272 - loss 0.09473854 - time (sec): 16.07 - samples/sec: 3218.02 - lr: 0.000039 - momentum: 0.000000 | |
| 2023-10-17 20:23:18,185 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:23:18,185 EPOCH 3 done: loss 0.0946 - lr: 0.000039 | |
| 2023-10-17 20:23:19,896 DEV : loss 0.12857291102409363 - f1-score (micro avg) 0.7695 | |
| 2023-10-17 20:23:19,901 saving best model | |
| 2023-10-17 20:23:20,369 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:23:22,050 epoch 4 - iter 27/272 - loss 0.04863011 - time (sec): 1.68 - samples/sec: 3532.90 - lr: 0.000038 - momentum: 0.000000 | |
| 2023-10-17 20:23:23,565 epoch 4 - iter 54/272 - loss 0.04952118 - time (sec): 3.19 - samples/sec: 3365.08 - lr: 0.000038 - momentum: 0.000000 | |
| 2023-10-17 20:23:25,299 epoch 4 - iter 81/272 - loss 0.04821615 - time (sec): 4.93 - samples/sec: 3464.45 - lr: 0.000037 - momentum: 0.000000 | |
| 2023-10-17 20:23:26,994 epoch 4 - iter 108/272 - loss 0.04656621 - time (sec): 6.62 - samples/sec: 3432.94 - lr: 0.000037 - momentum: 0.000000 | |
| 2023-10-17 20:23:28,582 epoch 4 - iter 135/272 - loss 0.04950359 - time (sec): 8.21 - samples/sec: 3362.25 - lr: 0.000036 - momentum: 0.000000 | |
| 2023-10-17 20:23:30,082 epoch 4 - iter 162/272 - loss 0.05105052 - time (sec): 9.71 - samples/sec: 3296.71 - lr: 0.000036 - momentum: 0.000000 | |
| 2023-10-17 20:23:31,689 epoch 4 - iter 189/272 - loss 0.05366686 - time (sec): 11.32 - samples/sec: 3237.27 - lr: 0.000035 - momentum: 0.000000 | |
| 2023-10-17 20:23:33,411 epoch 4 - iter 216/272 - loss 0.05164999 - time (sec): 13.04 - samples/sec: 3240.84 - lr: 0.000034 - momentum: 0.000000 | |
| 2023-10-17 20:23:34,963 epoch 4 - iter 243/272 - loss 0.05133109 - time (sec): 14.59 - samples/sec: 3225.19 - lr: 0.000034 - momentum: 0.000000 | |
| 2023-10-17 20:23:36,481 epoch 4 - iter 270/272 - loss 0.05924423 - time (sec): 16.11 - samples/sec: 3216.17 - lr: 0.000033 - momentum: 0.000000 | |
| 2023-10-17 20:23:36,568 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:23:36,568 EPOCH 4 done: loss 0.0591 - lr: 0.000033 | |
| 2023-10-17 20:23:38,107 DEV : loss 0.14095589518547058 - f1-score (micro avg) 0.8248 | |
| 2023-10-17 20:23:38,115 saving best model | |
| 2023-10-17 20:23:38,647 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:23:40,181 epoch 5 - iter 27/272 - loss 0.04161918 - time (sec): 1.53 - samples/sec: 3371.72 - lr: 0.000033 - momentum: 0.000000 | |
| 2023-10-17 20:23:41,797 epoch 5 - iter 54/272 - loss 0.03906740 - time (sec): 3.15 - samples/sec: 3286.92 - lr: 0.000032 - momentum: 0.000000 | |
| 2023-10-17 20:23:43,295 epoch 5 - iter 81/272 - loss 0.03980555 - time (sec): 4.65 - samples/sec: 3305.42 - lr: 0.000032 - momentum: 0.000000 | |
| 2023-10-17 20:23:44,934 epoch 5 - iter 108/272 - loss 0.04222380 - time (sec): 6.29 - samples/sec: 3294.55 - lr: 0.000031 - momentum: 0.000000 | |
| 2023-10-17 20:23:46,547 epoch 5 - iter 135/272 - loss 0.04134787 - time (sec): 7.90 - samples/sec: 3329.13 - lr: 0.000031 - momentum: 0.000000 | |
| 2023-10-17 20:23:48,180 epoch 5 - iter 162/272 - loss 0.03847928 - time (sec): 9.53 - samples/sec: 3319.66 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-17 20:23:49,690 epoch 5 - iter 189/272 - loss 0.04003670 - time (sec): 11.04 - samples/sec: 3326.51 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-17 20:23:51,339 epoch 5 - iter 216/272 - loss 0.03896642 - time (sec): 12.69 - samples/sec: 3324.71 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-17 20:23:52,752 epoch 5 - iter 243/272 - loss 0.03875774 - time (sec): 14.10 - samples/sec: 3286.69 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-17 20:23:54,441 epoch 5 - iter 270/272 - loss 0.03752829 - time (sec): 15.79 - samples/sec: 3275.49 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-17 20:23:54,552 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:23:54,552 EPOCH 5 done: loss 0.0375 - lr: 0.000028 | |
| 2023-10-17 20:23:56,053 DEV : loss 0.14450490474700928 - f1-score (micro avg) 0.8303 | |
| 2023-10-17 20:23:56,057 saving best model | |
| 2023-10-17 20:23:56,529 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:23:58,265 epoch 6 - iter 27/272 - loss 0.02331958 - time (sec): 1.73 - samples/sec: 3400.01 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-17 20:23:59,798 epoch 6 - iter 54/272 - loss 0.02778531 - time (sec): 3.27 - samples/sec: 3378.82 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-17 20:24:01,382 epoch 6 - iter 81/272 - loss 0.02856352 - time (sec): 4.85 - samples/sec: 3399.05 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-17 20:24:02,988 epoch 6 - iter 108/272 - loss 0.02887330 - time (sec): 6.46 - samples/sec: 3419.07 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-17 20:24:04,498 epoch 6 - iter 135/272 - loss 0.02445293 - time (sec): 7.97 - samples/sec: 3406.75 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-17 20:24:06,001 epoch 6 - iter 162/272 - loss 0.02445139 - time (sec): 9.47 - samples/sec: 3355.78 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-17 20:24:07,542 epoch 6 - iter 189/272 - loss 0.02422895 - time (sec): 11.01 - samples/sec: 3360.71 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-17 20:24:09,131 epoch 6 - iter 216/272 - loss 0.02456752 - time (sec): 12.60 - samples/sec: 3357.57 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-17 20:24:10,700 epoch 6 - iter 243/272 - loss 0.02951527 - time (sec): 14.17 - samples/sec: 3303.46 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-17 20:24:12,292 epoch 6 - iter 270/272 - loss 0.02803499 - time (sec): 15.76 - samples/sec: 3294.17 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-17 20:24:12,377 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:24:12,378 EPOCH 6 done: loss 0.0280 - lr: 0.000022 | |
| 2023-10-17 20:24:13,893 DEV : loss 0.164916530251503 - f1-score (micro avg) 0.8349 | |
| 2023-10-17 20:24:13,898 saving best model | |
| 2023-10-17 20:24:14,377 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:24:16,001 epoch 7 - iter 27/272 - loss 0.02600591 - time (sec): 1.62 - samples/sec: 3156.24 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-17 20:24:17,553 epoch 7 - iter 54/272 - loss 0.02176704 - time (sec): 3.17 - samples/sec: 3042.50 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-17 20:24:19,116 epoch 7 - iter 81/272 - loss 0.02312263 - time (sec): 4.74 - samples/sec: 3180.06 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-17 20:24:20,639 epoch 7 - iter 108/272 - loss 0.02098405 - time (sec): 6.26 - samples/sec: 3186.77 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-17 20:24:22,295 epoch 7 - iter 135/272 - loss 0.02136903 - time (sec): 7.92 - samples/sec: 3168.51 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-17 20:24:23,839 epoch 7 - iter 162/272 - loss 0.01922451 - time (sec): 9.46 - samples/sec: 3247.84 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-17 20:24:25,360 epoch 7 - iter 189/272 - loss 0.01820994 - time (sec): 10.98 - samples/sec: 3232.36 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-17 20:24:27,097 epoch 7 - iter 216/272 - loss 0.01760377 - time (sec): 12.72 - samples/sec: 3252.49 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-17 20:24:28,705 epoch 7 - iter 243/272 - loss 0.01983655 - time (sec): 14.32 - samples/sec: 3285.53 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-17 20:24:30,192 epoch 7 - iter 270/272 - loss 0.02082722 - time (sec): 15.81 - samples/sec: 3267.16 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-17 20:24:30,289 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:24:30,289 EPOCH 7 done: loss 0.0214 - lr: 0.000017 | |
| 2023-10-17 20:24:31,970 DEV : loss 0.1378893107175827 - f1-score (micro avg) 0.8466 | |
| 2023-10-17 20:24:31,974 saving best model | |
| 2023-10-17 20:24:32,437 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:24:34,194 epoch 8 - iter 27/272 - loss 0.02138210 - time (sec): 1.76 - samples/sec: 3402.72 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-17 20:24:35,940 epoch 8 - iter 54/272 - loss 0.01603143 - time (sec): 3.50 - samples/sec: 3511.78 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-17 20:24:37,649 epoch 8 - iter 81/272 - loss 0.01321229 - time (sec): 5.21 - samples/sec: 3438.41 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-17 20:24:39,220 epoch 8 - iter 108/272 - loss 0.01354273 - time (sec): 6.78 - samples/sec: 3379.13 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-17 20:24:40,760 epoch 8 - iter 135/272 - loss 0.01494549 - time (sec): 8.32 - samples/sec: 3317.33 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-17 20:24:42,340 epoch 8 - iter 162/272 - loss 0.01356546 - time (sec): 9.90 - samples/sec: 3302.23 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-17 20:24:44,005 epoch 8 - iter 189/272 - loss 0.01223719 - time (sec): 11.57 - samples/sec: 3292.22 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-17 20:24:45,450 epoch 8 - iter 216/272 - loss 0.01234719 - time (sec): 13.01 - samples/sec: 3226.97 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-17 20:24:47,009 epoch 8 - iter 243/272 - loss 0.01158905 - time (sec): 14.57 - samples/sec: 3223.70 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-17 20:24:48,502 epoch 8 - iter 270/272 - loss 0.01164301 - time (sec): 16.06 - samples/sec: 3227.93 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-17 20:24:48,584 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:24:48,584 EPOCH 8 done: loss 0.0116 - lr: 0.000011 | |
| 2023-10-17 20:24:50,133 DEV : loss 0.17313425242900848 - f1-score (micro avg) 0.8411 | |
| 2023-10-17 20:24:50,139 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:24:51,767 epoch 9 - iter 27/272 - loss 0.01050858 - time (sec): 1.63 - samples/sec: 3239.68 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-17 20:24:53,284 epoch 9 - iter 54/272 - loss 0.00816307 - time (sec): 3.14 - samples/sec: 3430.50 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-17 20:24:55,016 epoch 9 - iter 81/272 - loss 0.00563877 - time (sec): 4.88 - samples/sec: 3331.55 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-17 20:24:56,573 epoch 9 - iter 108/272 - loss 0.00751326 - time (sec): 6.43 - samples/sec: 3319.73 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-17 20:24:58,184 epoch 9 - iter 135/272 - loss 0.00746821 - time (sec): 8.04 - samples/sec: 3333.63 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-17 20:24:59,745 epoch 9 - iter 162/272 - loss 0.00835793 - time (sec): 9.60 - samples/sec: 3302.04 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-17 20:25:01,328 epoch 9 - iter 189/272 - loss 0.00843661 - time (sec): 11.19 - samples/sec: 3278.39 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-17 20:25:03,008 epoch 9 - iter 216/272 - loss 0.00844583 - time (sec): 12.87 - samples/sec: 3268.37 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-17 20:25:04,632 epoch 9 - iter 243/272 - loss 0.00798675 - time (sec): 14.49 - samples/sec: 3245.09 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-17 20:25:06,262 epoch 9 - iter 270/272 - loss 0.00914489 - time (sec): 16.12 - samples/sec: 3208.36 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-17 20:25:06,364 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:25:06,364 EPOCH 9 done: loss 0.0091 - lr: 0.000006 | |
| 2023-10-17 20:25:07,842 DEV : loss 0.16325917840003967 - f1-score (micro avg) 0.8454 | |
| 2023-10-17 20:25:07,848 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:25:09,333 epoch 10 - iter 27/272 - loss 0.01177117 - time (sec): 1.48 - samples/sec: 3150.74 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-17 20:25:10,839 epoch 10 - iter 54/272 - loss 0.00588272 - time (sec): 2.99 - samples/sec: 3203.39 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-17 20:25:12,334 epoch 10 - iter 81/272 - loss 0.00422933 - time (sec): 4.49 - samples/sec: 3248.98 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-17 20:25:13,912 epoch 10 - iter 108/272 - loss 0.00469858 - time (sec): 6.06 - samples/sec: 3231.54 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-17 20:25:15,425 epoch 10 - iter 135/272 - loss 0.00590915 - time (sec): 7.58 - samples/sec: 3187.05 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-17 20:25:16,981 epoch 10 - iter 162/272 - loss 0.00571912 - time (sec): 9.13 - samples/sec: 3238.99 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-17 20:25:18,598 epoch 10 - iter 189/272 - loss 0.00575909 - time (sec): 10.75 - samples/sec: 3253.20 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-17 20:25:20,320 epoch 10 - iter 216/272 - loss 0.00592286 - time (sec): 12.47 - samples/sec: 3244.35 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-17 20:25:22,153 epoch 10 - iter 243/272 - loss 0.00637850 - time (sec): 14.30 - samples/sec: 3226.88 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-17 20:25:23,793 epoch 10 - iter 270/272 - loss 0.00590127 - time (sec): 15.94 - samples/sec: 3246.86 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-10-17 20:25:23,884 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:25:23,885 EPOCH 10 done: loss 0.0059 - lr: 0.000000 | |
| 2023-10-17 20:25:25,440 DEV : loss 0.16820533573627472 - f1-score (micro avg) 0.8296 | |
| 2023-10-17 20:25:25,843 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 20:25:25,844 Loading model from best epoch ... | |
| 2023-10-17 20:25:27,361 SequenceTagger predicts: Dictionary with 17 tags: O, S-LOC, B-LOC, E-LOC, I-LOC, S-PER, B-PER, E-PER, I-PER, S-HumanProd, B-HumanProd, E-HumanProd, I-HumanProd, S-ORG, B-ORG, E-ORG, I-ORG | |
| 2023-10-17 20:25:29,711 | |
| Results: | |
| - F-score (micro) 0.7984 | |
| - F-score (macro) 0.7542 | |
| - Accuracy 0.6809 | |
| By class: | |
| precision recall f1-score support | |
| LOC 0.8439 0.8141 0.8287 312 | |
| PER 0.7541 0.8846 0.8142 208 | |
| ORG 0.5500 0.6000 0.5739 55 | |
| HumanProd 0.6667 1.0000 0.8000 22 | |
| micro avg 0.7727 0.8258 0.7984 597 | |
| macro avg 0.7037 0.8247 0.7542 597 | |
| weighted avg 0.7790 0.8258 0.7991 597 | |
| 2023-10-17 20:25:29,711 ---------------------------------------------------------------------------------------------------- | |