| 2023-10-25 21:12:45,451 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 21:12:45,452 Model: "SequenceTagger( | |
| (embeddings): TransformerWordEmbeddings( | |
| (model): BertModel( | |
| (embeddings): BertEmbeddings( | |
| (word_embeddings): Embedding(64001, 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): BertEncoder( | |
| (layer): ModuleList( | |
| (0-11): 12 x BertLayer( | |
| (attention): BertAttention( | |
| (self): BertSelfAttention( | |
| (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): BertSelfOutput( | |
| (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): BertIntermediate( | |
| (dense): Linear(in_features=768, out_features=3072, bias=True) | |
| (intermediate_act_fn): GELUActivation() | |
| ) | |
| (output): BertOutput( | |
| (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) | |
| ) | |
| ) | |
| ) | |
| ) | |
| (pooler): BertPooler( | |
| (dense): Linear(in_features=768, out_features=768, bias=True) | |
| (activation): Tanh() | |
| ) | |
| ) | |
| ) | |
| (locked_dropout): LockedDropout(p=0.5) | |
| (linear): Linear(in_features=768, out_features=17, bias=True) | |
| (loss_function): CrossEntropyLoss() | |
| )" | |
| 2023-10-25 21:12:45,452 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 21:12:45,453 MultiCorpus: 1166 train + 165 dev + 415 test sentences | |
| - NER_HIPE_2022 Corpus: 1166 train + 165 dev + 415 test sentences - /root/.flair/datasets/ner_hipe_2022/v2.1/newseye/fi/with_doc_seperator | |
| 2023-10-25 21:12:45,453 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 21:12:45,453 Train: 1166 sentences | |
| 2023-10-25 21:12:45,453 (train_with_dev=False, train_with_test=False) | |
| 2023-10-25 21:12:45,453 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 21:12:45,453 Training Params: | |
| 2023-10-25 21:12:45,453 - learning_rate: "5e-05" | |
| 2023-10-25 21:12:45,453 - mini_batch_size: "4" | |
| 2023-10-25 21:12:45,453 - max_epochs: "10" | |
| 2023-10-25 21:12:45,453 - shuffle: "True" | |
| 2023-10-25 21:12:45,453 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 21:12:45,453 Plugins: | |
| 2023-10-25 21:12:45,453 - TensorboardLogger | |
| 2023-10-25 21:12:45,453 - LinearScheduler | warmup_fraction: '0.1' | |
| 2023-10-25 21:12:45,453 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 21:12:45,453 Final evaluation on model from best epoch (best-model.pt) | |
| 2023-10-25 21:12:45,453 - metric: "('micro avg', 'f1-score')" | |
| 2023-10-25 21:12:45,453 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 21:12:45,453 Computation: | |
| 2023-10-25 21:12:45,453 - compute on device: cuda:0 | |
| 2023-10-25 21:12:45,453 - embedding storage: none | |
| 2023-10-25 21:12:45,453 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 21:12:45,453 Model training base path: "hmbench-newseye/fi-dbmdz/bert-base-historic-multilingual-64k-td-cased-bs4-wsFalse-e10-lr5e-05-poolingfirst-layers-1-crfFalse-3" | |
| 2023-10-25 21:12:45,453 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 21:12:45,453 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 21:12:45,453 Logging anything other than scalars to TensorBoard is currently not supported. | |
| 2023-10-25 21:12:46,773 epoch 1 - iter 29/292 - loss 2.60630160 - time (sec): 1.32 - samples/sec: 2620.93 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-25 21:12:48,030 epoch 1 - iter 58/292 - loss 1.73093403 - time (sec): 2.58 - samples/sec: 2898.55 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-25 21:12:49,336 epoch 1 - iter 87/292 - loss 1.29007377 - time (sec): 3.88 - samples/sec: 3112.26 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-25 21:12:50,589 epoch 1 - iter 116/292 - loss 1.08928573 - time (sec): 5.13 - samples/sec: 3136.32 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-25 21:12:51,860 epoch 1 - iter 145/292 - loss 0.93038328 - time (sec): 6.41 - samples/sec: 3201.92 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-25 21:12:53,193 epoch 1 - iter 174/292 - loss 0.83340092 - time (sec): 7.74 - samples/sec: 3228.79 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-25 21:12:54,501 epoch 1 - iter 203/292 - loss 0.74787824 - time (sec): 9.05 - samples/sec: 3289.33 - lr: 0.000035 - momentum: 0.000000 | |
| 2023-10-25 21:12:55,918 epoch 1 - iter 232/292 - loss 0.68293476 - time (sec): 10.46 - samples/sec: 3333.71 - lr: 0.000040 - momentum: 0.000000 | |
| 2023-10-25 21:12:57,231 epoch 1 - iter 261/292 - loss 0.61828383 - time (sec): 11.78 - samples/sec: 3395.00 - lr: 0.000045 - momentum: 0.000000 | |
| 2023-10-25 21:12:58,524 epoch 1 - iter 290/292 - loss 0.57952199 - time (sec): 13.07 - samples/sec: 3387.23 - lr: 0.000049 - momentum: 0.000000 | |
| 2023-10-25 21:12:58,602 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 21:12:58,602 EPOCH 1 done: loss 0.5801 - lr: 0.000049 | |
| 2023-10-25 21:12:59,117 DEV : loss 0.1393888294696808 - f1-score (micro avg) 0.6157 | |
| 2023-10-25 21:12:59,121 saving best model | |
| 2023-10-25 21:12:59,633 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 21:13:00,938 epoch 2 - iter 29/292 - loss 0.16641729 - time (sec): 1.30 - samples/sec: 3551.69 - lr: 0.000049 - momentum: 0.000000 | |
| 2023-10-25 21:13:02,295 epoch 2 - iter 58/292 - loss 0.14870205 - time (sec): 2.66 - samples/sec: 3657.47 - lr: 0.000049 - momentum: 0.000000 | |
| 2023-10-25 21:13:03,566 epoch 2 - iter 87/292 - loss 0.15224226 - time (sec): 3.93 - samples/sec: 3558.93 - lr: 0.000048 - momentum: 0.000000 | |
| 2023-10-25 21:13:04,863 epoch 2 - iter 116/292 - loss 0.15195587 - time (sec): 5.23 - samples/sec: 3491.95 - lr: 0.000048 - momentum: 0.000000 | |
| 2023-10-25 21:13:06,114 epoch 2 - iter 145/292 - loss 0.15173369 - time (sec): 6.48 - samples/sec: 3425.51 - lr: 0.000047 - momentum: 0.000000 | |
| 2023-10-25 21:13:07,298 epoch 2 - iter 174/292 - loss 0.16302891 - time (sec): 7.66 - samples/sec: 3398.01 - lr: 0.000047 - momentum: 0.000000 | |
| 2023-10-25 21:13:08,492 epoch 2 - iter 203/292 - loss 0.16090612 - time (sec): 8.86 - samples/sec: 3414.98 - lr: 0.000046 - momentum: 0.000000 | |
| 2023-10-25 21:13:09,795 epoch 2 - iter 232/292 - loss 0.15301547 - time (sec): 10.16 - samples/sec: 3440.05 - lr: 0.000046 - momentum: 0.000000 | |
| 2023-10-25 21:13:11,060 epoch 2 - iter 261/292 - loss 0.15185628 - time (sec): 11.43 - samples/sec: 3468.19 - lr: 0.000045 - momentum: 0.000000 | |
| 2023-10-25 21:13:12,335 epoch 2 - iter 290/292 - loss 0.15180422 - time (sec): 12.70 - samples/sec: 3473.70 - lr: 0.000045 - momentum: 0.000000 | |
| 2023-10-25 21:13:12,422 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 21:13:12,423 EPOCH 2 done: loss 0.1516 - lr: 0.000045 | |
| 2023-10-25 21:13:13,340 DEV : loss 0.1067458763718605 - f1-score (micro avg) 0.7253 | |
| 2023-10-25 21:13:13,344 saving best model | |
| 2023-10-25 21:13:14,183 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 21:13:15,560 epoch 3 - iter 29/292 - loss 0.07559153 - time (sec): 1.37 - samples/sec: 3251.25 - lr: 0.000044 - momentum: 0.000000 | |
| 2023-10-25 21:13:16,805 epoch 3 - iter 58/292 - loss 0.07386580 - time (sec): 2.62 - samples/sec: 2941.45 - lr: 0.000043 - momentum: 0.000000 | |
| 2023-10-25 21:13:18,136 epoch 3 - iter 87/292 - loss 0.07463057 - time (sec): 3.95 - samples/sec: 3118.77 - lr: 0.000043 - momentum: 0.000000 | |
| 2023-10-25 21:13:19,407 epoch 3 - iter 116/292 - loss 0.07309791 - time (sec): 5.22 - samples/sec: 3058.69 - lr: 0.000042 - momentum: 0.000000 | |
| 2023-10-25 21:13:20,812 epoch 3 - iter 145/292 - loss 0.07859240 - time (sec): 6.62 - samples/sec: 3310.07 - lr: 0.000042 - momentum: 0.000000 | |
| 2023-10-25 21:13:22,125 epoch 3 - iter 174/292 - loss 0.08064284 - time (sec): 7.94 - samples/sec: 3359.83 - lr: 0.000041 - momentum: 0.000000 | |
| 2023-10-25 21:13:23,411 epoch 3 - iter 203/292 - loss 0.08000187 - time (sec): 9.22 - samples/sec: 3387.08 - lr: 0.000041 - momentum: 0.000000 | |
| 2023-10-25 21:13:24,634 epoch 3 - iter 232/292 - loss 0.07888199 - time (sec): 10.45 - samples/sec: 3370.63 - lr: 0.000040 - momentum: 0.000000 | |
| 2023-10-25 21:13:25,866 epoch 3 - iter 261/292 - loss 0.07895832 - time (sec): 11.68 - samples/sec: 3351.73 - lr: 0.000040 - momentum: 0.000000 | |
| 2023-10-25 21:13:27,159 epoch 3 - iter 290/292 - loss 0.08051650 - time (sec): 12.97 - samples/sec: 3374.19 - lr: 0.000039 - momentum: 0.000000 | |
| 2023-10-25 21:13:27,266 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 21:13:27,266 EPOCH 3 done: loss 0.0807 - lr: 0.000039 | |
| 2023-10-25 21:13:28,186 DEV : loss 0.10645782947540283 - f1-score (micro avg) 0.7273 | |
| 2023-10-25 21:13:28,190 saving best model | |
| 2023-10-25 21:13:28,853 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 21:13:30,194 epoch 4 - iter 29/292 - loss 0.05879957 - time (sec): 1.34 - samples/sec: 3783.44 - lr: 0.000038 - momentum: 0.000000 | |
| 2023-10-25 21:13:31,451 epoch 4 - iter 58/292 - loss 0.05787533 - time (sec): 2.60 - samples/sec: 3488.46 - lr: 0.000038 - momentum: 0.000000 | |
| 2023-10-25 21:13:32,757 epoch 4 - iter 87/292 - loss 0.05964165 - time (sec): 3.90 - samples/sec: 3404.79 - lr: 0.000037 - momentum: 0.000000 | |
| 2023-10-25 21:13:34,060 epoch 4 - iter 116/292 - loss 0.05624702 - time (sec): 5.21 - samples/sec: 3327.34 - lr: 0.000037 - momentum: 0.000000 | |
| 2023-10-25 21:13:35,289 epoch 4 - iter 145/292 - loss 0.05478522 - time (sec): 6.43 - samples/sec: 3263.01 - lr: 0.000036 - momentum: 0.000000 | |
| 2023-10-25 21:13:36,625 epoch 4 - iter 174/292 - loss 0.05936602 - time (sec): 7.77 - samples/sec: 3299.85 - lr: 0.000036 - momentum: 0.000000 | |
| 2023-10-25 21:13:37,824 epoch 4 - iter 203/292 - loss 0.05877258 - time (sec): 8.97 - samples/sec: 3309.89 - lr: 0.000035 - momentum: 0.000000 | |
| 2023-10-25 21:13:39,052 epoch 4 - iter 232/292 - loss 0.05534208 - time (sec): 10.20 - samples/sec: 3293.06 - lr: 0.000035 - momentum: 0.000000 | |
| 2023-10-25 21:13:40,403 epoch 4 - iter 261/292 - loss 0.05738089 - time (sec): 11.55 - samples/sec: 3384.13 - lr: 0.000034 - momentum: 0.000000 | |
| 2023-10-25 21:13:41,720 epoch 4 - iter 290/292 - loss 0.05628166 - time (sec): 12.86 - samples/sec: 3443.39 - lr: 0.000033 - momentum: 0.000000 | |
| 2023-10-25 21:13:41,808 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 21:13:41,808 EPOCH 4 done: loss 0.0561 - lr: 0.000033 | |
| 2023-10-25 21:13:42,726 DEV : loss 0.13811993598937988 - f1-score (micro avg) 0.7425 | |
| 2023-10-25 21:13:42,730 saving best model | |
| 2023-10-25 21:13:43,402 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 21:13:44,735 epoch 5 - iter 29/292 - loss 0.02917983 - time (sec): 1.33 - samples/sec: 3600.95 - lr: 0.000033 - momentum: 0.000000 | |
| 2023-10-25 21:13:45,986 epoch 5 - iter 58/292 - loss 0.03003225 - time (sec): 2.58 - samples/sec: 3317.20 - lr: 0.000032 - momentum: 0.000000 | |
| 2023-10-25 21:13:47,328 epoch 5 - iter 87/292 - loss 0.03965107 - time (sec): 3.92 - samples/sec: 3485.40 - lr: 0.000032 - momentum: 0.000000 | |
| 2023-10-25 21:13:48,619 epoch 5 - iter 116/292 - loss 0.04015937 - time (sec): 5.21 - samples/sec: 3403.14 - lr: 0.000031 - momentum: 0.000000 | |
| 2023-10-25 21:13:49,919 epoch 5 - iter 145/292 - loss 0.03738301 - time (sec): 6.51 - samples/sec: 3370.76 - lr: 0.000031 - momentum: 0.000000 | |
| 2023-10-25 21:13:51,199 epoch 5 - iter 174/292 - loss 0.03512502 - time (sec): 7.79 - samples/sec: 3305.98 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-25 21:13:52,517 epoch 5 - iter 203/292 - loss 0.03795555 - time (sec): 9.11 - samples/sec: 3285.02 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-25 21:13:53,848 epoch 5 - iter 232/292 - loss 0.04076074 - time (sec): 10.44 - samples/sec: 3339.81 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-25 21:13:55,256 epoch 5 - iter 261/292 - loss 0.03934850 - time (sec): 11.85 - samples/sec: 3380.71 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-25 21:13:56,543 epoch 5 - iter 290/292 - loss 0.04048060 - time (sec): 13.14 - samples/sec: 3374.10 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-25 21:13:56,617 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 21:13:56,617 EPOCH 5 done: loss 0.0404 - lr: 0.000028 | |
| 2023-10-25 21:13:57,540 DEV : loss 0.12971803545951843 - f1-score (micro avg) 0.7451 | |
| 2023-10-25 21:13:57,544 saving best model | |
| 2023-10-25 21:13:58,224 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 21:13:59,472 epoch 6 - iter 29/292 - loss 0.02180752 - time (sec): 1.24 - samples/sec: 3433.49 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-25 21:14:00,795 epoch 6 - iter 58/292 - loss 0.02936813 - time (sec): 2.57 - samples/sec: 3411.13 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-25 21:14:02,143 epoch 6 - iter 87/292 - loss 0.02555129 - time (sec): 3.91 - samples/sec: 3498.75 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-25 21:14:03,427 epoch 6 - iter 116/292 - loss 0.02657167 - time (sec): 5.20 - samples/sec: 3501.91 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-25 21:14:04,721 epoch 6 - iter 145/292 - loss 0.02565577 - time (sec): 6.49 - samples/sec: 3419.27 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-25 21:14:06,062 epoch 6 - iter 174/292 - loss 0.02343463 - time (sec): 7.83 - samples/sec: 3344.78 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-25 21:14:07,348 epoch 6 - iter 203/292 - loss 0.02416227 - time (sec): 9.12 - samples/sec: 3368.83 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-25 21:14:08,679 epoch 6 - iter 232/292 - loss 0.02927410 - time (sec): 10.45 - samples/sec: 3384.05 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-25 21:14:09,995 epoch 6 - iter 261/292 - loss 0.03021667 - time (sec): 11.77 - samples/sec: 3401.67 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-25 21:14:11,280 epoch 6 - iter 290/292 - loss 0.03036653 - time (sec): 13.05 - samples/sec: 3389.93 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-25 21:14:11,367 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 21:14:11,367 EPOCH 6 done: loss 0.0307 - lr: 0.000022 | |
| 2023-10-25 21:14:12,290 DEV : loss 0.15307584404945374 - f1-score (micro avg) 0.7665 | |
| 2023-10-25 21:14:12,294 saving best model | |
| 2023-10-25 21:14:12,958 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 21:14:14,228 epoch 7 - iter 29/292 - loss 0.02367547 - time (sec): 1.27 - samples/sec: 3400.04 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-25 21:14:15,919 epoch 7 - iter 58/292 - loss 0.02823955 - time (sec): 2.96 - samples/sec: 3480.61 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-25 21:14:17,150 epoch 7 - iter 87/292 - loss 0.02673198 - time (sec): 4.19 - samples/sec: 3329.46 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-25 21:14:18,398 epoch 7 - iter 116/292 - loss 0.02646895 - time (sec): 5.44 - samples/sec: 3258.84 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-25 21:14:19,722 epoch 7 - iter 145/292 - loss 0.02552160 - time (sec): 6.76 - samples/sec: 3321.63 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-25 21:14:21,003 epoch 7 - iter 174/292 - loss 0.02323132 - time (sec): 8.04 - samples/sec: 3367.73 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-25 21:14:22,256 epoch 7 - iter 203/292 - loss 0.02225006 - time (sec): 9.29 - samples/sec: 3393.37 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-25 21:14:23,470 epoch 7 - iter 232/292 - loss 0.02294774 - time (sec): 10.51 - samples/sec: 3343.71 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-25 21:14:24,767 epoch 7 - iter 261/292 - loss 0.02407455 - time (sec): 11.80 - samples/sec: 3361.55 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-25 21:14:26,083 epoch 7 - iter 290/292 - loss 0.02328112 - time (sec): 13.12 - samples/sec: 3374.12 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-25 21:14:26,163 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 21:14:26,163 EPOCH 7 done: loss 0.0232 - lr: 0.000017 | |
| 2023-10-25 21:14:27,082 DEV : loss 0.1477293223142624 - f1-score (micro avg) 0.787 | |
| 2023-10-25 21:14:27,087 saving best model | |
| 2023-10-25 21:14:27,754 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 21:14:29,068 epoch 8 - iter 29/292 - loss 0.04019118 - time (sec): 1.31 - samples/sec: 3033.76 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-25 21:14:30,486 epoch 8 - iter 58/292 - loss 0.02562495 - time (sec): 2.73 - samples/sec: 3338.48 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-25 21:14:31,835 epoch 8 - iter 87/292 - loss 0.02135462 - time (sec): 4.08 - samples/sec: 3416.50 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-25 21:14:33,120 epoch 8 - iter 116/292 - loss 0.02053731 - time (sec): 5.36 - samples/sec: 3408.96 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-25 21:14:34,425 epoch 8 - iter 145/292 - loss 0.02012399 - time (sec): 6.67 - samples/sec: 3372.65 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-25 21:14:35,694 epoch 8 - iter 174/292 - loss 0.01842217 - time (sec): 7.94 - samples/sec: 3388.27 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-25 21:14:36,985 epoch 8 - iter 203/292 - loss 0.01663993 - time (sec): 9.23 - samples/sec: 3331.69 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-25 21:14:38,289 epoch 8 - iter 232/292 - loss 0.01669885 - time (sec): 10.53 - samples/sec: 3367.99 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-25 21:14:39,605 epoch 8 - iter 261/292 - loss 0.01668062 - time (sec): 11.85 - samples/sec: 3368.50 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-25 21:14:40,885 epoch 8 - iter 290/292 - loss 0.01628557 - time (sec): 13.13 - samples/sec: 3376.27 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-25 21:14:40,973 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 21:14:40,973 EPOCH 8 done: loss 0.0162 - lr: 0.000011 | |
| 2023-10-25 21:14:41,893 DEV : loss 0.1719065010547638 - f1-score (micro avg) 0.7582 | |
| 2023-10-25 21:14:41,897 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 21:14:43,194 epoch 9 - iter 29/292 - loss 0.00358527 - time (sec): 1.30 - samples/sec: 3663.02 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-25 21:14:44,499 epoch 9 - iter 58/292 - loss 0.00492909 - time (sec): 2.60 - samples/sec: 3524.73 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-25 21:14:45,755 epoch 9 - iter 87/292 - loss 0.00373125 - time (sec): 3.86 - samples/sec: 3372.51 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-25 21:14:47,134 epoch 9 - iter 116/292 - loss 0.00767643 - time (sec): 5.24 - samples/sec: 3419.71 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-25 21:14:48,469 epoch 9 - iter 145/292 - loss 0.01032308 - time (sec): 6.57 - samples/sec: 3470.78 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-25 21:14:49,777 epoch 9 - iter 174/292 - loss 0.01017440 - time (sec): 7.88 - samples/sec: 3476.45 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-25 21:14:51,085 epoch 9 - iter 203/292 - loss 0.00944404 - time (sec): 9.19 - samples/sec: 3441.81 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-25 21:14:52,353 epoch 9 - iter 232/292 - loss 0.01116023 - time (sec): 10.45 - samples/sec: 3406.07 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-25 21:14:53,666 epoch 9 - iter 261/292 - loss 0.01067018 - time (sec): 11.77 - samples/sec: 3371.12 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-25 21:14:54,957 epoch 9 - iter 290/292 - loss 0.00991839 - time (sec): 13.06 - samples/sec: 3384.07 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-25 21:14:55,046 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 21:14:55,047 EPOCH 9 done: loss 0.0099 - lr: 0.000006 | |
| 2023-10-25 21:14:55,967 DEV : loss 0.17519107460975647 - f1-score (micro avg) 0.7682 | |
| 2023-10-25 21:14:55,971 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 21:14:57,251 epoch 10 - iter 29/292 - loss 0.00493698 - time (sec): 1.28 - samples/sec: 3374.74 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-25 21:14:58,512 epoch 10 - iter 58/292 - loss 0.00797778 - time (sec): 2.54 - samples/sec: 3427.40 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-25 21:14:59,849 epoch 10 - iter 87/292 - loss 0.01121526 - time (sec): 3.88 - samples/sec: 3401.36 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-25 21:15:01,143 epoch 10 - iter 116/292 - loss 0.00908355 - time (sec): 5.17 - samples/sec: 3370.72 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-25 21:15:02,436 epoch 10 - iter 145/292 - loss 0.00825735 - time (sec): 6.46 - samples/sec: 3348.68 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-25 21:15:03,716 epoch 10 - iter 174/292 - loss 0.00808191 - time (sec): 7.74 - samples/sec: 3310.53 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-25 21:15:05,138 epoch 10 - iter 203/292 - loss 0.00845788 - time (sec): 9.17 - samples/sec: 3386.32 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-25 21:15:06,420 epoch 10 - iter 232/292 - loss 0.00783064 - time (sec): 10.45 - samples/sec: 3375.44 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-25 21:15:07,819 epoch 10 - iter 261/292 - loss 0.00786645 - time (sec): 11.85 - samples/sec: 3371.73 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-25 21:15:09,104 epoch 10 - iter 290/292 - loss 0.00733907 - time (sec): 13.13 - samples/sec: 3362.91 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-10-25 21:15:09,186 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 21:15:09,187 EPOCH 10 done: loss 0.0073 - lr: 0.000000 | |
| 2023-10-25 21:15:10,107 DEV : loss 0.177558034658432 - f1-score (micro avg) 0.7613 | |
| 2023-10-25 21:15:10,525 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-25 21:15:10,527 Loading model from best epoch ... | |
| 2023-10-25 21:15:12,151 SequenceTagger predicts: Dictionary with 17 tags: O, S-LOC, B-LOC, E-LOC, I-LOC, S-PER, B-PER, E-PER, I-PER, S-ORG, B-ORG, E-ORG, I-ORG, S-HumanProd, B-HumanProd, E-HumanProd, I-HumanProd | |
| 2023-10-25 21:15:13,880 | |
| Results: | |
| - F-score (micro) 0.7417 | |
| - F-score (macro) 0.6377 | |
| - Accuracy 0.6109 | |
| By class: | |
| precision recall f1-score support | |
| PER 0.7983 0.8190 0.8085 348 | |
| LOC 0.6450 0.8352 0.7279 261 | |
| ORG 0.4390 0.3462 0.3871 52 | |
| HumanProd 0.5517 0.7273 0.6275 22 | |
| micro avg 0.7020 0.7862 0.7417 683 | |
| macro avg 0.6085 0.6819 0.6377 683 | |
| weighted avg 0.7044 0.7862 0.7398 683 | |
| 2023-10-25 21:15:13,880 ---------------------------------------------------------------------------------------------------- | |