| 2023-10-19 23:51:49,700 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:51:49,701 Model: "SequenceTagger( | |
| (embeddings): TransformerWordEmbeddings( | |
| (model): BertModel( | |
| (embeddings): BertEmbeddings( | |
| (word_embeddings): Embedding(32001, 128) | |
| (position_embeddings): Embedding(512, 128) | |
| (token_type_embeddings): Embedding(2, 128) | |
| (LayerNorm): LayerNorm((128,), eps=1e-12, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (encoder): BertEncoder( | |
| (layer): ModuleList( | |
| (0-1): 2 x BertLayer( | |
| (attention): BertAttention( | |
| (self): BertSelfAttention( | |
| (query): Linear(in_features=128, out_features=128, bias=True) | |
| (key): Linear(in_features=128, out_features=128, bias=True) | |
| (value): Linear(in_features=128, out_features=128, bias=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (output): BertSelfOutput( | |
| (dense): Linear(in_features=128, out_features=128, bias=True) | |
| (LayerNorm): LayerNorm((128,), eps=1e-12, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (intermediate): BertIntermediate( | |
| (dense): Linear(in_features=128, out_features=512, bias=True) | |
| (intermediate_act_fn): GELUActivation() | |
| ) | |
| (output): BertOutput( | |
| (dense): Linear(in_features=512, out_features=128, bias=True) | |
| (LayerNorm): LayerNorm((128,), eps=1e-12, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| ) | |
| ) | |
| (pooler): BertPooler( | |
| (dense): Linear(in_features=128, out_features=128, bias=True) | |
| (activation): Tanh() | |
| ) | |
| ) | |
| ) | |
| (locked_dropout): LockedDropout(p=0.5) | |
| (linear): Linear(in_features=128, out_features=17, bias=True) | |
| (loss_function): CrossEntropyLoss() | |
| )" | |
| 2023-10-19 23:51:49,701 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:51:49,701 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 | |
| 2023-10-19 23:51:49,701 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:51:49,701 Train: 1166 sentences | |
| 2023-10-19 23:51:49,701 (train_with_dev=False, train_with_test=False) | |
| 2023-10-19 23:51:49,701 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:51:49,701 Training Params: | |
| 2023-10-19 23:51:49,701 - learning_rate: "3e-05" | |
| 2023-10-19 23:51:49,701 - mini_batch_size: "8" | |
| 2023-10-19 23:51:49,701 - max_epochs: "10" | |
| 2023-10-19 23:51:49,701 - shuffle: "True" | |
| 2023-10-19 23:51:49,701 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:51:49,701 Plugins: | |
| 2023-10-19 23:51:49,701 - TensorboardLogger | |
| 2023-10-19 23:51:49,701 - LinearScheduler | warmup_fraction: '0.1' | |
| 2023-10-19 23:51:49,701 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:51:49,701 Final evaluation on model from best epoch (best-model.pt) | |
| 2023-10-19 23:51:49,701 - metric: "('micro avg', 'f1-score')" | |
| 2023-10-19 23:51:49,701 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:51:49,701 Computation: | |
| 2023-10-19 23:51:49,701 - compute on device: cuda:0 | |
| 2023-10-19 23:51:49,701 - embedding storage: none | |
| 2023-10-19 23:51:49,702 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:51:49,702 Model training base path: "hmbench-newseye/fi-dbmdz/bert-tiny-historic-multilingual-cased-bs8-wsFalse-e10-lr3e-05-poolingfirst-layers-1-crfFalse-3" | |
| 2023-10-19 23:51:49,702 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:51:49,702 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:51:49,702 Logging anything other than scalars to TensorBoard is currently not supported. | |
| 2023-10-19 23:51:50,088 epoch 1 - iter 14/146 - loss 3.34803276 - time (sec): 0.39 - samples/sec: 11886.51 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-19 23:51:50,441 epoch 1 - iter 28/146 - loss 3.24426997 - time (sec): 0.74 - samples/sec: 11746.87 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-19 23:51:50,828 epoch 1 - iter 42/146 - loss 3.17722726 - time (sec): 1.13 - samples/sec: 11334.14 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-19 23:51:51,227 epoch 1 - iter 56/146 - loss 3.06383245 - time (sec): 1.52 - samples/sec: 11127.79 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-19 23:51:51,611 epoch 1 - iter 70/146 - loss 2.97900869 - time (sec): 1.91 - samples/sec: 11251.57 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-19 23:51:51,985 epoch 1 - iter 84/146 - loss 2.86475164 - time (sec): 2.28 - samples/sec: 11411.19 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-19 23:51:52,374 epoch 1 - iter 98/146 - loss 2.76952224 - time (sec): 2.67 - samples/sec: 11378.82 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-19 23:51:52,748 epoch 1 - iter 112/146 - loss 2.62555563 - time (sec): 3.05 - samples/sec: 11482.65 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-19 23:51:53,129 epoch 1 - iter 126/146 - loss 2.50608976 - time (sec): 3.43 - samples/sec: 11324.46 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-19 23:51:53,511 epoch 1 - iter 140/146 - loss 2.38598195 - time (sec): 3.81 - samples/sec: 11288.10 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-19 23:51:53,672 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:51:53,672 EPOCH 1 done: loss 2.3402 - lr: 0.000029 | |
| 2023-10-19 23:51:53,941 DEV : loss 0.4833422005176544 - f1-score (micro avg) 0.0 | |
| 2023-10-19 23:51:53,945 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:51:54,358 epoch 2 - iter 14/146 - loss 1.00186629 - time (sec): 0.41 - samples/sec: 12089.20 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-19 23:51:54,720 epoch 2 - iter 28/146 - loss 0.89014949 - time (sec): 0.78 - samples/sec: 11314.02 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-19 23:51:55,079 epoch 2 - iter 42/146 - loss 0.85331323 - time (sec): 1.13 - samples/sec: 11572.81 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-19 23:51:55,473 epoch 2 - iter 56/146 - loss 0.82062153 - time (sec): 1.53 - samples/sec: 11530.13 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-19 23:51:55,826 epoch 2 - iter 70/146 - loss 0.80036944 - time (sec): 1.88 - samples/sec: 11591.03 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-19 23:51:56,200 epoch 2 - iter 84/146 - loss 0.78167558 - time (sec): 2.25 - samples/sec: 11607.64 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-19 23:51:56,541 epoch 2 - iter 98/146 - loss 0.73470966 - time (sec): 2.60 - samples/sec: 11570.72 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-19 23:51:56,922 epoch 2 - iter 112/146 - loss 0.71674782 - time (sec): 2.98 - samples/sec: 11688.35 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-19 23:51:57,290 epoch 2 - iter 126/146 - loss 0.70473681 - time (sec): 3.35 - samples/sec: 11606.83 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-19 23:51:57,656 epoch 2 - iter 140/146 - loss 0.70770530 - time (sec): 3.71 - samples/sec: 11598.03 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-19 23:51:57,796 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:51:57,796 EPOCH 2 done: loss 0.7028 - lr: 0.000027 | |
| 2023-10-19 23:51:58,422 DEV : loss 0.44611138105392456 - f1-score (micro avg) 0.0 | |
| 2023-10-19 23:51:58,426 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:51:58,949 epoch 3 - iter 14/146 - loss 0.56843240 - time (sec): 0.52 - samples/sec: 7685.20 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-19 23:51:59,330 epoch 3 - iter 28/146 - loss 0.55665083 - time (sec): 0.90 - samples/sec: 9273.02 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-19 23:51:59,705 epoch 3 - iter 42/146 - loss 0.56927226 - time (sec): 1.28 - samples/sec: 10481.34 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-19 23:52:00,049 epoch 3 - iter 56/146 - loss 0.56146026 - time (sec): 1.62 - samples/sec: 10990.27 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-19 23:52:00,407 epoch 3 - iter 70/146 - loss 0.56962488 - time (sec): 1.98 - samples/sec: 11026.51 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-19 23:52:00,760 epoch 3 - iter 84/146 - loss 0.55978929 - time (sec): 2.33 - samples/sec: 11177.29 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-19 23:52:01,117 epoch 3 - iter 98/146 - loss 0.55736095 - time (sec): 2.69 - samples/sec: 11279.49 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-19 23:52:01,491 epoch 3 - iter 112/146 - loss 0.57916592 - time (sec): 3.06 - samples/sec: 11199.25 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-19 23:52:01,868 epoch 3 - iter 126/146 - loss 0.60494417 - time (sec): 3.44 - samples/sec: 11332.47 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-19 23:52:02,213 epoch 3 - iter 140/146 - loss 0.59677716 - time (sec): 3.79 - samples/sec: 11354.76 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-19 23:52:02,351 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:52:02,351 EPOCH 3 done: loss 0.5947 - lr: 0.000024 | |
| 2023-10-19 23:52:02,980 DEV : loss 0.3864370584487915 - f1-score (micro avg) 0.0 | |
| 2023-10-19 23:52:02,984 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:52:03,349 epoch 4 - iter 14/146 - loss 0.51833400 - time (sec): 0.36 - samples/sec: 11745.60 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-19 23:52:03,714 epoch 4 - iter 28/146 - loss 0.54395629 - time (sec): 0.73 - samples/sec: 11621.06 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-19 23:52:04,082 epoch 4 - iter 42/146 - loss 0.56680138 - time (sec): 1.10 - samples/sec: 10967.22 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-19 23:52:04,447 epoch 4 - iter 56/146 - loss 0.57277620 - time (sec): 1.46 - samples/sec: 11339.24 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-19 23:52:04,825 epoch 4 - iter 70/146 - loss 0.63447119 - time (sec): 1.84 - samples/sec: 11379.23 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-19 23:52:05,194 epoch 4 - iter 84/146 - loss 0.61181656 - time (sec): 2.21 - samples/sec: 11408.00 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-19 23:52:05,552 epoch 4 - iter 98/146 - loss 0.58758215 - time (sec): 2.57 - samples/sec: 11328.25 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-19 23:52:05,957 epoch 4 - iter 112/146 - loss 0.57376561 - time (sec): 2.97 - samples/sec: 11463.68 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-19 23:52:06,331 epoch 4 - iter 126/146 - loss 0.57197538 - time (sec): 3.35 - samples/sec: 11366.94 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-19 23:52:06,689 epoch 4 - iter 140/146 - loss 0.57285088 - time (sec): 3.70 - samples/sec: 11470.39 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-19 23:52:06,850 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:52:06,850 EPOCH 4 done: loss 0.5641 - lr: 0.000020 | |
| 2023-10-19 23:52:07,480 DEV : loss 0.35983359813690186 - f1-score (micro avg) 0.0 | |
| 2023-10-19 23:52:07,485 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:52:07,886 epoch 5 - iter 14/146 - loss 0.72697613 - time (sec): 0.40 - samples/sec: 11787.78 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-19 23:52:08,229 epoch 5 - iter 28/146 - loss 0.67048227 - time (sec): 0.74 - samples/sec: 11342.21 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-19 23:52:08,606 epoch 5 - iter 42/146 - loss 0.60440180 - time (sec): 1.12 - samples/sec: 11690.40 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-19 23:52:08,982 epoch 5 - iter 56/146 - loss 0.56150800 - time (sec): 1.50 - samples/sec: 11649.36 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-19 23:52:09,373 epoch 5 - iter 70/146 - loss 0.52666893 - time (sec): 1.89 - samples/sec: 11755.06 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-19 23:52:09,725 epoch 5 - iter 84/146 - loss 0.51426781 - time (sec): 2.24 - samples/sec: 11594.14 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-19 23:52:10,084 epoch 5 - iter 98/146 - loss 0.50838649 - time (sec): 2.60 - samples/sec: 11665.32 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-19 23:52:10,429 epoch 5 - iter 112/146 - loss 0.50712580 - time (sec): 2.94 - samples/sec: 11427.86 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-19 23:52:10,808 epoch 5 - iter 126/146 - loss 0.52046347 - time (sec): 3.32 - samples/sec: 11439.33 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-19 23:52:11,153 epoch 5 - iter 140/146 - loss 0.51748259 - time (sec): 3.67 - samples/sec: 11606.10 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-19 23:52:11,300 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:52:11,300 EPOCH 5 done: loss 0.5165 - lr: 0.000017 | |
| 2023-10-19 23:52:11,942 DEV : loss 0.3400147259235382 - f1-score (micro avg) 0.0239 | |
| 2023-10-19 23:52:11,946 saving best model | |
| 2023-10-19 23:52:11,974 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:52:12,348 epoch 6 - iter 14/146 - loss 0.71859012 - time (sec): 0.37 - samples/sec: 11707.07 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-19 23:52:12,718 epoch 6 - iter 28/146 - loss 0.56899183 - time (sec): 0.74 - samples/sec: 11591.23 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-19 23:52:13,066 epoch 6 - iter 42/146 - loss 0.51990607 - time (sec): 1.09 - samples/sec: 11725.64 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-19 23:52:13,421 epoch 6 - iter 56/146 - loss 0.53360635 - time (sec): 1.45 - samples/sec: 11407.04 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-19 23:52:13,794 epoch 6 - iter 70/146 - loss 0.51135818 - time (sec): 1.82 - samples/sec: 11590.61 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-19 23:52:14,173 epoch 6 - iter 84/146 - loss 0.52944252 - time (sec): 2.20 - samples/sec: 11857.16 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-19 23:52:14,529 epoch 6 - iter 98/146 - loss 0.51191496 - time (sec): 2.55 - samples/sec: 11896.68 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-19 23:52:14,897 epoch 6 - iter 112/146 - loss 0.50006322 - time (sec): 2.92 - samples/sec: 11820.64 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-19 23:52:15,263 epoch 6 - iter 126/146 - loss 0.49173276 - time (sec): 3.29 - samples/sec: 11820.55 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-19 23:52:15,633 epoch 6 - iter 140/146 - loss 0.48245262 - time (sec): 3.66 - samples/sec: 11790.09 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-19 23:52:15,786 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:52:15,786 EPOCH 6 done: loss 0.4839 - lr: 0.000014 | |
| 2023-10-19 23:52:16,429 DEV : loss 0.330739289522171 - f1-score (micro avg) 0.0578 | |
| 2023-10-19 23:52:16,433 saving best model | |
| 2023-10-19 23:52:16,467 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:52:16,808 epoch 7 - iter 14/146 - loss 0.39481050 - time (sec): 0.34 - samples/sec: 10822.62 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-19 23:52:17,182 epoch 7 - iter 28/146 - loss 0.37652749 - time (sec): 0.71 - samples/sec: 10971.66 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-19 23:52:17,551 epoch 7 - iter 42/146 - loss 0.41835909 - time (sec): 1.08 - samples/sec: 11195.45 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-19 23:52:17,895 epoch 7 - iter 56/146 - loss 0.42637595 - time (sec): 1.43 - samples/sec: 10986.57 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-19 23:52:18,285 epoch 7 - iter 70/146 - loss 0.46759904 - time (sec): 1.82 - samples/sec: 11177.84 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-19 23:52:18,641 epoch 7 - iter 84/146 - loss 0.47208007 - time (sec): 2.17 - samples/sec: 11097.59 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-19 23:52:19,156 epoch 7 - iter 98/146 - loss 0.46177264 - time (sec): 2.69 - samples/sec: 10435.71 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-19 23:52:19,543 epoch 7 - iter 112/146 - loss 0.47139861 - time (sec): 3.07 - samples/sec: 10770.10 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-19 23:52:19,935 epoch 7 - iter 126/146 - loss 0.47595257 - time (sec): 3.47 - samples/sec: 10955.23 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-19 23:52:20,297 epoch 7 - iter 140/146 - loss 0.46725905 - time (sec): 3.83 - samples/sec: 11088.10 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-19 23:52:20,466 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:52:20,466 EPOCH 7 done: loss 0.4635 - lr: 0.000010 | |
| 2023-10-19 23:52:21,114 DEV : loss 0.32605770230293274 - f1-score (micro avg) 0.0972 | |
| 2023-10-19 23:52:21,118 saving best model | |
| 2023-10-19 23:52:21,151 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:52:21,533 epoch 8 - iter 14/146 - loss 0.39063923 - time (sec): 0.38 - samples/sec: 11350.79 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-19 23:52:21,890 epoch 8 - iter 28/146 - loss 0.52358403 - time (sec): 0.74 - samples/sec: 11999.88 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-19 23:52:22,256 epoch 8 - iter 42/146 - loss 0.47448311 - time (sec): 1.10 - samples/sec: 11965.72 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-19 23:52:22,629 epoch 8 - iter 56/146 - loss 0.44651128 - time (sec): 1.48 - samples/sec: 11768.99 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-19 23:52:23,000 epoch 8 - iter 70/146 - loss 0.43905400 - time (sec): 1.85 - samples/sec: 11734.69 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-19 23:52:23,336 epoch 8 - iter 84/146 - loss 0.43488104 - time (sec): 2.18 - samples/sec: 11814.12 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-19 23:52:23,679 epoch 8 - iter 98/146 - loss 0.44948982 - time (sec): 2.53 - samples/sec: 11595.87 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-19 23:52:24,064 epoch 8 - iter 112/146 - loss 0.45606613 - time (sec): 2.91 - samples/sec: 11562.77 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-19 23:52:24,437 epoch 8 - iter 126/146 - loss 0.44624813 - time (sec): 3.28 - samples/sec: 11655.29 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-19 23:52:24,792 epoch 8 - iter 140/146 - loss 0.44820969 - time (sec): 3.64 - samples/sec: 11694.03 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-19 23:52:24,948 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:52:24,948 EPOCH 8 done: loss 0.4477 - lr: 0.000007 | |
| 2023-10-19 23:52:25,586 DEV : loss 0.3263406455516815 - f1-score (micro avg) 0.1153 | |
| 2023-10-19 23:52:25,590 saving best model | |
| 2023-10-19 23:52:25,622 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:52:25,985 epoch 9 - iter 14/146 - loss 0.37820188 - time (sec): 0.36 - samples/sec: 10688.65 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-19 23:52:26,348 epoch 9 - iter 28/146 - loss 0.43671802 - time (sec): 0.73 - samples/sec: 10798.78 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-19 23:52:26,711 epoch 9 - iter 42/146 - loss 0.41517691 - time (sec): 1.09 - samples/sec: 11087.48 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-19 23:52:27,068 epoch 9 - iter 56/146 - loss 0.41215518 - time (sec): 1.44 - samples/sec: 11017.47 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-19 23:52:27,440 epoch 9 - iter 70/146 - loss 0.41827437 - time (sec): 1.82 - samples/sec: 11438.00 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-19 23:52:27,791 epoch 9 - iter 84/146 - loss 0.42593948 - time (sec): 2.17 - samples/sec: 11533.40 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-19 23:52:28,171 epoch 9 - iter 98/146 - loss 0.44034346 - time (sec): 2.55 - samples/sec: 11779.63 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-19 23:52:28,533 epoch 9 - iter 112/146 - loss 0.44311122 - time (sec): 2.91 - samples/sec: 11922.65 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-19 23:52:28,895 epoch 9 - iter 126/146 - loss 0.44155197 - time (sec): 3.27 - samples/sec: 12014.38 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-19 23:52:29,249 epoch 9 - iter 140/146 - loss 0.44005196 - time (sec): 3.63 - samples/sec: 11838.33 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-19 23:52:29,394 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:52:29,394 EPOCH 9 done: loss 0.4382 - lr: 0.000004 | |
| 2023-10-19 23:52:30,032 DEV : loss 0.3212380111217499 - f1-score (micro avg) 0.1858 | |
| 2023-10-19 23:52:30,036 saving best model | |
| 2023-10-19 23:52:30,068 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:52:30,452 epoch 10 - iter 14/146 - loss 0.32923291 - time (sec): 0.38 - samples/sec: 13011.39 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-19 23:52:30,810 epoch 10 - iter 28/146 - loss 0.38363662 - time (sec): 0.74 - samples/sec: 12147.27 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-19 23:52:31,181 epoch 10 - iter 42/146 - loss 0.38745870 - time (sec): 1.11 - samples/sec: 11796.33 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-19 23:52:31,543 epoch 10 - iter 56/146 - loss 0.37499813 - time (sec): 1.47 - samples/sec: 11874.41 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-19 23:52:31,922 epoch 10 - iter 70/146 - loss 0.39212077 - time (sec): 1.85 - samples/sec: 11639.66 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-19 23:52:32,302 epoch 10 - iter 84/146 - loss 0.41564761 - time (sec): 2.23 - samples/sec: 11571.15 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-19 23:52:32,647 epoch 10 - iter 98/146 - loss 0.42084198 - time (sec): 2.58 - samples/sec: 11389.64 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-19 23:52:33,018 epoch 10 - iter 112/146 - loss 0.42000229 - time (sec): 2.95 - samples/sec: 11351.89 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-19 23:52:33,380 epoch 10 - iter 126/146 - loss 0.43344724 - time (sec): 3.31 - samples/sec: 11581.27 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-19 23:52:33,752 epoch 10 - iter 140/146 - loss 0.43011787 - time (sec): 3.68 - samples/sec: 11638.03 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-10-19 23:52:33,905 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:52:33,906 EPOCH 10 done: loss 0.4317 - lr: 0.000000 | |
| 2023-10-19 23:52:34,546 DEV : loss 0.32181745767593384 - f1-score (micro avg) 0.1801 | |
| 2023-10-19 23:52:34,578 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:52:34,579 Loading model from best epoch ... | |
| 2023-10-19 23:52:34,653 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 | |
| 2023-10-19 23:52:35,708 | |
| Results: | |
| - F-score (micro) 0.1645 | |
| - F-score (macro) 0.0772 | |
| - Accuracy 0.0923 | |
| By class: | |
| precision recall f1-score support | |
| PER 0.2151 0.2126 0.2139 348 | |
| LOC 0.2727 0.0575 0.0949 261 | |
| ORG 0.0000 0.0000 0.0000 52 | |
| HumanProd 0.0000 0.0000 0.0000 22 | |
| micro avg 0.2231 0.1303 0.1645 683 | |
| macro avg 0.1220 0.0675 0.0772 683 | |
| weighted avg 0.2138 0.1303 0.1453 683 | |
| 2023-10-19 23:52:35,708 ---------------------------------------------------------------------------------------------------- | |