| 2023-10-20 10:00:36,344 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-20 10:00:36,344 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=13, bias=True) | |
| (loss_function): CrossEntropyLoss() | |
| )" | |
| 2023-10-20 10:00:36,344 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-20 10:00:36,344 MultiCorpus: 6183 train + 680 dev + 2113 test sentences | |
| - NER_HIPE_2022 Corpus: 6183 train + 680 dev + 2113 test sentences - /root/.flair/datasets/ner_hipe_2022/v2.1/topres19th/en/with_doc_seperator | |
| 2023-10-20 10:00:36,345 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-20 10:00:36,345 Train: 6183 sentences | |
| 2023-10-20 10:00:36,345 (train_with_dev=False, train_with_test=False) | |
| 2023-10-20 10:00:36,345 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-20 10:00:36,345 Training Params: | |
| 2023-10-20 10:00:36,345 - learning_rate: "3e-05" | |
| 2023-10-20 10:00:36,345 - mini_batch_size: "8" | |
| 2023-10-20 10:00:36,345 - max_epochs: "10" | |
| 2023-10-20 10:00:36,345 - shuffle: "True" | |
| 2023-10-20 10:00:36,345 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-20 10:00:36,345 Plugins: | |
| 2023-10-20 10:00:36,345 - TensorboardLogger | |
| 2023-10-20 10:00:36,345 - LinearScheduler | warmup_fraction: '0.1' | |
| 2023-10-20 10:00:36,345 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-20 10:00:36,345 Final evaluation on model from best epoch (best-model.pt) | |
| 2023-10-20 10:00:36,345 - metric: "('micro avg', 'f1-score')" | |
| 2023-10-20 10:00:36,345 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-20 10:00:36,345 Computation: | |
| 2023-10-20 10:00:36,345 - compute on device: cuda:0 | |
| 2023-10-20 10:00:36,345 - embedding storage: none | |
| 2023-10-20 10:00:36,345 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-20 10:00:36,345 Model training base path: "hmbench-topres19th/en-dbmdz/bert-tiny-historic-multilingual-cased-bs8-wsFalse-e10-lr3e-05-poolingfirst-layers-1-crfFalse-4" | |
| 2023-10-20 10:00:36,345 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-20 10:00:36,345 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-20 10:00:36,345 Logging anything other than scalars to TensorBoard is currently not supported. | |
| 2023-10-20 10:00:38,005 epoch 1 - iter 77/773 - loss 3.81241056 - time (sec): 1.66 - samples/sec: 7452.07 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-20 10:00:39,655 epoch 1 - iter 154/773 - loss 3.61951758 - time (sec): 3.31 - samples/sec: 7488.42 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-20 10:00:41,384 epoch 1 - iter 231/773 - loss 3.30275246 - time (sec): 5.04 - samples/sec: 7254.09 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-20 10:00:43,171 epoch 1 - iter 308/773 - loss 2.89747658 - time (sec): 6.82 - samples/sec: 7201.04 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-20 10:00:44,906 epoch 1 - iter 385/773 - loss 2.50629080 - time (sec): 8.56 - samples/sec: 7072.38 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-20 10:00:46,625 epoch 1 - iter 462/773 - loss 2.15258275 - time (sec): 10.28 - samples/sec: 7082.99 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-20 10:00:48,309 epoch 1 - iter 539/773 - loss 1.88716852 - time (sec): 11.96 - samples/sec: 7097.11 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-20 10:00:50,102 epoch 1 - iter 616/773 - loss 1.66647173 - time (sec): 13.76 - samples/sec: 7139.05 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-20 10:00:51,814 epoch 1 - iter 693/773 - loss 1.50059755 - time (sec): 15.47 - samples/sec: 7193.98 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-20 10:00:53,502 epoch 1 - iter 770/773 - loss 1.37496153 - time (sec): 17.16 - samples/sec: 7219.32 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-20 10:00:53,558 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-20 10:00:53,558 EPOCH 1 done: loss 1.3710 - lr: 0.000030 | |
| 2023-10-20 10:00:54,265 DEV : loss 0.15286844968795776 - f1-score (micro avg) 0.0 | |
| 2023-10-20 10:00:54,278 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-20 10:00:55,770 epoch 2 - iter 77/773 - loss 0.23214451 - time (sec): 1.49 - samples/sec: 8859.76 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-20 10:00:57,781 epoch 2 - iter 154/773 - loss 0.24097431 - time (sec): 3.50 - samples/sec: 7562.15 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-20 10:00:59,442 epoch 2 - iter 231/773 - loss 0.24356049 - time (sec): 5.16 - samples/sec: 7206.01 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-20 10:01:01,167 epoch 2 - iter 308/773 - loss 0.24470903 - time (sec): 6.89 - samples/sec: 7125.02 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-20 10:01:02,897 epoch 2 - iter 385/773 - loss 0.24262456 - time (sec): 8.62 - samples/sec: 7071.31 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-20 10:01:04,655 epoch 2 - iter 462/773 - loss 0.23888426 - time (sec): 10.38 - samples/sec: 7082.59 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-20 10:01:06,429 epoch 2 - iter 539/773 - loss 0.22964243 - time (sec): 12.15 - samples/sec: 7132.08 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-20 10:01:08,166 epoch 2 - iter 616/773 - loss 0.23048232 - time (sec): 13.89 - samples/sec: 7075.56 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-20 10:01:09,923 epoch 2 - iter 693/773 - loss 0.22376378 - time (sec): 15.64 - samples/sec: 7042.07 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-20 10:01:11,712 epoch 2 - iter 770/773 - loss 0.21921775 - time (sec): 17.43 - samples/sec: 7098.42 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-20 10:01:11,774 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-20 10:01:11,774 EPOCH 2 done: loss 0.2189 - lr: 0.000027 | |
| 2023-10-20 10:01:12,842 DEV : loss 0.10697879642248154 - f1-score (micro avg) 0.2113 | |
| 2023-10-20 10:01:12,854 saving best model | |
| 2023-10-20 10:01:12,882 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-20 10:01:14,585 epoch 3 - iter 77/773 - loss 0.17960081 - time (sec): 1.70 - samples/sec: 7327.95 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-20 10:01:16,295 epoch 3 - iter 154/773 - loss 0.17934017 - time (sec): 3.41 - samples/sec: 7047.87 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-20 10:01:18,025 epoch 3 - iter 231/773 - loss 0.17558716 - time (sec): 5.14 - samples/sec: 7188.59 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-20 10:01:19,753 epoch 3 - iter 308/773 - loss 0.17212991 - time (sec): 6.87 - samples/sec: 7197.64 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-20 10:01:21,516 epoch 3 - iter 385/773 - loss 0.17346036 - time (sec): 8.63 - samples/sec: 7219.64 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-20 10:01:23,201 epoch 3 - iter 462/773 - loss 0.17673051 - time (sec): 10.32 - samples/sec: 7092.46 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-20 10:01:24,962 epoch 3 - iter 539/773 - loss 0.17649304 - time (sec): 12.08 - samples/sec: 7123.71 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-20 10:01:26,682 epoch 3 - iter 616/773 - loss 0.17628556 - time (sec): 13.80 - samples/sec: 7172.27 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-20 10:01:28,419 epoch 3 - iter 693/773 - loss 0.17756531 - time (sec): 15.54 - samples/sec: 7157.36 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-20 10:01:30,165 epoch 3 - iter 770/773 - loss 0.17579288 - time (sec): 17.28 - samples/sec: 7169.81 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-20 10:01:30,225 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-20 10:01:30,225 EPOCH 3 done: loss 0.1759 - lr: 0.000023 | |
| 2023-10-20 10:01:31,314 DEV : loss 0.0952216237783432 - f1-score (micro avg) 0.3757 | |
| 2023-10-20 10:01:31,327 saving best model | |
| 2023-10-20 10:01:31,361 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-20 10:01:33,173 epoch 4 - iter 77/773 - loss 0.18477387 - time (sec): 1.81 - samples/sec: 7281.37 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-20 10:01:34,897 epoch 4 - iter 154/773 - loss 0.18279801 - time (sec): 3.53 - samples/sec: 7010.16 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-20 10:01:36,632 epoch 4 - iter 231/773 - loss 0.17577730 - time (sec): 5.27 - samples/sec: 6871.73 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-20 10:01:38,395 epoch 4 - iter 308/773 - loss 0.17374644 - time (sec): 7.03 - samples/sec: 7028.03 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-20 10:01:40,155 epoch 4 - iter 385/773 - loss 0.17036912 - time (sec): 8.79 - samples/sec: 6952.04 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-20 10:01:41,895 epoch 4 - iter 462/773 - loss 0.16676008 - time (sec): 10.53 - samples/sec: 6967.86 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-20 10:01:43,678 epoch 4 - iter 539/773 - loss 0.16364124 - time (sec): 12.32 - samples/sec: 6973.48 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-20 10:01:45,415 epoch 4 - iter 616/773 - loss 0.16324635 - time (sec): 14.05 - samples/sec: 7019.45 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-20 10:01:47,202 epoch 4 - iter 693/773 - loss 0.16215188 - time (sec): 15.84 - samples/sec: 7030.24 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-20 10:01:48,917 epoch 4 - iter 770/773 - loss 0.15946543 - time (sec): 17.56 - samples/sec: 7046.10 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-20 10:01:48,986 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-20 10:01:48,986 EPOCH 4 done: loss 0.1598 - lr: 0.000020 | |
| 2023-10-20 10:01:50,067 DEV : loss 0.08685088157653809 - f1-score (micro avg) 0.4806 | |
| 2023-10-20 10:01:50,079 saving best model | |
| 2023-10-20 10:01:50,119 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-20 10:01:51,873 epoch 5 - iter 77/773 - loss 0.14344519 - time (sec): 1.75 - samples/sec: 6814.44 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-20 10:01:53,683 epoch 5 - iter 154/773 - loss 0.15258628 - time (sec): 3.56 - samples/sec: 7121.76 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-20 10:01:55,431 epoch 5 - iter 231/773 - loss 0.15926291 - time (sec): 5.31 - samples/sec: 7141.00 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-20 10:01:57,170 epoch 5 - iter 308/773 - loss 0.15525040 - time (sec): 7.05 - samples/sec: 7002.21 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-20 10:01:59,041 epoch 5 - iter 385/773 - loss 0.15298376 - time (sec): 8.92 - samples/sec: 6989.00 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-20 10:02:00,849 epoch 5 - iter 462/773 - loss 0.14900655 - time (sec): 10.73 - samples/sec: 6924.76 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-20 10:02:02,653 epoch 5 - iter 539/773 - loss 0.14781168 - time (sec): 12.53 - samples/sec: 6941.72 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-20 10:02:04,495 epoch 5 - iter 616/773 - loss 0.15062811 - time (sec): 14.38 - samples/sec: 6896.32 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-20 10:02:06,282 epoch 5 - iter 693/773 - loss 0.15115235 - time (sec): 16.16 - samples/sec: 6910.24 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-20 10:02:08,002 epoch 5 - iter 770/773 - loss 0.14968908 - time (sec): 17.88 - samples/sec: 6919.99 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-20 10:02:08,074 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-20 10:02:08,074 EPOCH 5 done: loss 0.1495 - lr: 0.000017 | |
| 2023-10-20 10:02:09,173 DEV : loss 0.08496666699647903 - f1-score (micro avg) 0.4939 | |
| 2023-10-20 10:02:09,185 saving best model | |
| 2023-10-20 10:02:09,219 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-20 10:02:10,915 epoch 6 - iter 77/773 - loss 0.13683614 - time (sec): 1.70 - samples/sec: 6668.03 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-20 10:02:12,711 epoch 6 - iter 154/773 - loss 0.14211735 - time (sec): 3.49 - samples/sec: 6801.54 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-20 10:02:14,513 epoch 6 - iter 231/773 - loss 0.14128117 - time (sec): 5.29 - samples/sec: 6853.01 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-20 10:02:16,289 epoch 6 - iter 308/773 - loss 0.13590630 - time (sec): 7.07 - samples/sec: 6891.57 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-20 10:02:17,903 epoch 6 - iter 385/773 - loss 0.14259420 - time (sec): 8.68 - samples/sec: 7003.45 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-20 10:02:19,585 epoch 6 - iter 462/773 - loss 0.14552202 - time (sec): 10.37 - samples/sec: 7037.70 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-20 10:02:21,375 epoch 6 - iter 539/773 - loss 0.14254133 - time (sec): 12.16 - samples/sec: 7031.44 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-20 10:02:23,107 epoch 6 - iter 616/773 - loss 0.14102050 - time (sec): 13.89 - samples/sec: 7092.37 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-20 10:02:24,871 epoch 6 - iter 693/773 - loss 0.13907785 - time (sec): 15.65 - samples/sec: 7098.85 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-20 10:02:26,636 epoch 6 - iter 770/773 - loss 0.14100570 - time (sec): 17.42 - samples/sec: 7095.47 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-20 10:02:26,717 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-20 10:02:26,717 EPOCH 6 done: loss 0.1404 - lr: 0.000013 | |
| 2023-10-20 10:02:27,791 DEV : loss 0.08332625776529312 - f1-score (micro avg) 0.5304 | |
| 2023-10-20 10:02:27,802 saving best model | |
| 2023-10-20 10:02:27,836 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-20 10:02:29,593 epoch 7 - iter 77/773 - loss 0.14476114 - time (sec): 1.76 - samples/sec: 7188.18 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-20 10:02:31,331 epoch 7 - iter 154/773 - loss 0.14402242 - time (sec): 3.49 - samples/sec: 7109.92 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-20 10:02:33,063 epoch 7 - iter 231/773 - loss 0.14036025 - time (sec): 5.23 - samples/sec: 7082.29 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-20 10:02:34,756 epoch 7 - iter 308/773 - loss 0.14534767 - time (sec): 6.92 - samples/sec: 7173.84 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-20 10:02:36,559 epoch 7 - iter 385/773 - loss 0.14110367 - time (sec): 8.72 - samples/sec: 7275.71 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-20 10:02:38,203 epoch 7 - iter 462/773 - loss 0.13753663 - time (sec): 10.37 - samples/sec: 7309.11 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-20 10:02:39,822 epoch 7 - iter 539/773 - loss 0.13875122 - time (sec): 11.99 - samples/sec: 7318.44 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-20 10:02:41,511 epoch 7 - iter 616/773 - loss 0.13955186 - time (sec): 13.67 - samples/sec: 7296.14 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-20 10:02:43,257 epoch 7 - iter 693/773 - loss 0.13895365 - time (sec): 15.42 - samples/sec: 7257.89 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-20 10:02:44,971 epoch 7 - iter 770/773 - loss 0.13686198 - time (sec): 17.13 - samples/sec: 7227.08 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-20 10:02:45,031 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-20 10:02:45,031 EPOCH 7 done: loss 0.1368 - lr: 0.000010 | |
| 2023-10-20 10:02:46,107 DEV : loss 0.08445805311203003 - f1-score (micro avg) 0.5253 | |
| 2023-10-20 10:02:46,118 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-20 10:02:47,862 epoch 8 - iter 77/773 - loss 0.12222683 - time (sec): 1.74 - samples/sec: 7201.77 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-20 10:02:49,623 epoch 8 - iter 154/773 - loss 0.12160289 - time (sec): 3.50 - samples/sec: 7112.73 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-20 10:02:51,352 epoch 8 - iter 231/773 - loss 0.12601210 - time (sec): 5.23 - samples/sec: 7119.34 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-20 10:02:53,104 epoch 8 - iter 308/773 - loss 0.12825557 - time (sec): 6.99 - samples/sec: 7114.87 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-20 10:02:54,802 epoch 8 - iter 385/773 - loss 0.13149787 - time (sec): 8.68 - samples/sec: 7182.75 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-20 10:02:56,573 epoch 8 - iter 462/773 - loss 0.13242894 - time (sec): 10.45 - samples/sec: 7128.04 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-20 10:02:58,284 epoch 8 - iter 539/773 - loss 0.13472536 - time (sec): 12.17 - samples/sec: 7127.85 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-20 10:03:00,085 epoch 8 - iter 616/773 - loss 0.13365370 - time (sec): 13.97 - samples/sec: 7098.48 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-20 10:03:01,833 epoch 8 - iter 693/773 - loss 0.13290360 - time (sec): 15.71 - samples/sec: 7091.52 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-20 10:03:03,535 epoch 8 - iter 770/773 - loss 0.13146102 - time (sec): 17.42 - samples/sec: 7107.06 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-20 10:03:03,599 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-20 10:03:03,599 EPOCH 8 done: loss 0.1312 - lr: 0.000007 | |
| 2023-10-20 10:03:04,675 DEV : loss 0.08267096430063248 - f1-score (micro avg) 0.5442 | |
| 2023-10-20 10:03:04,687 saving best model | |
| 2023-10-20 10:03:04,730 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-20 10:03:06,377 epoch 9 - iter 77/773 - loss 0.13426845 - time (sec): 1.65 - samples/sec: 7221.24 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-20 10:03:08,121 epoch 9 - iter 154/773 - loss 0.12764335 - time (sec): 3.39 - samples/sec: 7073.83 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-20 10:03:09,885 epoch 9 - iter 231/773 - loss 0.13064958 - time (sec): 5.15 - samples/sec: 7054.91 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-20 10:03:11,689 epoch 9 - iter 308/773 - loss 0.12547793 - time (sec): 6.96 - samples/sec: 7098.59 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-20 10:03:13,457 epoch 9 - iter 385/773 - loss 0.12185205 - time (sec): 8.73 - samples/sec: 7038.94 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-20 10:03:15,360 epoch 9 - iter 462/773 - loss 0.12534457 - time (sec): 10.63 - samples/sec: 6904.04 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-20 10:03:17,212 epoch 9 - iter 539/773 - loss 0.12499457 - time (sec): 12.48 - samples/sec: 6875.73 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-20 10:03:19,029 epoch 9 - iter 616/773 - loss 0.12754088 - time (sec): 14.30 - samples/sec: 6896.18 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-20 10:03:20,794 epoch 9 - iter 693/773 - loss 0.12629823 - time (sec): 16.06 - samples/sec: 6965.13 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-20 10:03:22,545 epoch 9 - iter 770/773 - loss 0.12671079 - time (sec): 17.81 - samples/sec: 6951.05 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-20 10:03:22,608 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-20 10:03:22,609 EPOCH 9 done: loss 0.1270 - lr: 0.000003 | |
| 2023-10-20 10:03:23,687 DEV : loss 0.08247760683298111 - f1-score (micro avg) 0.5471 | |
| 2023-10-20 10:03:23,698 saving best model | |
| 2023-10-20 10:03:23,736 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-20 10:03:25,433 epoch 10 - iter 77/773 - loss 0.14764006 - time (sec): 1.70 - samples/sec: 6905.70 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-20 10:03:27,260 epoch 10 - iter 154/773 - loss 0.13385632 - time (sec): 3.52 - samples/sec: 6919.85 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-20 10:03:28,975 epoch 10 - iter 231/773 - loss 0.12965434 - time (sec): 5.24 - samples/sec: 7108.23 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-20 10:03:30,805 epoch 10 - iter 308/773 - loss 0.12967758 - time (sec): 7.07 - samples/sec: 7041.74 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-20 10:03:32,607 epoch 10 - iter 385/773 - loss 0.13165440 - time (sec): 8.87 - samples/sec: 6989.40 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-20 10:03:34,348 epoch 10 - iter 462/773 - loss 0.13289038 - time (sec): 10.61 - samples/sec: 6946.57 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-20 10:03:36,176 epoch 10 - iter 539/773 - loss 0.13066958 - time (sec): 12.44 - samples/sec: 6936.41 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-20 10:03:37,989 epoch 10 - iter 616/773 - loss 0.12645987 - time (sec): 14.25 - samples/sec: 6961.31 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-20 10:03:39,744 epoch 10 - iter 693/773 - loss 0.12677426 - time (sec): 16.01 - samples/sec: 6945.06 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-10-20 10:03:41,586 epoch 10 - iter 770/773 - loss 0.12613690 - time (sec): 17.85 - samples/sec: 6927.38 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-10-20 10:03:41,655 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-20 10:03:41,655 EPOCH 10 done: loss 0.1262 - lr: 0.000000 | |
| 2023-10-20 10:03:42,740 DEV : loss 0.08230794966220856 - f1-score (micro avg) 0.5483 | |
| 2023-10-20 10:03:42,752 saving best model | |
| 2023-10-20 10:03:42,817 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-20 10:03:42,817 Loading model from best epoch ... | |
| 2023-10-20 10:03:42,890 SequenceTagger predicts: Dictionary with 13 tags: O, S-LOC, B-LOC, E-LOC, I-LOC, S-BUILDING, B-BUILDING, E-BUILDING, I-BUILDING, S-STREET, B-STREET, E-STREET, I-STREET | |
| 2023-10-20 10:03:45,758 | |
| Results: | |
| - F-score (micro) 0.5024 | |
| - F-score (macro) 0.189 | |
| - Accuracy 0.3412 | |
| By class: | |
| precision recall f1-score support | |
| LOC 0.5714 0.5624 0.5669 946 | |
| BUILDING 0.0000 0.0000 0.0000 185 | |
| STREET 0.0000 0.0000 0.0000 56 | |
| micro avg 0.5714 0.4482 0.5024 1187 | |
| macro avg 0.1905 0.1875 0.1890 1187 | |
| weighted avg 0.4554 0.4482 0.4518 1187 | |
| 2023-10-20 10:03:45,758 ---------------------------------------------------------------------------------------------------- | |