| 2023-10-19 23:55:49,914 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:55:49,915 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 23:55:49,915 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:55:49,915 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 23:55:49,915 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:55:49,915 Train: 1166 sentences | |
| 2023-10-19 23:55:49,915 (train_with_dev=False, train_with_test=False) | |
| 2023-10-19 23:55:49,915 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:55:49,915 Training Params: | |
| 2023-10-19 23:55:49,915 - learning_rate: "3e-05" | |
| 2023-10-19 23:55:49,915 - mini_batch_size: "8" | |
| 2023-10-19 23:55:49,915 - max_epochs: "10" | |
| 2023-10-19 23:55:49,915 - shuffle: "True" | |
| 2023-10-19 23:55:49,915 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:55:49,915 Plugins: | |
| 2023-10-19 23:55:49,915 - TensorboardLogger | |
| 2023-10-19 23:55:49,915 - LinearScheduler | warmup_fraction: '0.1' | |
| 2023-10-19 23:55:49,915 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:55:49,915 Final evaluation on model from best epoch (best-model.pt) | |
| 2023-10-19 23:55:49,915 - metric: "('micro avg', 'f1-score')" | |
| 2023-10-19 23:55:49,915 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:55:49,915 Computation: | |
| 2023-10-19 23:55:49,915 - compute on device: cuda:0 | |
| 2023-10-19 23:55:49,915 - embedding storage: none | |
| 2023-10-19 23:55:49,916 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:55:49,916 Model training base path: "hmbench-newseye/fi-dbmdz/bert-tiny-historic-multilingual-cased-bs8-wsFalse-e10-lr3e-05-poolingfirst-layers-1-crfFalse-4" | |
| 2023-10-19 23:55:49,916 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:55:49,916 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:55:49,916 Logging anything other than scalars to TensorBoard is currently not supported. | |
| 2023-10-19 23:55:50,257 epoch 1 - iter 14/146 - loss 3.62686657 - time (sec): 0.34 - samples/sec: 11462.03 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-19 23:55:50,667 epoch 1 - iter 28/146 - loss 3.56566381 - time (sec): 0.75 - samples/sec: 12179.62 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-19 23:55:51,024 epoch 1 - iter 42/146 - loss 3.54309758 - time (sec): 1.11 - samples/sec: 11595.73 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-19 23:55:51,375 epoch 1 - iter 56/146 - loss 3.49169459 - time (sec): 1.46 - samples/sec: 11651.88 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-19 23:55:51,731 epoch 1 - iter 70/146 - loss 3.41550947 - time (sec): 1.81 - samples/sec: 11684.22 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-19 23:55:52,075 epoch 1 - iter 84/146 - loss 3.30661928 - time (sec): 2.16 - samples/sec: 11659.69 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-19 23:55:52,445 epoch 1 - iter 98/146 - loss 3.16012091 - time (sec): 2.53 - samples/sec: 11732.42 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-19 23:55:52,826 epoch 1 - iter 112/146 - loss 3.01059943 - time (sec): 2.91 - samples/sec: 11857.44 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-19 23:55:53,168 epoch 1 - iter 126/146 - loss 2.85714802 - time (sec): 3.25 - samples/sec: 11958.56 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-19 23:55:53,513 epoch 1 - iter 140/146 - loss 2.72108786 - time (sec): 3.60 - samples/sec: 11862.69 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-19 23:55:53,663 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:55:53,663 EPOCH 1 done: loss 2.6533 - lr: 0.000029 | |
| 2023-10-19 23:55:54,077 DEV : loss 0.6145911812782288 - f1-score (micro avg) 0.0 | |
| 2023-10-19 23:55:54,081 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:55:54,384 epoch 2 - iter 14/146 - loss 1.01168374 - time (sec): 0.30 - samples/sec: 10680.08 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-19 23:55:54,732 epoch 2 - iter 28/146 - loss 0.94678590 - time (sec): 0.65 - samples/sec: 12103.77 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-19 23:55:55,052 epoch 2 - iter 42/146 - loss 0.88474481 - time (sec): 0.97 - samples/sec: 12016.96 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-19 23:55:55,410 epoch 2 - iter 56/146 - loss 0.84644859 - time (sec): 1.33 - samples/sec: 11952.94 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-19 23:55:55,772 epoch 2 - iter 70/146 - loss 0.82087110 - time (sec): 1.69 - samples/sec: 12197.15 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-19 23:55:56,176 epoch 2 - iter 84/146 - loss 0.82573188 - time (sec): 2.10 - samples/sec: 12233.44 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-19 23:55:56,548 epoch 2 - iter 98/146 - loss 0.78402906 - time (sec): 2.47 - samples/sec: 12422.83 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-19 23:55:56,896 epoch 2 - iter 112/146 - loss 0.76691151 - time (sec): 2.82 - samples/sec: 12174.71 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-19 23:55:57,260 epoch 2 - iter 126/146 - loss 0.74906536 - time (sec): 3.18 - samples/sec: 12104.22 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-19 23:55:57,628 epoch 2 - iter 140/146 - loss 0.73743452 - time (sec): 3.55 - samples/sec: 12066.27 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-19 23:55:57,770 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:55:57,770 EPOCH 2 done: loss 0.7358 - lr: 0.000027 | |
| 2023-10-19 23:55:58,418 DEV : loss 0.4394523501396179 - f1-score (micro avg) 0.0 | |
| 2023-10-19 23:55:58,422 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:55:58,789 epoch 3 - iter 14/146 - loss 0.55148619 - time (sec): 0.37 - samples/sec: 12383.51 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-19 23:55:59,175 epoch 3 - iter 28/146 - loss 0.59695029 - time (sec): 0.75 - samples/sec: 12007.04 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-19 23:55:59,521 epoch 3 - iter 42/146 - loss 0.61934555 - time (sec): 1.10 - samples/sec: 11516.03 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-19 23:55:59,885 epoch 3 - iter 56/146 - loss 0.60983026 - time (sec): 1.46 - samples/sec: 11617.10 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-19 23:56:00,238 epoch 3 - iter 70/146 - loss 0.62579085 - time (sec): 1.82 - samples/sec: 11513.86 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-19 23:56:00,598 epoch 3 - iter 84/146 - loss 0.62085526 - time (sec): 2.18 - samples/sec: 11495.44 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-19 23:56:00,979 epoch 3 - iter 98/146 - loss 0.60632732 - time (sec): 2.56 - samples/sec: 11717.36 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-19 23:56:01,356 epoch 3 - iter 112/146 - loss 0.62524719 - time (sec): 2.93 - samples/sec: 11811.94 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-19 23:56:01,706 epoch 3 - iter 126/146 - loss 0.61922831 - time (sec): 3.28 - samples/sec: 11741.34 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-19 23:56:02,056 epoch 3 - iter 140/146 - loss 0.61879485 - time (sec): 3.63 - samples/sec: 11646.27 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-19 23:56:02,223 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:56:02,223 EPOCH 3 done: loss 0.6072 - lr: 0.000024 | |
| 2023-10-19 23:56:02,848 DEV : loss 0.3797164857387543 - f1-score (micro avg) 0.0 | |
| 2023-10-19 23:56:02,851 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:56:03,218 epoch 4 - iter 14/146 - loss 0.58641619 - time (sec): 0.37 - samples/sec: 12170.12 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-19 23:56:03,592 epoch 4 - iter 28/146 - loss 0.57181105 - time (sec): 0.74 - samples/sec: 12468.22 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-19 23:56:03,978 epoch 4 - iter 42/146 - loss 0.52217062 - time (sec): 1.13 - samples/sec: 12377.06 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-19 23:56:04,330 epoch 4 - iter 56/146 - loss 0.52381805 - time (sec): 1.48 - samples/sec: 11812.83 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-19 23:56:04,680 epoch 4 - iter 70/146 - loss 0.52577098 - time (sec): 1.83 - samples/sec: 11554.17 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-19 23:56:05,045 epoch 4 - iter 84/146 - loss 0.51450474 - time (sec): 2.19 - samples/sec: 11452.25 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-19 23:56:05,385 epoch 4 - iter 98/146 - loss 0.51166184 - time (sec): 2.53 - samples/sec: 11274.24 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-19 23:56:05,773 epoch 4 - iter 112/146 - loss 0.51209906 - time (sec): 2.92 - samples/sec: 11425.38 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-19 23:56:06,157 epoch 4 - iter 126/146 - loss 0.54642243 - time (sec): 3.30 - samples/sec: 11674.51 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-19 23:56:06,509 epoch 4 - iter 140/146 - loss 0.54514031 - time (sec): 3.66 - samples/sec: 11603.60 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-19 23:56:06,668 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:56:06,668 EPOCH 4 done: loss 0.5436 - lr: 0.000020 | |
| 2023-10-19 23:56:07,301 DEV : loss 0.34846723079681396 - f1-score (micro avg) 0.0 | |
| 2023-10-19 23:56:07,305 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:56:07,684 epoch 5 - iter 14/146 - loss 0.48210081 - time (sec): 0.38 - samples/sec: 10721.55 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-19 23:56:08,065 epoch 5 - iter 28/146 - loss 0.48716782 - time (sec): 0.76 - samples/sec: 11473.13 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-19 23:56:08,444 epoch 5 - iter 42/146 - loss 0.51726817 - time (sec): 1.14 - samples/sec: 11747.61 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-19 23:56:08,799 epoch 5 - iter 56/146 - loss 0.52378662 - time (sec): 1.49 - samples/sec: 11395.11 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-19 23:56:09,173 epoch 5 - iter 70/146 - loss 0.52298388 - time (sec): 1.87 - samples/sec: 11618.95 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-19 23:56:09,546 epoch 5 - iter 84/146 - loss 0.52146337 - time (sec): 2.24 - samples/sec: 11490.07 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-19 23:56:09,917 epoch 5 - iter 98/146 - loss 0.52723859 - time (sec): 2.61 - samples/sec: 11397.33 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-19 23:56:10,438 epoch 5 - iter 112/146 - loss 0.51952344 - time (sec): 3.13 - samples/sec: 10819.48 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-19 23:56:10,776 epoch 5 - iter 126/146 - loss 0.51715617 - time (sec): 3.47 - samples/sec: 10972.98 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-19 23:56:11,153 epoch 5 - iter 140/146 - loss 0.49965520 - time (sec): 3.85 - samples/sec: 11217.58 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-19 23:56:11,298 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:56:11,298 EPOCH 5 done: loss 0.5025 - lr: 0.000017 | |
| 2023-10-19 23:56:11,928 DEV : loss 0.3356049656867981 - f1-score (micro avg) 0.0 | |
| 2023-10-19 23:56:11,932 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:56:12,289 epoch 6 - iter 14/146 - loss 0.51328999 - time (sec): 0.36 - samples/sec: 12430.14 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-19 23:56:12,646 epoch 6 - iter 28/146 - loss 0.50111882 - time (sec): 0.71 - samples/sec: 12164.80 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-19 23:56:12,997 epoch 6 - iter 42/146 - loss 0.47633665 - time (sec): 1.06 - samples/sec: 11765.26 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-19 23:56:13,368 epoch 6 - iter 56/146 - loss 0.50441129 - time (sec): 1.44 - samples/sec: 11938.40 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-19 23:56:13,736 epoch 6 - iter 70/146 - loss 0.48930849 - time (sec): 1.80 - samples/sec: 11776.73 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-19 23:56:14,150 epoch 6 - iter 84/146 - loss 0.48837595 - time (sec): 2.22 - samples/sec: 12129.85 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-19 23:56:14,527 epoch 6 - iter 98/146 - loss 0.49885434 - time (sec): 2.59 - samples/sec: 11969.84 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-19 23:56:14,889 epoch 6 - iter 112/146 - loss 0.48721693 - time (sec): 2.96 - samples/sec: 11934.58 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-19 23:56:15,237 epoch 6 - iter 126/146 - loss 0.48865106 - time (sec): 3.30 - samples/sec: 11751.03 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-19 23:56:15,599 epoch 6 - iter 140/146 - loss 0.48424717 - time (sec): 3.67 - samples/sec: 11597.07 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-19 23:56:15,749 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:56:15,749 EPOCH 6 done: loss 0.4803 - lr: 0.000014 | |
| 2023-10-19 23:56:16,391 DEV : loss 0.33338305354118347 - f1-score (micro avg) 0.0159 | |
| 2023-10-19 23:56:16,395 saving best model | |
| 2023-10-19 23:56:16,424 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:56:16,810 epoch 7 - iter 14/146 - loss 0.51247900 - time (sec): 0.39 - samples/sec: 10542.60 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-19 23:56:17,182 epoch 7 - iter 28/146 - loss 0.46353999 - time (sec): 0.76 - samples/sec: 11315.92 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-19 23:56:17,538 epoch 7 - iter 42/146 - loss 0.47267613 - time (sec): 1.11 - samples/sec: 12103.13 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-19 23:56:17,909 epoch 7 - iter 56/146 - loss 0.51136275 - time (sec): 1.48 - samples/sec: 11998.57 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-19 23:56:18,283 epoch 7 - iter 70/146 - loss 0.49491599 - time (sec): 1.86 - samples/sec: 11859.20 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-19 23:56:18,648 epoch 7 - iter 84/146 - loss 0.49513367 - time (sec): 2.22 - samples/sec: 11602.73 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-19 23:56:18,991 epoch 7 - iter 98/146 - loss 0.48191917 - time (sec): 2.57 - samples/sec: 11562.30 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-19 23:56:19,373 epoch 7 - iter 112/146 - loss 0.48660231 - time (sec): 2.95 - samples/sec: 11284.94 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-19 23:56:19,779 epoch 7 - iter 126/146 - loss 0.47276807 - time (sec): 3.35 - samples/sec: 11505.26 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-19 23:56:20,145 epoch 7 - iter 140/146 - loss 0.46794068 - time (sec): 3.72 - samples/sec: 11482.84 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-19 23:56:20,309 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:56:20,309 EPOCH 7 done: loss 0.4652 - lr: 0.000010 | |
| 2023-10-19 23:56:20,961 DEV : loss 0.3205569088459015 - f1-score (micro avg) 0.0643 | |
| 2023-10-19 23:56:20,965 saving best model | |
| 2023-10-19 23:56:21,012 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:56:21,398 epoch 8 - iter 14/146 - loss 0.40190856 - time (sec): 0.39 - samples/sec: 11719.30 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-19 23:56:21,801 epoch 8 - iter 28/146 - loss 0.44444101 - time (sec): 0.79 - samples/sec: 12183.11 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-19 23:56:22,130 epoch 8 - iter 42/146 - loss 0.44314790 - time (sec): 1.12 - samples/sec: 11777.77 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-19 23:56:22,520 epoch 8 - iter 56/146 - loss 0.43739722 - time (sec): 1.51 - samples/sec: 11786.96 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-19 23:56:22,869 epoch 8 - iter 70/146 - loss 0.44209666 - time (sec): 1.86 - samples/sec: 11339.21 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-19 23:56:23,229 epoch 8 - iter 84/146 - loss 0.44111953 - time (sec): 2.22 - samples/sec: 11001.38 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-19 23:56:23,618 epoch 8 - iter 98/146 - loss 0.45685855 - time (sec): 2.61 - samples/sec: 11135.51 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-19 23:56:23,986 epoch 8 - iter 112/146 - loss 0.44776697 - time (sec): 2.97 - samples/sec: 11397.68 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-19 23:56:24,374 epoch 8 - iter 126/146 - loss 0.44711644 - time (sec): 3.36 - samples/sec: 11425.36 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-19 23:56:24,755 epoch 8 - iter 140/146 - loss 0.44596266 - time (sec): 3.74 - samples/sec: 11451.64 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-19 23:56:24,916 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:56:24,916 EPOCH 8 done: loss 0.4450 - lr: 0.000007 | |
| 2023-10-19 23:56:25,551 DEV : loss 0.3211706280708313 - f1-score (micro avg) 0.0707 | |
| 2023-10-19 23:56:25,555 saving best model | |
| 2023-10-19 23:56:25,587 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:56:25,942 epoch 9 - iter 14/146 - loss 0.41113884 - time (sec): 0.35 - samples/sec: 10970.83 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-19 23:56:26,317 epoch 9 - iter 28/146 - loss 0.46709047 - time (sec): 0.73 - samples/sec: 11164.26 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-19 23:56:26,657 epoch 9 - iter 42/146 - loss 0.46730149 - time (sec): 1.07 - samples/sec: 10630.35 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-19 23:56:27,014 epoch 9 - iter 56/146 - loss 0.47270215 - time (sec): 1.43 - samples/sec: 10837.67 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-19 23:56:27,384 epoch 9 - iter 70/146 - loss 0.46801889 - time (sec): 1.80 - samples/sec: 11086.23 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-19 23:56:27,760 epoch 9 - iter 84/146 - loss 0.46293481 - time (sec): 2.17 - samples/sec: 11335.03 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-19 23:56:28,130 epoch 9 - iter 98/146 - loss 0.46472869 - time (sec): 2.54 - samples/sec: 11343.97 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-19 23:56:28,649 epoch 9 - iter 112/146 - loss 0.46885479 - time (sec): 3.06 - samples/sec: 10880.87 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-19 23:56:29,036 epoch 9 - iter 126/146 - loss 0.45905054 - time (sec): 3.45 - samples/sec: 11042.62 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-19 23:56:29,430 epoch 9 - iter 140/146 - loss 0.44994878 - time (sec): 3.84 - samples/sec: 11214.07 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-19 23:56:29,569 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:56:29,570 EPOCH 9 done: loss 0.4484 - lr: 0.000004 | |
| 2023-10-19 23:56:30,206 DEV : loss 0.3181568682193756 - f1-score (micro avg) 0.1063 | |
| 2023-10-19 23:56:30,210 saving best model | |
| 2023-10-19 23:56:30,244 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:56:30,637 epoch 10 - iter 14/146 - loss 0.35982159 - time (sec): 0.39 - samples/sec: 12001.18 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-19 23:56:31,027 epoch 10 - iter 28/146 - loss 0.43016882 - time (sec): 0.78 - samples/sec: 12131.26 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-19 23:56:31,382 epoch 10 - iter 42/146 - loss 0.40530873 - time (sec): 1.14 - samples/sec: 12189.99 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-19 23:56:31,738 epoch 10 - iter 56/146 - loss 0.40504319 - time (sec): 1.49 - samples/sec: 11983.54 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-19 23:56:32,072 epoch 10 - iter 70/146 - loss 0.42251256 - time (sec): 1.83 - samples/sec: 11478.97 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-19 23:56:32,444 epoch 10 - iter 84/146 - loss 0.41757393 - time (sec): 2.20 - samples/sec: 11724.88 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-19 23:56:32,800 epoch 10 - iter 98/146 - loss 0.41278875 - time (sec): 2.56 - samples/sec: 11633.49 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-19 23:56:33,178 epoch 10 - iter 112/146 - loss 0.42903464 - time (sec): 2.93 - samples/sec: 11796.43 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-19 23:56:33,536 epoch 10 - iter 126/146 - loss 0.43335473 - time (sec): 3.29 - samples/sec: 11618.36 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-19 23:56:33,910 epoch 10 - iter 140/146 - loss 0.43507462 - time (sec): 3.67 - samples/sec: 11645.96 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-10-19 23:56:34,057 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:56:34,057 EPOCH 10 done: loss 0.4355 - lr: 0.000000 | |
| 2023-10-19 23:56:34,694 DEV : loss 0.31846562027931213 - f1-score (micro avg) 0.1049 | |
| 2023-10-19 23:56:34,725 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 23:56:34,726 Loading model from best epoch ... | |
| 2023-10-19 23:56:34,799 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 23:56:35,694 | |
| Results: | |
| - F-score (micro) 0.172 | |
| - F-score (macro) 0.0739 | |
| - Accuracy 0.0958 | |
| By class: | |
| precision recall f1-score support | |
| PER 0.2470 0.2328 0.2396 348 | |
| LOC 0.3333 0.0307 0.0561 261 | |
| ORG 0.0000 0.0000 0.0000 52 | |
| HumanProd 0.0000 0.0000 0.0000 22 | |
| micro avg 0.2528 0.1303 0.1720 683 | |
| macro avg 0.1451 0.0659 0.0739 683 | |
| weighted avg 0.2532 0.1303 0.1436 683 | |
| 2023-10-19 23:56:35,694 ---------------------------------------------------------------------------------------------------- | |