| 2023-10-18 21:44:50,558 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:44:50,559 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() | |
| )" | |
| 2023-10-18 21:44:50,559 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:44:50,559 MultiCorpus: 7936 train + 992 dev + 992 test sentences | |
| - NER_ICDAR_EUROPEANA Corpus: 7936 train + 992 dev + 992 test sentences - /root/.flair/datasets/ner_icdar_europeana/fr | |
| 2023-10-18 21:44:50,559 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:44:50,559 Train: 7936 sentences | |
| 2023-10-18 21:44:50,559 (train_with_dev=False, train_with_test=False) | |
| 2023-10-18 21:44:50,559 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:44:50,559 Training Params: | |
| 2023-10-18 21:44:50,559 - learning_rate: "5e-05" | |
| 2023-10-18 21:44:50,559 - mini_batch_size: "4" | |
| 2023-10-18 21:44:50,559 - max_epochs: "10" | |
| 2023-10-18 21:44:50,559 - shuffle: "True" | |
| 2023-10-18 21:44:50,559 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:44:50,559 Plugins: | |
| 2023-10-18 21:44:50,559 - TensorboardLogger | |
| 2023-10-18 21:44:50,559 - LinearScheduler | warmup_fraction: '0.1' | |
| 2023-10-18 21:44:50,559 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:44:50,559 Final evaluation on model from best epoch (best-model.pt) | |
| 2023-10-18 21:44:50,559 - metric: "('micro avg', 'f1-score')" | |
| 2023-10-18 21:44:50,559 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:44:50,559 Computation: | |
| 2023-10-18 21:44:50,559 - compute on device: cuda:0 | |
| 2023-10-18 21:44:50,559 - embedding storage: none | |
| 2023-10-18 21:44:50,559 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:44:50,560 Model training base path: "hmbench-icdar/fr-dbmdz/bert-tiny-historic-multilingual-cased-bs4-wsFalse-e10-lr5e-05-poolingfirst-layers-1-crfFalse-5" | |
| 2023-10-18 21:44:50,560 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:44:50,560 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:44:50,560 Logging anything other than scalars to TensorBoard is currently not supported. | |
| 2023-10-18 21:44:53,702 epoch 1 - iter 198/1984 - loss 3.02755835 - time (sec): 3.14 - samples/sec: 5433.82 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-18 21:44:56,723 epoch 1 - iter 396/1984 - loss 2.50705750 - time (sec): 6.16 - samples/sec: 5318.29 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-18 21:44:59,776 epoch 1 - iter 594/1984 - loss 1.89414489 - time (sec): 9.22 - samples/sec: 5401.23 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-18 21:45:02,860 epoch 1 - iter 792/1984 - loss 1.52591738 - time (sec): 12.30 - samples/sec: 5438.96 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-18 21:45:05,884 epoch 1 - iter 990/1984 - loss 1.32097567 - time (sec): 15.32 - samples/sec: 5430.32 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-18 21:45:08,933 epoch 1 - iter 1188/1984 - loss 1.16575852 - time (sec): 18.37 - samples/sec: 5416.07 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-18 21:45:11,986 epoch 1 - iter 1386/1984 - loss 1.04445703 - time (sec): 21.43 - samples/sec: 5421.99 - lr: 0.000035 - momentum: 0.000000 | |
| 2023-10-18 21:45:15,011 epoch 1 - iter 1584/1984 - loss 0.95783838 - time (sec): 24.45 - samples/sec: 5385.50 - lr: 0.000040 - momentum: 0.000000 | |
| 2023-10-18 21:45:18,008 epoch 1 - iter 1782/1984 - loss 0.88791048 - time (sec): 27.45 - samples/sec: 5377.95 - lr: 0.000045 - momentum: 0.000000 | |
| 2023-10-18 21:45:21,038 epoch 1 - iter 1980/1984 - loss 0.83155339 - time (sec): 30.48 - samples/sec: 5371.39 - lr: 0.000050 - momentum: 0.000000 | |
| 2023-10-18 21:45:21,095 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:45:21,095 EPOCH 1 done: loss 0.8309 - lr: 0.000050 | |
| 2023-10-18 21:45:22,631 DEV : loss 0.21765930950641632 - f1-score (micro avg) 0.3337 | |
| 2023-10-18 21:45:22,649 saving best model | |
| 2023-10-18 21:45:22,682 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:45:25,694 epoch 2 - iter 198/1984 - loss 0.31683963 - time (sec): 3.01 - samples/sec: 5386.59 - lr: 0.000049 - momentum: 0.000000 | |
| 2023-10-18 21:45:28,770 epoch 2 - iter 396/1984 - loss 0.29456292 - time (sec): 6.09 - samples/sec: 5410.37 - lr: 0.000049 - momentum: 0.000000 | |
| 2023-10-18 21:45:31,796 epoch 2 - iter 594/1984 - loss 0.28745860 - time (sec): 9.11 - samples/sec: 5414.94 - lr: 0.000048 - momentum: 0.000000 | |
| 2023-10-18 21:45:34,843 epoch 2 - iter 792/1984 - loss 0.28332924 - time (sec): 12.16 - samples/sec: 5467.12 - lr: 0.000048 - momentum: 0.000000 | |
| 2023-10-18 21:45:37,882 epoch 2 - iter 990/1984 - loss 0.27820558 - time (sec): 15.20 - samples/sec: 5452.84 - lr: 0.000047 - momentum: 0.000000 | |
| 2023-10-18 21:45:40,914 epoch 2 - iter 1188/1984 - loss 0.27692060 - time (sec): 18.23 - samples/sec: 5428.66 - lr: 0.000047 - momentum: 0.000000 | |
| 2023-10-18 21:45:43,924 epoch 2 - iter 1386/1984 - loss 0.27338747 - time (sec): 21.24 - samples/sec: 5368.92 - lr: 0.000046 - momentum: 0.000000 | |
| 2023-10-18 21:45:46,946 epoch 2 - iter 1584/1984 - loss 0.27329556 - time (sec): 24.26 - samples/sec: 5333.65 - lr: 0.000046 - momentum: 0.000000 | |
| 2023-10-18 21:45:50,005 epoch 2 - iter 1782/1984 - loss 0.26872899 - time (sec): 27.32 - samples/sec: 5362.45 - lr: 0.000045 - momentum: 0.000000 | |
| 2023-10-18 21:45:53,066 epoch 2 - iter 1980/1984 - loss 0.26392738 - time (sec): 30.38 - samples/sec: 5383.14 - lr: 0.000044 - momentum: 0.000000 | |
| 2023-10-18 21:45:53,129 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:45:53,129 EPOCH 2 done: loss 0.2637 - lr: 0.000044 | |
| 2023-10-18 21:45:54,965 DEV : loss 0.18782073259353638 - f1-score (micro avg) 0.3894 | |
| 2023-10-18 21:45:54,983 saving best model | |
| 2023-10-18 21:45:55,015 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:45:57,994 epoch 3 - iter 198/1984 - loss 0.23184493 - time (sec): 2.98 - samples/sec: 5373.79 - lr: 0.000044 - momentum: 0.000000 | |
| 2023-10-18 21:46:00,989 epoch 3 - iter 396/1984 - loss 0.22422770 - time (sec): 5.97 - samples/sec: 5368.69 - lr: 0.000043 - momentum: 0.000000 | |
| 2023-10-18 21:46:03,985 epoch 3 - iter 594/1984 - loss 0.21842906 - time (sec): 8.97 - samples/sec: 5335.00 - lr: 0.000043 - momentum: 0.000000 | |
| 2023-10-18 21:46:07,452 epoch 3 - iter 792/1984 - loss 0.22427957 - time (sec): 12.44 - samples/sec: 5161.76 - lr: 0.000042 - momentum: 0.000000 | |
| 2023-10-18 21:46:10,251 epoch 3 - iter 990/1984 - loss 0.22526202 - time (sec): 15.23 - samples/sec: 5294.55 - lr: 0.000042 - momentum: 0.000000 | |
| 2023-10-18 21:46:13,311 epoch 3 - iter 1188/1984 - loss 0.22436343 - time (sec): 18.29 - samples/sec: 5313.27 - lr: 0.000041 - momentum: 0.000000 | |
| 2023-10-18 21:46:16,377 epoch 3 - iter 1386/1984 - loss 0.22350554 - time (sec): 21.36 - samples/sec: 5321.49 - lr: 0.000041 - momentum: 0.000000 | |
| 2023-10-18 21:46:19,427 epoch 3 - iter 1584/1984 - loss 0.22239930 - time (sec): 24.41 - samples/sec: 5338.02 - lr: 0.000040 - momentum: 0.000000 | |
| 2023-10-18 21:46:22,480 epoch 3 - iter 1782/1984 - loss 0.22294790 - time (sec): 27.46 - samples/sec: 5331.42 - lr: 0.000039 - momentum: 0.000000 | |
| 2023-10-18 21:46:25,656 epoch 3 - iter 1980/1984 - loss 0.21981448 - time (sec): 30.64 - samples/sec: 5343.64 - lr: 0.000039 - momentum: 0.000000 | |
| 2023-10-18 21:46:25,714 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:46:25,714 EPOCH 3 done: loss 0.2202 - lr: 0.000039 | |
| 2023-10-18 21:46:27,536 DEV : loss 0.16426852345466614 - f1-score (micro avg) 0.4378 | |
| 2023-10-18 21:46:27,556 saving best model | |
| 2023-10-18 21:46:27,591 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:46:30,645 epoch 4 - iter 198/1984 - loss 0.21821162 - time (sec): 3.05 - samples/sec: 5334.38 - lr: 0.000038 - momentum: 0.000000 | |
| 2023-10-18 21:46:33,608 epoch 4 - iter 396/1984 - loss 0.20572668 - time (sec): 6.02 - samples/sec: 5322.24 - lr: 0.000038 - momentum: 0.000000 | |
| 2023-10-18 21:46:36,639 epoch 4 - iter 594/1984 - loss 0.20384467 - time (sec): 9.05 - samples/sec: 5369.64 - lr: 0.000037 - momentum: 0.000000 | |
| 2023-10-18 21:46:39,741 epoch 4 - iter 792/1984 - loss 0.20226613 - time (sec): 12.15 - samples/sec: 5356.48 - lr: 0.000037 - momentum: 0.000000 | |
| 2023-10-18 21:46:42,759 epoch 4 - iter 990/1984 - loss 0.20003297 - time (sec): 15.17 - samples/sec: 5402.33 - lr: 0.000036 - momentum: 0.000000 | |
| 2023-10-18 21:46:45,772 epoch 4 - iter 1188/1984 - loss 0.20039277 - time (sec): 18.18 - samples/sec: 5425.68 - lr: 0.000036 - momentum: 0.000000 | |
| 2023-10-18 21:46:48,837 epoch 4 - iter 1386/1984 - loss 0.20002361 - time (sec): 21.25 - samples/sec: 5445.13 - lr: 0.000035 - momentum: 0.000000 | |
| 2023-10-18 21:46:51,873 epoch 4 - iter 1584/1984 - loss 0.19776710 - time (sec): 24.28 - samples/sec: 5438.11 - lr: 0.000034 - momentum: 0.000000 | |
| 2023-10-18 21:46:54,901 epoch 4 - iter 1782/1984 - loss 0.19638486 - time (sec): 27.31 - samples/sec: 5423.82 - lr: 0.000034 - momentum: 0.000000 | |
| 2023-10-18 21:46:57,951 epoch 4 - iter 1980/1984 - loss 0.19597838 - time (sec): 30.36 - samples/sec: 5390.08 - lr: 0.000033 - momentum: 0.000000 | |
| 2023-10-18 21:46:58,013 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:46:58,013 EPOCH 4 done: loss 0.1958 - lr: 0.000033 | |
| 2023-10-18 21:46:59,836 DEV : loss 0.1590408831834793 - f1-score (micro avg) 0.4645 | |
| 2023-10-18 21:46:59,855 saving best model | |
| 2023-10-18 21:46:59,889 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:47:02,987 epoch 5 - iter 198/1984 - loss 0.19862903 - time (sec): 3.10 - samples/sec: 4997.21 - lr: 0.000033 - momentum: 0.000000 | |
| 2023-10-18 21:47:06,060 epoch 5 - iter 396/1984 - loss 0.19073285 - time (sec): 6.17 - samples/sec: 5095.42 - lr: 0.000032 - momentum: 0.000000 | |
| 2023-10-18 21:47:09,118 epoch 5 - iter 594/1984 - loss 0.18017645 - time (sec): 9.23 - samples/sec: 5174.83 - lr: 0.000032 - momentum: 0.000000 | |
| 2023-10-18 21:47:12,192 epoch 5 - iter 792/1984 - loss 0.18150575 - time (sec): 12.30 - samples/sec: 5182.82 - lr: 0.000031 - momentum: 0.000000 | |
| 2023-10-18 21:47:15,250 epoch 5 - iter 990/1984 - loss 0.18132472 - time (sec): 15.36 - samples/sec: 5225.93 - lr: 0.000031 - momentum: 0.000000 | |
| 2023-10-18 21:47:18,322 epoch 5 - iter 1188/1984 - loss 0.17910642 - time (sec): 18.43 - samples/sec: 5286.47 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-18 21:47:21,373 epoch 5 - iter 1386/1984 - loss 0.17861652 - time (sec): 21.48 - samples/sec: 5314.48 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-18 21:47:24,445 epoch 5 - iter 1584/1984 - loss 0.17851281 - time (sec): 24.56 - samples/sec: 5329.37 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-18 21:47:27,499 epoch 5 - iter 1782/1984 - loss 0.17681625 - time (sec): 27.61 - samples/sec: 5357.24 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-18 21:47:30,515 epoch 5 - iter 1980/1984 - loss 0.17933583 - time (sec): 30.62 - samples/sec: 5342.88 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-18 21:47:30,583 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:47:30,583 EPOCH 5 done: loss 0.1792 - lr: 0.000028 | |
| 2023-10-18 21:47:32,431 DEV : loss 0.15715673565864563 - f1-score (micro avg) 0.5065 | |
| 2023-10-18 21:47:32,449 saving best model | |
| 2023-10-18 21:47:32,487 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:47:35,526 epoch 6 - iter 198/1984 - loss 0.18455211 - time (sec): 3.04 - samples/sec: 5515.02 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-18 21:47:38,795 epoch 6 - iter 396/1984 - loss 0.18436525 - time (sec): 6.31 - samples/sec: 5325.15 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-18 21:47:41,821 epoch 6 - iter 594/1984 - loss 0.17975805 - time (sec): 9.33 - samples/sec: 5309.96 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-18 21:47:44,832 epoch 6 - iter 792/1984 - loss 0.17157674 - time (sec): 12.34 - samples/sec: 5300.16 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-18 21:47:47,848 epoch 6 - iter 990/1984 - loss 0.17078466 - time (sec): 15.36 - samples/sec: 5315.70 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-18 21:47:50,932 epoch 6 - iter 1188/1984 - loss 0.16688998 - time (sec): 18.44 - samples/sec: 5337.14 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-18 21:47:54,002 epoch 6 - iter 1386/1984 - loss 0.16587726 - time (sec): 21.51 - samples/sec: 5396.04 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-18 21:47:57,025 epoch 6 - iter 1584/1984 - loss 0.16677262 - time (sec): 24.54 - samples/sec: 5343.91 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-18 21:48:00,020 epoch 6 - iter 1782/1984 - loss 0.16683507 - time (sec): 27.53 - samples/sec: 5344.66 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-18 21:48:03,006 epoch 6 - iter 1980/1984 - loss 0.16690010 - time (sec): 30.52 - samples/sec: 5359.47 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-18 21:48:03,067 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:48:03,067 EPOCH 6 done: loss 0.1674 - lr: 0.000022 | |
| 2023-10-18 21:48:04,904 DEV : loss 0.15758880972862244 - f1-score (micro avg) 0.5325 | |
| 2023-10-18 21:48:04,922 saving best model | |
| 2023-10-18 21:48:04,961 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:48:07,977 epoch 7 - iter 198/1984 - loss 0.15459941 - time (sec): 3.02 - samples/sec: 5183.56 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-18 21:48:10,991 epoch 7 - iter 396/1984 - loss 0.16073533 - time (sec): 6.03 - samples/sec: 5469.06 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-18 21:48:14,051 epoch 7 - iter 594/1984 - loss 0.15792323 - time (sec): 9.09 - samples/sec: 5452.10 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-18 21:48:17,116 epoch 7 - iter 792/1984 - loss 0.15303565 - time (sec): 12.15 - samples/sec: 5391.67 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-18 21:48:20,201 epoch 7 - iter 990/1984 - loss 0.15501183 - time (sec): 15.24 - samples/sec: 5350.01 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-18 21:48:23,341 epoch 7 - iter 1188/1984 - loss 0.15432518 - time (sec): 18.38 - samples/sec: 5327.01 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-18 21:48:26,378 epoch 7 - iter 1386/1984 - loss 0.15354368 - time (sec): 21.42 - samples/sec: 5334.08 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-18 21:48:29,540 epoch 7 - iter 1584/1984 - loss 0.15398265 - time (sec): 24.58 - samples/sec: 5384.87 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-18 21:48:32,576 epoch 7 - iter 1782/1984 - loss 0.15459399 - time (sec): 27.61 - samples/sec: 5374.90 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-18 21:48:35,610 epoch 7 - iter 1980/1984 - loss 0.15754883 - time (sec): 30.65 - samples/sec: 5337.49 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-18 21:48:35,671 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:48:35,671 EPOCH 7 done: loss 0.1573 - lr: 0.000017 | |
| 2023-10-18 21:48:37,508 DEV : loss 0.15788982808589935 - f1-score (micro avg) 0.5569 | |
| 2023-10-18 21:48:37,527 saving best model | |
| 2023-10-18 21:48:37,561 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:48:40,596 epoch 8 - iter 198/1984 - loss 0.14924294 - time (sec): 3.03 - samples/sec: 5847.53 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-18 21:48:43,640 epoch 8 - iter 396/1984 - loss 0.14667895 - time (sec): 6.08 - samples/sec: 5664.45 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-18 21:48:46,622 epoch 8 - iter 594/1984 - loss 0.14204086 - time (sec): 9.06 - samples/sec: 5694.55 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-18 21:48:49,614 epoch 8 - iter 792/1984 - loss 0.14280278 - time (sec): 12.05 - samples/sec: 5715.33 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-18 21:48:52,626 epoch 8 - iter 990/1984 - loss 0.14084806 - time (sec): 15.06 - samples/sec: 5572.09 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-18 21:48:55,678 epoch 8 - iter 1188/1984 - loss 0.14241472 - time (sec): 18.12 - samples/sec: 5546.88 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-18 21:48:58,761 epoch 8 - iter 1386/1984 - loss 0.14358925 - time (sec): 21.20 - samples/sec: 5494.28 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-18 21:49:01,761 epoch 8 - iter 1584/1984 - loss 0.14471371 - time (sec): 24.20 - samples/sec: 5472.04 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-18 21:49:04,782 epoch 8 - iter 1782/1984 - loss 0.14729854 - time (sec): 27.22 - samples/sec: 5422.32 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-18 21:49:07,819 epoch 8 - iter 1980/1984 - loss 0.14902796 - time (sec): 30.26 - samples/sec: 5409.51 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-18 21:49:07,876 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:49:07,876 EPOCH 8 done: loss 0.1490 - lr: 0.000011 | |
| 2023-10-18 21:49:10,078 DEV : loss 0.15831266343593597 - f1-score (micro avg) 0.5582 | |
| 2023-10-18 21:49:10,097 saving best model | |
| 2023-10-18 21:49:10,130 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:49:13,217 epoch 9 - iter 198/1984 - loss 0.13787577 - time (sec): 3.09 - samples/sec: 5374.53 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-18 21:49:16,276 epoch 9 - iter 396/1984 - loss 0.14301758 - time (sec): 6.15 - samples/sec: 5466.73 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-18 21:49:19,440 epoch 9 - iter 594/1984 - loss 0.14924873 - time (sec): 9.31 - samples/sec: 5493.05 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-18 21:49:22,490 epoch 9 - iter 792/1984 - loss 0.15082222 - time (sec): 12.36 - samples/sec: 5442.31 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-18 21:49:25,512 epoch 9 - iter 990/1984 - loss 0.14676994 - time (sec): 15.38 - samples/sec: 5422.54 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-18 21:49:28,365 epoch 9 - iter 1188/1984 - loss 0.14564122 - time (sec): 18.23 - samples/sec: 5438.66 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-18 21:49:31,146 epoch 9 - iter 1386/1984 - loss 0.14469641 - time (sec): 21.02 - samples/sec: 5512.99 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-18 21:49:34,194 epoch 9 - iter 1584/1984 - loss 0.14740619 - time (sec): 24.06 - samples/sec: 5467.90 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-18 21:49:37,127 epoch 9 - iter 1782/1984 - loss 0.14524676 - time (sec): 27.00 - samples/sec: 5467.48 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-18 21:49:40,115 epoch 9 - iter 1980/1984 - loss 0.14330917 - time (sec): 29.98 - samples/sec: 5462.56 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-18 21:49:40,171 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:49:40,171 EPOCH 9 done: loss 0.1432 - lr: 0.000006 | |
| 2023-10-18 21:49:41,979 DEV : loss 0.16277986764907837 - f1-score (micro avg) 0.5731 | |
| 2023-10-18 21:49:41,998 saving best model | |
| 2023-10-18 21:49:42,031 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:49:45,068 epoch 10 - iter 198/1984 - loss 0.14623963 - time (sec): 3.04 - samples/sec: 5299.69 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-18 21:49:48,152 epoch 10 - iter 396/1984 - loss 0.13592264 - time (sec): 6.12 - samples/sec: 5369.93 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-18 21:49:51,235 epoch 10 - iter 594/1984 - loss 0.13273236 - time (sec): 9.20 - samples/sec: 5449.73 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-18 21:49:54,260 epoch 10 - iter 792/1984 - loss 0.13486998 - time (sec): 12.23 - samples/sec: 5375.78 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-18 21:49:57,283 epoch 10 - iter 990/1984 - loss 0.13630045 - time (sec): 15.25 - samples/sec: 5335.35 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-18 21:50:00,321 epoch 10 - iter 1188/1984 - loss 0.13938042 - time (sec): 18.29 - samples/sec: 5355.77 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-18 21:50:03,337 epoch 10 - iter 1386/1984 - loss 0.14082238 - time (sec): 21.30 - samples/sec: 5372.41 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-18 21:50:06,512 epoch 10 - iter 1584/1984 - loss 0.14201225 - time (sec): 24.48 - samples/sec: 5376.70 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-18 21:50:09,464 epoch 10 - iter 1782/1984 - loss 0.14275124 - time (sec): 27.43 - samples/sec: 5369.93 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-18 21:50:12,545 epoch 10 - iter 1980/1984 - loss 0.14099621 - time (sec): 30.51 - samples/sec: 5365.36 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-10-18 21:50:12,606 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:50:12,606 EPOCH 10 done: loss 0.1412 - lr: 0.000000 | |
| 2023-10-18 21:50:14,448 DEV : loss 0.1613704115152359 - f1-score (micro avg) 0.5714 | |
| 2023-10-18 21:50:14,498 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:50:14,498 Loading model from best epoch ... | |
| 2023-10-18 21:50:14,584 SequenceTagger predicts: Dictionary with 13 tags: O, S-PER, B-PER, E-PER, I-PER, S-LOC, B-LOC, E-LOC, I-LOC, S-ORG, B-ORG, E-ORG, I-ORG | |
| 2023-10-18 21:50:16,122 | |
| Results: | |
| - F-score (micro) 0.579 | |
| - F-score (macro) 0.4219 | |
| - Accuracy 0.4471 | |
| By class: | |
| precision recall f1-score support | |
| LOC 0.7049 0.7038 0.7044 655 | |
| PER 0.3574 0.5336 0.4281 223 | |
| ORG 0.2264 0.0945 0.1333 127 | |
| micro avg 0.5692 0.5891 0.5790 1005 | |
| macro avg 0.4296 0.4440 0.4219 1005 | |
| weighted avg 0.5673 0.5891 0.5709 1005 | |
| 2023-10-18 21:50:16,122 ---------------------------------------------------------------------------------------------------- | |