| 2023-10-13 12:00:27,065 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 12:00:27,066 Model: "SequenceTagger( | |
| (embeddings): TransformerWordEmbeddings( | |
| (model): BertModel( | |
| (embeddings): BertEmbeddings( | |
| (word_embeddings): Embedding(32001, 768) | |
| (position_embeddings): Embedding(512, 768) | |
| (token_type_embeddings): Embedding(2, 768) | |
| (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (encoder): BertEncoder( | |
| (layer): ModuleList( | |
| (0-11): 12 x BertLayer( | |
| (attention): BertAttention( | |
| (self): BertSelfAttention( | |
| (query): Linear(in_features=768, out_features=768, bias=True) | |
| (key): Linear(in_features=768, out_features=768, bias=True) | |
| (value): Linear(in_features=768, out_features=768, bias=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (output): BertSelfOutput( | |
| (dense): Linear(in_features=768, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (intermediate): BertIntermediate( | |
| (dense): Linear(in_features=768, out_features=3072, bias=True) | |
| (intermediate_act_fn): GELUActivation() | |
| ) | |
| (output): BertOutput( | |
| (dense): Linear(in_features=3072, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| ) | |
| ) | |
| (pooler): BertPooler( | |
| (dense): Linear(in_features=768, out_features=768, bias=True) | |
| (activation): Tanh() | |
| ) | |
| ) | |
| ) | |
| (locked_dropout): LockedDropout(p=0.5) | |
| (linear): Linear(in_features=768, out_features=21, bias=True) | |
| (loss_function): CrossEntropyLoss() | |
| )" | |
| 2023-10-13 12:00:27,066 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 12:00:27,066 MultiCorpus: 3575 train + 1235 dev + 1266 test sentences | |
| - NER_HIPE_2022 Corpus: 3575 train + 1235 dev + 1266 test sentences - /root/.flair/datasets/ner_hipe_2022/v2.1/hipe2020/de/with_doc_seperator | |
| 2023-10-13 12:00:27,066 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 12:00:27,066 Train: 3575 sentences | |
| 2023-10-13 12:00:27,066 (train_with_dev=False, train_with_test=False) | |
| 2023-10-13 12:00:27,066 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 12:00:27,066 Training Params: | |
| 2023-10-13 12:00:27,066 - learning_rate: "5e-05" | |
| 2023-10-13 12:00:27,066 - mini_batch_size: "4" | |
| 2023-10-13 12:00:27,066 - max_epochs: "10" | |
| 2023-10-13 12:00:27,066 - shuffle: "True" | |
| 2023-10-13 12:00:27,066 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 12:00:27,066 Plugins: | |
| 2023-10-13 12:00:27,066 - LinearScheduler | warmup_fraction: '0.1' | |
| 2023-10-13 12:00:27,066 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 12:00:27,066 Final evaluation on model from best epoch (best-model.pt) | |
| 2023-10-13 12:00:27,066 - metric: "('micro avg', 'f1-score')" | |
| 2023-10-13 12:00:27,066 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 12:00:27,066 Computation: | |
| 2023-10-13 12:00:27,067 - compute on device: cuda:0 | |
| 2023-10-13 12:00:27,067 - embedding storage: none | |
| 2023-10-13 12:00:27,067 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 12:00:27,067 Model training base path: "hmbench-hipe2020/de-dbmdz/bert-base-historic-multilingual-cased-bs4-wsFalse-e10-lr5e-05-poolingfirst-layers-1-crfFalse-1" | |
| 2023-10-13 12:00:27,067 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 12:00:27,067 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 12:00:31,356 epoch 1 - iter 89/894 - loss 2.65202089 - time (sec): 4.29 - samples/sec: 2230.44 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-13 12:00:35,325 epoch 1 - iter 178/894 - loss 1.69966045 - time (sec): 8.26 - samples/sec: 2125.46 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-13 12:00:39,217 epoch 1 - iter 267/894 - loss 1.30319450 - time (sec): 12.15 - samples/sec: 2082.04 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-13 12:00:43,289 epoch 1 - iter 356/894 - loss 1.06401462 - time (sec): 16.22 - samples/sec: 2087.13 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-13 12:00:47,424 epoch 1 - iter 445/894 - loss 0.91793285 - time (sec): 20.36 - samples/sec: 2064.05 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-13 12:00:51,643 epoch 1 - iter 534/894 - loss 0.80690184 - time (sec): 24.58 - samples/sec: 2073.01 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-13 12:00:55,771 epoch 1 - iter 623/894 - loss 0.72960178 - time (sec): 28.70 - samples/sec: 2074.20 - lr: 0.000035 - momentum: 0.000000 | |
| 2023-10-13 12:01:00,063 epoch 1 - iter 712/894 - loss 0.66121317 - time (sec): 33.00 - samples/sec: 2095.23 - lr: 0.000040 - momentum: 0.000000 | |
| 2023-10-13 12:01:04,132 epoch 1 - iter 801/894 - loss 0.61592548 - time (sec): 37.06 - samples/sec: 2080.65 - lr: 0.000045 - momentum: 0.000000 | |
| 2023-10-13 12:01:08,647 epoch 1 - iter 890/894 - loss 0.57823314 - time (sec): 41.58 - samples/sec: 2070.70 - lr: 0.000050 - momentum: 0.000000 | |
| 2023-10-13 12:01:08,863 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 12:01:08,863 EPOCH 1 done: loss 0.5761 - lr: 0.000050 | |
| 2023-10-13 12:01:14,125 DEV : loss 0.19171087443828583 - f1-score (micro avg) 0.5523 | |
| 2023-10-13 12:01:14,162 saving best model | |
| 2023-10-13 12:01:14,561 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 12:01:19,169 epoch 2 - iter 89/894 - loss 0.16742899 - time (sec): 4.61 - samples/sec: 1876.18 - lr: 0.000049 - momentum: 0.000000 | |
| 2023-10-13 12:01:24,154 epoch 2 - iter 178/894 - loss 0.18661985 - time (sec): 9.59 - samples/sec: 1799.79 - lr: 0.000049 - momentum: 0.000000 | |
| 2023-10-13 12:01:28,900 epoch 2 - iter 267/894 - loss 0.18491634 - time (sec): 14.34 - samples/sec: 1810.30 - lr: 0.000048 - momentum: 0.000000 | |
| 2023-10-13 12:01:33,617 epoch 2 - iter 356/894 - loss 0.17699142 - time (sec): 19.05 - samples/sec: 1803.39 - lr: 0.000048 - momentum: 0.000000 | |
| 2023-10-13 12:01:38,281 epoch 2 - iter 445/894 - loss 0.17304819 - time (sec): 23.72 - samples/sec: 1787.25 - lr: 0.000047 - momentum: 0.000000 | |
| 2023-10-13 12:01:43,059 epoch 2 - iter 534/894 - loss 0.16781167 - time (sec): 28.50 - samples/sec: 1795.31 - lr: 0.000047 - momentum: 0.000000 | |
| 2023-10-13 12:01:47,846 epoch 2 - iter 623/894 - loss 0.16699818 - time (sec): 33.28 - samples/sec: 1814.02 - lr: 0.000046 - momentum: 0.000000 | |
| 2023-10-13 12:01:51,935 epoch 2 - iter 712/894 - loss 0.16546982 - time (sec): 37.37 - samples/sec: 1837.50 - lr: 0.000046 - momentum: 0.000000 | |
| 2023-10-13 12:01:56,087 epoch 2 - iter 801/894 - loss 0.16583765 - time (sec): 41.52 - samples/sec: 1849.52 - lr: 0.000045 - momentum: 0.000000 | |
| 2023-10-13 12:02:00,492 epoch 2 - iter 890/894 - loss 0.16396919 - time (sec): 45.93 - samples/sec: 1877.86 - lr: 0.000044 - momentum: 0.000000 | |
| 2023-10-13 12:02:00,666 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 12:02:00,666 EPOCH 2 done: loss 0.1637 - lr: 0.000044 | |
| 2023-10-13 12:02:09,259 DEV : loss 0.1673235297203064 - f1-score (micro avg) 0.6731 | |
| 2023-10-13 12:02:09,287 saving best model | |
| 2023-10-13 12:02:09,740 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 12:02:14,071 epoch 3 - iter 89/894 - loss 0.11293528 - time (sec): 4.32 - samples/sec: 1806.55 - lr: 0.000044 - momentum: 0.000000 | |
| 2023-10-13 12:02:18,083 epoch 3 - iter 178/894 - loss 0.09808312 - time (sec): 8.34 - samples/sec: 1941.24 - lr: 0.000043 - momentum: 0.000000 | |
| 2023-10-13 12:02:22,186 epoch 3 - iter 267/894 - loss 0.10487395 - time (sec): 12.44 - samples/sec: 1958.54 - lr: 0.000043 - momentum: 0.000000 | |
| 2023-10-13 12:02:26,519 epoch 3 - iter 356/894 - loss 0.09664391 - time (sec): 16.77 - samples/sec: 1981.81 - lr: 0.000042 - momentum: 0.000000 | |
| 2023-10-13 12:02:31,084 epoch 3 - iter 445/894 - loss 0.09801920 - time (sec): 21.34 - samples/sec: 1989.82 - lr: 0.000042 - momentum: 0.000000 | |
| 2023-10-13 12:02:35,161 epoch 3 - iter 534/894 - loss 0.09498912 - time (sec): 25.41 - samples/sec: 2021.14 - lr: 0.000041 - momentum: 0.000000 | |
| 2023-10-13 12:02:39,416 epoch 3 - iter 623/894 - loss 0.09310128 - time (sec): 29.67 - samples/sec: 2021.67 - lr: 0.000041 - momentum: 0.000000 | |
| 2023-10-13 12:02:43,736 epoch 3 - iter 712/894 - loss 0.09653710 - time (sec): 33.99 - samples/sec: 2015.81 - lr: 0.000040 - momentum: 0.000000 | |
| 2023-10-13 12:02:47,930 epoch 3 - iter 801/894 - loss 0.09612514 - time (sec): 38.18 - samples/sec: 2015.52 - lr: 0.000039 - momentum: 0.000000 | |
| 2023-10-13 12:02:52,340 epoch 3 - iter 890/894 - loss 0.09660086 - time (sec): 42.59 - samples/sec: 2024.95 - lr: 0.000039 - momentum: 0.000000 | |
| 2023-10-13 12:02:52,514 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 12:02:52,514 EPOCH 3 done: loss 0.0964 - lr: 0.000039 | |
| 2023-10-13 12:03:01,037 DEV : loss 0.1543554961681366 - f1-score (micro avg) 0.7237 | |
| 2023-10-13 12:03:01,064 saving best model | |
| 2023-10-13 12:03:01,494 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 12:03:05,695 epoch 4 - iter 89/894 - loss 0.06872160 - time (sec): 4.20 - samples/sec: 2147.40 - lr: 0.000038 - momentum: 0.000000 | |
| 2023-10-13 12:03:09,945 epoch 4 - iter 178/894 - loss 0.06523083 - time (sec): 8.45 - samples/sec: 2031.05 - lr: 0.000038 - momentum: 0.000000 | |
| 2023-10-13 12:03:14,291 epoch 4 - iter 267/894 - loss 0.06233008 - time (sec): 12.80 - samples/sec: 2053.49 - lr: 0.000037 - momentum: 0.000000 | |
| 2023-10-13 12:03:18,654 epoch 4 - iter 356/894 - loss 0.06329979 - time (sec): 17.16 - samples/sec: 2106.44 - lr: 0.000037 - momentum: 0.000000 | |
| 2023-10-13 12:03:22,852 epoch 4 - iter 445/894 - loss 0.06037310 - time (sec): 21.36 - samples/sec: 2099.06 - lr: 0.000036 - momentum: 0.000000 | |
| 2023-10-13 12:03:26,947 epoch 4 - iter 534/894 - loss 0.06290240 - time (sec): 25.45 - samples/sec: 2104.17 - lr: 0.000036 - momentum: 0.000000 | |
| 2023-10-13 12:03:30,914 epoch 4 - iter 623/894 - loss 0.06194766 - time (sec): 29.42 - samples/sec: 2101.71 - lr: 0.000035 - momentum: 0.000000 | |
| 2023-10-13 12:03:35,018 epoch 4 - iter 712/894 - loss 0.06159615 - time (sec): 33.52 - samples/sec: 2095.48 - lr: 0.000034 - momentum: 0.000000 | |
| 2023-10-13 12:03:39,166 epoch 4 - iter 801/894 - loss 0.06291890 - time (sec): 37.67 - samples/sec: 2060.79 - lr: 0.000034 - momentum: 0.000000 | |
| 2023-10-13 12:03:43,303 epoch 4 - iter 890/894 - loss 0.06248239 - time (sec): 41.81 - samples/sec: 2062.20 - lr: 0.000033 - momentum: 0.000000 | |
| 2023-10-13 12:03:43,493 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 12:03:43,493 EPOCH 4 done: loss 0.0628 - lr: 0.000033 | |
| 2023-10-13 12:03:51,962 DEV : loss 0.19826681911945343 - f1-score (micro avg) 0.7608 | |
| 2023-10-13 12:03:51,990 saving best model | |
| 2023-10-13 12:03:52,464 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 12:03:57,042 epoch 5 - iter 89/894 - loss 0.05415502 - time (sec): 4.57 - samples/sec: 2124.39 - lr: 0.000033 - momentum: 0.000000 | |
| 2023-10-13 12:04:01,786 epoch 5 - iter 178/894 - loss 0.05000802 - time (sec): 9.32 - samples/sec: 1905.31 - lr: 0.000032 - momentum: 0.000000 | |
| 2023-10-13 12:04:06,621 epoch 5 - iter 267/894 - loss 0.05083210 - time (sec): 14.15 - samples/sec: 1878.52 - lr: 0.000032 - momentum: 0.000000 | |
| 2023-10-13 12:04:11,213 epoch 5 - iter 356/894 - loss 0.04975196 - time (sec): 18.75 - samples/sec: 1850.66 - lr: 0.000031 - momentum: 0.000000 | |
| 2023-10-13 12:04:15,475 epoch 5 - iter 445/894 - loss 0.04576638 - time (sec): 23.01 - samples/sec: 1900.36 - lr: 0.000031 - momentum: 0.000000 | |
| 2023-10-13 12:04:19,525 epoch 5 - iter 534/894 - loss 0.04845092 - time (sec): 27.06 - samples/sec: 1939.73 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-13 12:04:23,737 epoch 5 - iter 623/894 - loss 0.04814231 - time (sec): 31.27 - samples/sec: 1941.02 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-13 12:04:28,002 epoch 5 - iter 712/894 - loss 0.04696082 - time (sec): 35.53 - samples/sec: 1955.02 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-13 12:04:32,196 epoch 5 - iter 801/894 - loss 0.04514786 - time (sec): 39.73 - samples/sec: 1956.95 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-13 12:04:36,300 epoch 5 - iter 890/894 - loss 0.04547050 - time (sec): 43.83 - samples/sec: 1966.57 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-13 12:04:36,493 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 12:04:36,493 EPOCH 5 done: loss 0.0453 - lr: 0.000028 | |
| 2023-10-13 12:04:44,989 DEV : loss 0.2249317169189453 - f1-score (micro avg) 0.7558 | |
| 2023-10-13 12:04:45,019 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 12:04:49,517 epoch 6 - iter 89/894 - loss 0.02250297 - time (sec): 4.50 - samples/sec: 1927.38 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-13 12:04:53,620 epoch 6 - iter 178/894 - loss 0.02755065 - time (sec): 8.60 - samples/sec: 1904.80 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-13 12:04:57,991 epoch 6 - iter 267/894 - loss 0.02537520 - time (sec): 12.97 - samples/sec: 1969.77 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-13 12:05:02,077 epoch 6 - iter 356/894 - loss 0.02778131 - time (sec): 17.06 - samples/sec: 2019.16 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-13 12:05:06,083 epoch 6 - iter 445/894 - loss 0.02565103 - time (sec): 21.06 - samples/sec: 1994.56 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-13 12:05:10,138 epoch 6 - iter 534/894 - loss 0.02415612 - time (sec): 25.12 - samples/sec: 2001.89 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-13 12:05:14,184 epoch 6 - iter 623/894 - loss 0.02615286 - time (sec): 29.16 - samples/sec: 1993.85 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-13 12:05:18,598 epoch 6 - iter 712/894 - loss 0.02606805 - time (sec): 33.58 - samples/sec: 2035.76 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-13 12:05:22,821 epoch 6 - iter 801/894 - loss 0.02757777 - time (sec): 37.80 - samples/sec: 2034.05 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-13 12:05:27,484 epoch 6 - iter 890/894 - loss 0.02680885 - time (sec): 42.46 - samples/sec: 2027.87 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-13 12:05:27,693 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 12:05:27,693 EPOCH 6 done: loss 0.0267 - lr: 0.000022 | |
| 2023-10-13 12:05:36,241 DEV : loss 0.2265176773071289 - f1-score (micro avg) 0.761 | |
| 2023-10-13 12:05:36,268 saving best model | |
| 2023-10-13 12:05:36,722 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 12:05:41,169 epoch 7 - iter 89/894 - loss 0.01241443 - time (sec): 4.45 - samples/sec: 1976.84 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-13 12:05:45,326 epoch 7 - iter 178/894 - loss 0.01280006 - time (sec): 8.60 - samples/sec: 1988.62 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-13 12:05:50,011 epoch 7 - iter 267/894 - loss 0.01410320 - time (sec): 13.29 - samples/sec: 2051.18 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-13 12:05:54,218 epoch 7 - iter 356/894 - loss 0.01506068 - time (sec): 17.50 - samples/sec: 2036.46 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-13 12:05:58,380 epoch 7 - iter 445/894 - loss 0.01802183 - time (sec): 21.66 - samples/sec: 2050.15 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-13 12:06:02,559 epoch 7 - iter 534/894 - loss 0.01957567 - time (sec): 25.84 - samples/sec: 2036.06 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-13 12:06:06,819 epoch 7 - iter 623/894 - loss 0.01864068 - time (sec): 30.10 - samples/sec: 2025.40 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-13 12:06:10,824 epoch 7 - iter 712/894 - loss 0.01838519 - time (sec): 34.10 - samples/sec: 2028.91 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-13 12:06:14,873 epoch 7 - iter 801/894 - loss 0.01897641 - time (sec): 38.15 - samples/sec: 2020.45 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-13 12:06:19,125 epoch 7 - iter 890/894 - loss 0.01885509 - time (sec): 42.40 - samples/sec: 2034.65 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-13 12:06:19,303 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 12:06:19,304 EPOCH 7 done: loss 0.0188 - lr: 0.000017 | |
| 2023-10-13 12:06:27,833 DEV : loss 0.23773737251758575 - f1-score (micro avg) 0.7709 | |
| 2023-10-13 12:06:27,862 saving best model | |
| 2023-10-13 12:06:28,338 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 12:06:32,884 epoch 8 - iter 89/894 - loss 0.01758360 - time (sec): 4.54 - samples/sec: 1907.50 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-13 12:06:37,227 epoch 8 - iter 178/894 - loss 0.01300323 - time (sec): 8.89 - samples/sec: 2000.63 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-13 12:06:41,456 epoch 8 - iter 267/894 - loss 0.01026527 - time (sec): 13.12 - samples/sec: 2049.43 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-13 12:06:45,592 epoch 8 - iter 356/894 - loss 0.00865146 - time (sec): 17.25 - samples/sec: 2112.95 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-13 12:06:49,491 epoch 8 - iter 445/894 - loss 0.01113562 - time (sec): 21.15 - samples/sec: 2087.22 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-13 12:06:53,684 epoch 8 - iter 534/894 - loss 0.01103381 - time (sec): 25.34 - samples/sec: 2076.68 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-13 12:06:58,224 epoch 8 - iter 623/894 - loss 0.01078598 - time (sec): 29.88 - samples/sec: 2063.56 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-13 12:07:02,633 epoch 8 - iter 712/894 - loss 0.01053832 - time (sec): 34.29 - samples/sec: 2039.31 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-13 12:07:06,832 epoch 8 - iter 801/894 - loss 0.01089148 - time (sec): 38.49 - samples/sec: 2028.88 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-13 12:07:10,958 epoch 8 - iter 890/894 - loss 0.01109678 - time (sec): 42.62 - samples/sec: 2022.12 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-13 12:07:11,139 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 12:07:11,139 EPOCH 8 done: loss 0.0110 - lr: 0.000011 | |
| 2023-10-13 12:07:19,962 DEV : loss 0.23593451082706451 - f1-score (micro avg) 0.7892 | |
| 2023-10-13 12:07:19,992 saving best model | |
| 2023-10-13 12:07:20,478 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 12:07:24,789 epoch 9 - iter 89/894 - loss 0.00628948 - time (sec): 4.30 - samples/sec: 1921.98 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-13 12:07:29,139 epoch 9 - iter 178/894 - loss 0.00390042 - time (sec): 8.65 - samples/sec: 2031.56 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-13 12:07:33,428 epoch 9 - iter 267/894 - loss 0.00644408 - time (sec): 12.94 - samples/sec: 2000.87 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-13 12:07:37,671 epoch 9 - iter 356/894 - loss 0.00542230 - time (sec): 17.18 - samples/sec: 2057.31 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-13 12:07:41,968 epoch 9 - iter 445/894 - loss 0.00725202 - time (sec): 21.48 - samples/sec: 2057.49 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-13 12:07:46,266 epoch 9 - iter 534/894 - loss 0.00698739 - time (sec): 25.78 - samples/sec: 2073.97 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-13 12:07:50,551 epoch 9 - iter 623/894 - loss 0.00633533 - time (sec): 30.06 - samples/sec: 2062.87 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-13 12:07:54,589 epoch 9 - iter 712/894 - loss 0.00588233 - time (sec): 34.10 - samples/sec: 2053.11 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-13 12:07:58,682 epoch 9 - iter 801/894 - loss 0.00614205 - time (sec): 38.19 - samples/sec: 2047.19 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-13 12:08:03,257 epoch 9 - iter 890/894 - loss 0.00729369 - time (sec): 42.77 - samples/sec: 2013.71 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-13 12:08:03,460 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 12:08:03,461 EPOCH 9 done: loss 0.0073 - lr: 0.000006 | |
| 2023-10-13 12:08:11,860 DEV : loss 0.24528658390045166 - f1-score (micro avg) 0.7827 | |
| 2023-10-13 12:08:11,887 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 12:08:15,936 epoch 10 - iter 89/894 - loss 0.00803708 - time (sec): 4.05 - samples/sec: 2170.54 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-13 12:08:20,177 epoch 10 - iter 178/894 - loss 0.00744826 - time (sec): 8.29 - samples/sec: 2017.30 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-13 12:08:24,447 epoch 10 - iter 267/894 - loss 0.00540126 - time (sec): 12.56 - samples/sec: 2013.04 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-13 12:08:28,584 epoch 10 - iter 356/894 - loss 0.00463210 - time (sec): 16.69 - samples/sec: 2041.58 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-13 12:08:32,819 epoch 10 - iter 445/894 - loss 0.00503189 - time (sec): 20.93 - samples/sec: 2066.56 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-13 12:08:37,002 epoch 10 - iter 534/894 - loss 0.00461758 - time (sec): 25.11 - samples/sec: 2079.27 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-13 12:08:41,295 epoch 10 - iter 623/894 - loss 0.00437106 - time (sec): 29.41 - samples/sec: 2072.49 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-13 12:08:45,312 epoch 10 - iter 712/894 - loss 0.00448286 - time (sec): 33.42 - samples/sec: 2070.88 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-13 12:08:49,472 epoch 10 - iter 801/894 - loss 0.00428854 - time (sec): 37.58 - samples/sec: 2051.98 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-13 12:08:53,712 epoch 10 - iter 890/894 - loss 0.00454052 - time (sec): 41.82 - samples/sec: 2060.73 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-10-13 12:08:53,895 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 12:08:53,895 EPOCH 10 done: loss 0.0045 - lr: 0.000000 | |
| 2023-10-13 12:09:02,408 DEV : loss 0.25100380182266235 - f1-score (micro avg) 0.7943 | |
| 2023-10-13 12:09:02,436 saving best model | |
| 2023-10-13 12:09:03,246 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-13 12:09:03,247 Loading model from best epoch ... | |
| 2023-10-13 12:09:04,728 SequenceTagger predicts: Dictionary with 21 tags: O, S-loc, B-loc, E-loc, I-loc, S-pers, B-pers, E-pers, I-pers, S-org, B-org, E-org, I-org, S-prod, B-prod, E-prod, I-prod, S-time, B-time, E-time, I-time | |
| 2023-10-13 12:09:09,207 | |
| Results: | |
| - F-score (micro) 0.7421 | |
| - F-score (macro) 0.6478 | |
| - Accuracy 0.6085 | |
| By class: | |
| precision recall f1-score support | |
| loc 0.8375 0.8473 0.8424 596 | |
| pers 0.6768 0.7357 0.7050 333 | |
| org 0.5392 0.4167 0.4701 132 | |
| prod 0.5490 0.4242 0.4786 66 | |
| time 0.6964 0.7959 0.7429 49 | |
| micro avg 0.7428 0.7415 0.7421 1176 | |
| macro avg 0.6598 0.6440 0.6478 1176 | |
| weighted avg 0.7364 0.7415 0.7371 1176 | |
| 2023-10-13 12:09:09,207 ---------------------------------------------------------------------------------------------------- | |