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2022-08-07 16:00:48,261 ---------------------------------------------------------------------------------------------------- |
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2022-08-07 16:00:48,267 Model: "SequenceTagger( |
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(embeddings): StackedEmbeddings( |
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(list_embedding_0): WordEmbeddings('fa') |
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(list_embedding_1): FlairEmbeddings( |
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(lm): LanguageModel( |
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(drop): Dropout(p=0.1, inplace=False) |
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(encoder): Embedding(5105, 100) |
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(rnn): LSTM(100, 2048) |
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(decoder): Linear(in_features=2048, out_features=5105, bias=True) |
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) |
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) |
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(list_embedding_2): FlairEmbeddings( |
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(lm): LanguageModel( |
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(drop): Dropout(p=0.1, inplace=False) |
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(encoder): Embedding(5105, 100) |
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(rnn): LSTM(100, 2048) |
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(decoder): Linear(in_features=2048, out_features=5105, bias=True) |
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) |
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) |
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) |
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(word_dropout): WordDropout(p=0.05) |
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(locked_dropout): LockedDropout(p=0.5) |
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(embedding2nn): Linear(in_features=4396, out_features=4396, bias=True) |
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(rnn): LSTM(4396, 256, batch_first=True, bidirectional=True) |
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(linear): Linear(in_features=512, out_features=32, bias=True) |
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(beta): 1.0 |
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(weights): None |
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(weight_tensor) None |
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)" |
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2022-08-07 16:00:48,272 ---------------------------------------------------------------------------------------------------- |
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2022-08-07 16:00:48,276 Corpus: "Corpus: 24000 train + 3000 dev + 3000 test sentences" |
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2022-08-07 16:00:48,281 ---------------------------------------------------------------------------------------------------- |
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2022-08-07 16:00:48,282 Parameters: |
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2022-08-07 16:00:48,285 - learning_rate: "0.1" |
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2022-08-07 16:00:48,289 - mini_batch_size: "8" |
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2022-08-07 16:00:48,293 - patience: "3" |
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2022-08-07 16:00:48,295 - anneal_factor: "0.5" |
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2022-08-07 16:00:48,296 - max_epochs: "5" |
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2022-08-07 16:00:48,297 - shuffle: "True" |
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2022-08-07 16:00:48,300 - train_with_dev: "False" |
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2022-08-07 16:00:48,301 - batch_growth_annealing: "False" |
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2022-08-07 16:00:48,303 ---------------------------------------------------------------------------------------------------- |
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2022-08-07 16:00:48,306 Model training base path: "/content/drive/MyDrive/project/data/pos/model2" |
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2022-08-07 16:00:48,309 ---------------------------------------------------------------------------------------------------- |
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2022-08-07 16:00:48,316 Device: cuda:0 |
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2022-08-07 16:00:48,317 ---------------------------------------------------------------------------------------------------- |
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2022-08-07 16:00:48,318 Embeddings storage mode: none |
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2022-08-07 16:00:48,337 ---------------------------------------------------------------------------------------------------- |
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2022-08-07 16:02:01,728 epoch 1 - iter 300/3000 - loss 0.75227154 - samples/sec: 32.71 - lr: 0.100000 |
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2022-08-07 16:03:44,240 epoch 1 - iter 600/3000 - loss 0.54616157 - samples/sec: 23.58 - lr: 0.100000 |
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2022-08-07 16:05:07,940 epoch 1 - iter 900/3000 - loss 0.46940731 - samples/sec: 28.91 - lr: 0.100000 |
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2022-08-07 16:06:48,542 epoch 1 - iter 1200/3000 - loss 0.41914715 - samples/sec: 24.03 - lr: 0.100000 |
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2022-08-07 16:08:31,313 epoch 1 - iter 1500/3000 - loss 0.38015901 - samples/sec: 23.52 - lr: 0.100000 |
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2022-08-07 16:10:05,508 epoch 1 - iter 1800/3000 - loss 0.35604709 - samples/sec: 25.67 - lr: 0.100000 |
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2022-08-07 16:11:31,898 epoch 1 - iter 2100/3000 - loss 0.33691470 - samples/sec: 28.01 - lr: 0.100000 |
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2022-08-07 16:13:00,338 epoch 1 - iter 2400/3000 - loss 0.32109903 - samples/sec: 27.35 - lr: 0.100000 |
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2022-08-07 16:14:32,548 epoch 1 - iter 2700/3000 - loss 0.31528796 - samples/sec: 26.23 - lr: 0.100000 |
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2022-08-07 16:16:09,123 epoch 1 - iter 3000/3000 - loss 0.30213703 - samples/sec: 25.03 - lr: 0.100000 |
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2022-08-07 16:16:09,831 ---------------------------------------------------------------------------------------------------- |
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2022-08-07 16:16:09,836 EPOCH 1 done: loss 0.3021 - lr 0.1000000 |
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2022-08-07 16:21:08,895 DEV : loss 0.1289350390434265 - f1-score (micro avg) 0.9601 |
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2022-08-07 16:21:08,937 BAD EPOCHS (no improvement): 0 |
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2022-08-07 16:21:10,769 saving best model |
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2022-08-07 16:21:12,532 ---------------------------------------------------------------------------------------------------- |
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2022-08-07 16:22:54,846 epoch 2 - iter 300/3000 - loss 0.21020090 - samples/sec: 23.46 - lr: 0.100000 |
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2022-08-07 16:24:33,507 epoch 2 - iter 600/3000 - loss 0.20664426 - samples/sec: 24.50 - lr: 0.100000 |
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2022-08-07 16:26:17,056 epoch 2 - iter 900/3000 - loss 0.20271364 - samples/sec: 23.33 - lr: 0.100000 |
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2022-08-07 16:27:59,228 epoch 2 - iter 1200/3000 - loss 0.20055706 - samples/sec: 23.65 - lr: 0.100000 |
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2022-08-07 16:29:39,722 epoch 2 - iter 1500/3000 - loss 0.19912427 - samples/sec: 24.05 - lr: 0.100000 |
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2022-08-07 16:31:27,754 epoch 2 - iter 1800/3000 - loss 0.19760227 - samples/sec: 22.36 - lr: 0.100000 |
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2022-08-07 16:33:12,162 epoch 2 - iter 2100/3000 - loss 0.19795635 - samples/sec: 23.14 - lr: 0.100000 |
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2022-08-07 16:34:53,586 epoch 2 - iter 2400/3000 - loss 0.19672791 - samples/sec: 23.84 - lr: 0.100000 |
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2022-08-07 16:36:42,505 epoch 2 - iter 2700/3000 - loss 0.19643492 - samples/sec: 22.19 - lr: 0.100000 |
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2022-08-07 16:38:22,496 epoch 2 - iter 3000/3000 - loss 0.19530593 - samples/sec: 24.17 - lr: 0.100000 |
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2022-08-07 16:38:23,157 ---------------------------------------------------------------------------------------------------- |
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2022-08-07 16:38:23,162 EPOCH 2 done: loss 0.1953 - lr 0.1000000 |
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2022-08-07 16:43:34,928 DEV : loss 0.10149012506008148 - f1-score (micro avg) 0.9708 |
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2022-08-07 16:43:34,973 BAD EPOCHS (no improvement): 0 |
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2022-08-07 16:43:36,767 saving best model |
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2022-08-07 16:43:38,486 ---------------------------------------------------------------------------------------------------- |
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2022-08-07 16:45:23,089 epoch 3 - iter 300/3000 - loss 0.17774341 - samples/sec: 22.95 - lr: 0.100000 |
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2022-08-07 16:47:08,214 epoch 3 - iter 600/3000 - loss 0.17596867 - samples/sec: 22.98 - lr: 0.100000 |
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2022-08-07 16:48:50,711 epoch 3 - iter 900/3000 - loss 0.17436321 - samples/sec: 23.58 - lr: 0.100000 |
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2022-08-07 16:50:35,039 epoch 3 - iter 1200/3000 - loss 0.17306311 - samples/sec: 23.16 - lr: 0.100000 |
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2022-08-07 16:52:20,808 epoch 3 - iter 1500/3000 - loss 0.17261464 - samples/sec: 22.84 - lr: 0.100000 |
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2022-08-07 16:54:02,750 epoch 3 - iter 1800/3000 - loss 0.17438407 - samples/sec: 23.71 - lr: 0.100000 |
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2022-08-07 16:55:42,154 epoch 3 - iter 2100/3000 - loss 0.17363800 - samples/sec: 24.31 - lr: 0.100000 |
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2022-08-07 16:57:21,978 epoch 3 - iter 2400/3000 - loss 0.17156485 - samples/sec: 24.21 - lr: 0.100000 |
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2022-08-07 16:59:05,968 epoch 3 - iter 2700/3000 - loss 0.17042576 - samples/sec: 23.23 - lr: 0.100000 |
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2022-08-07 17:00:46,166 epoch 3 - iter 3000/3000 - loss 0.16937353 - samples/sec: 24.12 - lr: 0.100000 |
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2022-08-07 17:00:46,857 ---------------------------------------------------------------------------------------------------- |
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2022-08-07 17:00:46,860 EPOCH 3 done: loss 0.1694 - lr 0.1000000 |
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2022-08-07 17:05:58,652 DEV : loss 0.09684865176677704 - f1-score (micro avg) 0.9731 |
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2022-08-07 17:05:58,703 BAD EPOCHS (no improvement): 0 |
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2022-08-07 17:06:00,477 saving best model |
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2022-08-07 17:06:02,321 ---------------------------------------------------------------------------------------------------- |
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2022-08-07 17:07:44,646 epoch 4 - iter 300/3000 - loss 0.16212096 - samples/sec: 23.46 - lr: 0.100000 |
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2022-08-07 17:09:25,119 epoch 4 - iter 600/3000 - loss 0.15843816 - samples/sec: 24.05 - lr: 0.100000 |
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2022-08-07 17:11:07,080 epoch 4 - iter 900/3000 - loss 0.15900626 - samples/sec: 23.70 - lr: 0.100000 |
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2022-08-07 17:12:47,149 epoch 4 - iter 1200/3000 - loss 0.15764029 - samples/sec: 24.15 - lr: 0.100000 |
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2022-08-07 17:14:33,737 epoch 4 - iter 1500/3000 - loss 0.16000098 - samples/sec: 22.66 - lr: 0.100000 |
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2022-08-07 17:16:21,024 epoch 4 - iter 1800/3000 - loss 0.15931205 - samples/sec: 22.52 - lr: 0.100000 |
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2022-08-07 17:18:01,785 epoch 4 - iter 2100/3000 - loss 0.15961928 - samples/sec: 23.99 - lr: 0.100000 |
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2022-08-07 17:19:44,524 epoch 4 - iter 2400/3000 - loss 0.15845056 - samples/sec: 23.52 - lr: 0.100000 |
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2022-08-07 17:21:27,429 epoch 4 - iter 2700/3000 - loss 0.15771950 - samples/sec: 23.49 - lr: 0.100000 |
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2022-08-07 17:23:10,018 epoch 4 - iter 3000/3000 - loss 0.15777116 - samples/sec: 23.56 - lr: 0.100000 |
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2022-08-07 17:23:10,788 ---------------------------------------------------------------------------------------------------- |
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2022-08-07 17:23:10,794 EPOCH 4 done: loss 0.1578 - lr 0.1000000 |
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2022-08-07 17:28:23,406 DEV : loss 0.09011354297399521 - f1-score (micro avg) 0.9744 |
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2022-08-07 17:28:23,451 BAD EPOCHS (no improvement): 0 |
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2022-08-07 17:28:25,515 saving best model |
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2022-08-07 17:28:27,346 ---------------------------------------------------------------------------------------------------- |
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2022-08-07 17:30:06,455 epoch 5 - iter 300/3000 - loss 0.14466099 - samples/sec: 24.22 - lr: 0.100000 |
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2022-08-07 17:31:44,351 epoch 5 - iter 600/3000 - loss 0.14401223 - samples/sec: 24.70 - lr: 0.100000 |
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2022-08-07 17:33:27,083 epoch 5 - iter 900/3000 - loss 0.14768050 - samples/sec: 23.53 - lr: 0.100000 |
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2022-08-07 17:35:07,577 epoch 5 - iter 1200/3000 - loss 0.14646819 - samples/sec: 24.05 - lr: 0.100000 |
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2022-08-07 17:36:47,275 epoch 5 - iter 1500/3000 - loss 0.14604558 - samples/sec: 24.25 - lr: 0.100000 |
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2022-08-07 17:38:24,129 epoch 5 - iter 1800/3000 - loss 0.14788483 - samples/sec: 24.96 - lr: 0.100000 |
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2022-08-07 17:40:04,518 epoch 5 - iter 2100/3000 - loss 0.14695063 - samples/sec: 24.08 - lr: 0.100000 |
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2022-08-07 17:41:51,964 epoch 5 - iter 2400/3000 - loss 0.14697433 - samples/sec: 22.49 - lr: 0.100000 |
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2022-08-07 17:43:32,173 epoch 5 - iter 2700/3000 - loss 0.14745015 - samples/sec: 24.12 - lr: 0.100000 |
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2022-08-07 17:45:17,557 epoch 5 - iter 3000/3000 - loss 0.14917362 - samples/sec: 22.93 - lr: 0.100000 |
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2022-08-07 17:45:18,255 ---------------------------------------------------------------------------------------------------- |
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2022-08-07 17:45:18,263 EPOCH 5 done: loss 0.1492 - lr 0.1000000 |
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2022-08-07 17:50:33,128 DEV : loss 0.08973350375890732 - f1-score (micro avg) 0.9746 |
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2022-08-07 17:50:33,176 BAD EPOCHS (no improvement): 0 |
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2022-08-07 17:50:34,869 saving best model |
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2022-08-07 17:50:38,774 ---------------------------------------------------------------------------------------------------- |
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2022-08-07 17:50:38,811 loading file /content/drive/MyDrive/project/data/pos/model2/best-model.pt |
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2022-08-07 17:55:05,420 0.9637 0.9637 0.9637 0.9637 |
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2022-08-07 17:55:05,422 |
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Results: |
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- F-score (micro) 0.9637 |
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- F-score (macro) 0.8989 |
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- Accuracy 0.9637 |
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By class: |
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precision recall f1-score support |
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N_SING 0.9724 0.9521 0.9621 30553 |
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P 0.9577 0.9919 0.9745 9951 |
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DELM 0.9982 0.9996 0.9989 8122 |
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ADJ 0.8768 0.9334 0.9042 7466 |
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CON 0.9905 0.9786 0.9845 6823 |
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N_PL 0.9719 0.9644 0.9681 5163 |
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V_PA 0.9753 0.9756 0.9755 2873 |
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V_PRS 0.9922 0.9852 0.9887 2841 |
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NUM 0.9907 0.9982 0.9944 2232 |
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PRO 0.9823 0.9349 0.9580 2258 |
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DET 0.9429 0.9800 0.9611 1853 |
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CLITIC 1.0000 1.0000 1.0000 1259 |
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V_PP 0.9398 0.9836 0.9612 1158 |
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V_SUB 0.9746 0.9680 0.9713 1031 |
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ADV 0.8180 0.8375 0.8276 880 |
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ADV_TIME 0.9238 0.9673 0.9451 489 |
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V_AUX 0.9947 0.9947 0.9947 379 |
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ADJ_SUP 0.9925 0.9815 0.9870 270 |
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ADJ_CMPR 0.9372 0.9275 0.9323 193 |
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ADV_NEG 0.9071 0.8523 0.8789 149 |
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ADV_I 0.8345 0.8286 0.8315 140 |
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ADJ_INO 0.8846 0.5476 0.6765 168 |
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FW 0.8442 0.5285 0.6500 123 |
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ADV_COMP 0.8072 0.8816 0.8428 76 |
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ADV_LOC 0.9342 0.9726 0.9530 73 |
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V_IMP 0.7826 0.6429 0.7059 56 |
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PREV 0.8276 0.7500 0.7869 32 |
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INT 0.8333 0.4167 0.5556 24 |
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micro avg 0.9637 0.9637 0.9637 86635 |
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macro avg 0.9245 0.8848 0.8989 86635 |
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weighted avg 0.9643 0.9637 0.9637 86635 |
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samples avg 0.9637 0.9637 0.9637 86635 |
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2022-08-07 17:55:05,427 ---------------------------------------------------------------------------------------------------- |
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