| 2022-04-03 20:45:35,951 ---------------------------------------------------------------------------------------------------- | |
| 2022-04-03 20:45:35,958 Model: "SequenceTagger( | |
| (embeddings): StackedEmbeddings( | |
| (list_embedding_0): WordEmbeddings('fa') | |
| (list_embedding_1): FlairEmbeddings( | |
| (lm): LanguageModel( | |
| (drop): Dropout(p=0.1, inplace=False) | |
| (encoder): Embedding(5105, 100) | |
| (rnn): LSTM(100, 2048) | |
| (decoder): Linear(in_features=2048, out_features=5105, bias=True) | |
| ) | |
| ) | |
| (list_embedding_2): FlairEmbeddings( | |
| (lm): LanguageModel( | |
| (drop): Dropout(p=0.1, inplace=False) | |
| (encoder): Embedding(5105, 100) | |
| (rnn): LSTM(100, 2048) | |
| (decoder): Linear(in_features=2048, out_features=5105, bias=True) | |
| ) | |
| ) | |
| ) | |
| (word_dropout): WordDropout(p=0.05) | |
| (locked_dropout): LockedDropout(p=0.5) | |
| (embedding2nn): Linear(in_features=4396, out_features=4396, bias=True) | |
| (rnn): LSTM(4396, 256, batch_first=True, bidirectional=True) | |
| (linear): Linear(in_features=512, out_features=17, bias=True) | |
| (beta): 1.0 | |
| (weights): None | |
| (weight_tensor) None | |
| )" | |
| 2022-04-03 20:45:35,962 ---------------------------------------------------------------------------------------------------- | |
| 2022-04-03 20:45:35,967 Corpus: "Corpus: 23060 train + 4070 dev + 4150 test sentences" | |
| 2022-04-03 20:45:35,971 ---------------------------------------------------------------------------------------------------- | |
| 2022-04-03 20:45:35,973 Parameters: | |
| 2022-04-03 20:45:35,975 - learning_rate: "0.05" | |
| 2022-04-03 20:45:35,977 - mini_batch_size: "4" | |
| 2022-04-03 20:45:35,980 - patience: "3" | |
| 2022-04-03 20:45:35,982 - anneal_factor: "0.5" | |
| 2022-04-03 20:45:35,985 - max_epochs: "40" | |
| 2022-04-03 20:45:35,988 - shuffle: "True" | |
| 2022-04-03 20:45:35,991 - train_with_dev: "False" | |
| 2022-04-03 20:45:35,996 - batch_growth_annealing: "False" | |
| 2022-04-03 20:45:35,998 ---------------------------------------------------------------------------------------------------- | |
| 2022-04-03 20:45:36,001 Model training base path: "/content/gdrive/MyDrive/project/data/ner/model2" | |
| 2022-04-03 20:45:36,004 ---------------------------------------------------------------------------------------------------- | |
| 2022-04-03 20:45:36,006 Device: cuda:0 | |
| 2022-04-03 20:45:36,007 ---------------------------------------------------------------------------------------------------- | |
| 2022-04-03 20:45:36,009 Embeddings storage mode: none | |
| 2022-04-03 20:45:36,559 ---------------------------------------------------------------------------------------------------- | |
| 2022-04-03 20:49:55,248 epoch 40 - iter 576/5765 - loss 0.05129424 - samples/sec: 8.91 - lr: 0.050000 | |
| 2022-04-03 20:54:12,817 epoch 40 - iter 1152/5765 - loss 0.05045109 - samples/sec: 8.98 - lr: 0.050000 | |
| 2022-04-03 20:58:35,265 epoch 40 - iter 1728/5765 - loss 0.05189116 - samples/sec: 8.81 - lr: 0.050000 | |
| 2022-04-03 21:03:11,325 epoch 40 - iter 2304/5765 - loss 0.05151945 - samples/sec: 8.38 - lr: 0.050000 | |
| 2022-04-03 21:07:46,802 epoch 40 - iter 2880/5765 - loss 0.05105861 - samples/sec: 8.40 - lr: 0.050000 | |
| 2022-04-03 21:12:16,061 epoch 40 - iter 3456/5765 - loss 0.05160696 - samples/sec: 8.59 - lr: 0.050000 | |
| 2022-04-03 21:16:46,997 epoch 40 - iter 4032/5765 - loss 0.05158343 - samples/sec: 8.54 - lr: 0.050000 | |
| 2022-04-03 21:21:12,246 epoch 40 - iter 4608/5765 - loss 0.05160290 - samples/sec: 8.72 - lr: 0.050000 | |
| 2022-04-03 21:25:34,335 epoch 40 - iter 5184/5765 - loss 0.05188003 - samples/sec: 8.83 - lr: 0.050000 | |
| 2022-04-03 21:30:00,227 epoch 40 - iter 5760/5765 - loss 0.05183257 - samples/sec: 8.70 - lr: 0.050000 | |
| 2022-04-03 21:30:03,367 ---------------------------------------------------------------------------------------------------- | |
| 2022-04-03 21:30:03,370 EPOCH 40 done: loss 0.0519 - lr 0.0500000 | |
| 2022-04-03 21:36:15,762 DEV : loss 0.05283118411898613 - f1-score (micro avg) 0.828 | |
| 2022-04-03 21:36:15,836 BAD EPOCHS (no improvement): 0 | |
| 2022-04-03 21:36:18,064 saving best model | |
| 2022-04-03 21:36:29,253 ---------------------------------------------------------------------------------------------------- | |
| 2022-04-03 21:36:29,271 loading file /content/gdrive/MyDrive/project/data/ner/model2/best-model.pt | |
| 2022-04-03 21:43:00,026 0.8616 0.82 0.8403 0.7357 | |
| 2022-04-03 21:43:00,030 | |
| Results: | |
| - F-score (micro) 0.8403 | |
| - F-score (macro) 0.8656 | |
| - Accuracy 0.7357 | |
| By class: | |
| precision recall f1-score support | |
| LOC 0.8789 0.8589 0.8688 4083 | |
| ORG 0.8390 0.7653 0.8005 3166 | |
| PER 0.8395 0.8169 0.8280 2741 | |
| DAT 0.8648 0.7957 0.8288 1150 | |
| MON 0.9758 0.9020 0.9374 357 | |
| TIM 0.8500 0.8193 0.8344 166 | |
| PCT 0.9615 0.9615 0.9615 156 | |
| micro avg 0.8616 0.8200 0.8403 11819 | |
| macro avg 0.8871 0.8456 0.8656 11819 | |
| weighted avg 0.8613 0.8200 0.8400 11819 | |
| samples avg 0.7357 0.7357 0.7357 11819 | |
| 2022-04-03 21:43:00,035 ---------------------------------------------------------------------------------------------------- | |