File size: 2,515 Bytes
3bae579 893e45c 3bae579 893e45c 3bae579 893e45c 3bae579 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 |
Writing logs to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/bert-base-uncased-yelp_polarity-2020-07-08-10:42/log.txt. Loading [94mnlp[0m dataset [94myelp_polarity[0m, split [94mtrain[0m. Loading [94mnlp[0m dataset [94myelp_polarity[0m, split [94mtest[0m. Loaded dataset. Found: 2 labels: ([0, 1]) Loading transformers AutoModelForSequenceClassification: bert-base-uncased Tokenizing training data. (len: 560000) Tokenizing eval data (len: 38000) Loaded data and tokenized in 720.6436557769775s Using torch.nn.DataParallel. Training model across 4 GPUs Wrote original training args to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/bert-base-uncased-yelp_polarity-2020-07-08-10:42/train_args.json. ***** Running training ***** Num examples = 560000 Batch size = 16 Max sequence length = 256 Num steps = 175000 Num epochs = 5 Learning rate = 5e-05 Eval accuracy: 95.95263157894736% Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/bert-base-uncased-yelp_polarity-2020-07-08-10:42/. Eval accuracy: 96.59473684210526% Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/bert-base-uncased-yelp_polarity-2020-07-08-10:42/. Eval accuracy: 96.69473684210527% Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/bert-base-uncased-yelp_polarity-2020-07-08-10:42/. Eval accuracy: 96.91052631578947% Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/bert-base-uncased-yelp_polarity-2020-07-08-10:42/. Eval accuracy: 96.99473684210527% Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/bert-base-uncased-yelp_polarity-2020-07-08-10:42/. Finished training. Re-loading and evaluating model from disk. Loading transformers AutoModelForSequenceClassification: bert-base-uncased Eval of saved model accuracy: 96.99473684210527% Saved tokenizer <textattack.models.tokenizers.auto_tokenizer.AutoTokenizer object at 0x7fcc548eb730> to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/bert-base-uncased-yelp_polarity-2020-07-08-10:42/. Wrote README to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/bert-base-uncased-yelp_polarity-2020-07-08-10:42/README.md. Wrote final training args to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/bert-base-uncased-yelp_polarity-2020-07-08-10:42/train_args.json. |