Update log.txt
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log.txt
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Writing logs to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/roberta-base-ag_news-2020-07-03-13:06/log.txt.
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Loading [94mnlp[0m dataset [94mag_news[0m, split [94mtrain[0m.
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Loading [94mnlp[0m dataset [94mag_news[0m, split [94mtest[0m.
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Loaded dataset. Found: 4 labels: ([0, 1, 2, 3])
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Loading transformers AutoModelForSequenceClassification: roberta-base
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Tokenizing training data. (len: 120000)
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Tokenizing eval data (len: 7600)
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Loaded data and tokenized in 147.60910987854004s
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Training model across 4 GPUs
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***** Running training *****
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Num examples = 120000
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Batch size = 16
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Max sequence length = 128
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Num steps = 37500
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Num epochs = 5
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Learning rate = 5e-05
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Eval accuracy: 93.71052631578948%
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Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/roberta-base-ag_news-2020-07-03-13:06/.
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Eval accuracy: 93.6842105263158%
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Eval accuracy: 94.61842105263158%
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Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/roberta-base-ag_news-2020-07-03-13:06/.
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Eval accuracy: 94.5921052631579%
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Eval accuracy: 94.69736842105263%
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Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/roberta-base-ag_news-2020-07-03-13:06/.
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Saved tokenizer <textattack.models.tokenizers.auto_tokenizer.AutoTokenizer object at 0x7fcac6e3aee0> to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/roberta-base-ag_news-2020-07-03-13:06/.
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Wrote README to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/roberta-base-ag_news-2020-07-03-13:06/README.md.
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Wrote training args to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/roberta-base-ag_news-2020-07-03-13:06/train_args.json.
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