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Writing logs to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/bert-base-uncased-imdb-2020-06-30-02:43/log.txt. |
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Loading [94mnlp[0m dataset [94mimdb[0m, split [94mtrain[0m. |
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Loading [94mnlp[0m dataset [94mimdb[0m, split [94mtest[0m. |
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Loaded dataset. Found: 2 labels: ([0, 1]) |
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Loading transformers AutoModelForSequenceClassification: bert-base-uncased |
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Tokenizing training data. (len: 25000) |
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Tokenizing eval data (len: 25000) |
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Loaded data and tokenized in 77.80554986000061s |
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Training model across 4 GPUs |
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***** Running training ***** |
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Num examples = 25000 |
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Batch size = 16 |
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Max sequence length = 128 |
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Num steps = 7810 |
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Num epochs = 5 |
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Learning rate = 2e-05 |
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Eval accuracy: 88.884% |
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Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/bert-base-uncased-imdb-2020-06-30-02:43/. |
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Eval accuracy: 88.92% |
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Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/bert-base-uncased-imdb-2020-06-30-02:43/. |
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Eval accuracy: 88.716% |
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Eval accuracy: 88.79599999999999% |
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Eval accuracy: 89.088% |
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Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/bert-base-uncased-imdb-2020-06-30-02:43/. |
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Saved tokenizer <textattack.models.tokenizers.auto_tokenizer.AutoTokenizer object at 0x7f17e4b2e940> to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/bert-base-uncased-imdb-2020-06-30-02:43/. |
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Wrote README to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/bert-base-uncased-imdb-2020-06-30-02:43/README.md. |
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Wrote training args to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/bert-base-uncased-imdb-2020-06-30-02:43/train_args.json. |
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