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-glue:cola-2020-06-29-14:54/log.txt.
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Loading [94mnlp[0m dataset [94mglue[0m, subset [94mcola[0m, split [94mtrain[0m.
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Loading [94mnlp[0m dataset [94mglue[0m, subset [94mcola[0m, split [94mvalidation[0m.
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Loaded dataset. Found: 2 labels: ([0, 1])
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Loading transformers AutoModelForSequenceClassification: roberta-base
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Tokenizing training data. (len: 8551)
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Tokenizing eval data (len: 1043)
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Loaded data and tokenized in 20.26492166519165s
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Training model across 4 GPUs
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***** Running training *****
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Num examples = 8551
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Batch size = 32
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Max sequence length = 128
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Num steps = 1335
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Num epochs = 5
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Learning rate = 2e-05
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Eval accuracy: 81.87919463087249%
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Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/roberta-base-glue:cola-2020-06-29-14:54/.
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Eval accuracy: 85.0431447746884%
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Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/roberta-base-glue:cola-2020-06-29-14:54/.
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Eval accuracy: 84.18024928092042%
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Eval accuracy: 84.0843720038351%
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Eval accuracy: 84.75551294343241%
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Saved tokenizer <textattack.models.tokenizers.auto_tokenizer.AutoTokenizer object at 0x7f94dc097dc0> to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/roberta-base-glue:cola-2020-06-29-14:54/.
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Wrote README to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/roberta-base-glue:cola-2020-06-29-14:54/README.md.
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Wrote training args to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/roberta-base-glue:cola-2020-06-29-14:54/train_args.json.
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