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/distilbert-base-uncased-rotten_tomatoes-2020-06-24-12:26/log.txt.
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Loading [94mnlp[0m dataset [94mrotten_tomatoes[0m, split [94mtrain[0m.
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Loading [94mnlp[0m dataset [94mrotten_tomatoes[0m, split [94mvalidation[0m.
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Filtering samples with labels outside of [0, 1, 2].
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Filtered 8530 train samples to 8530 points.
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Filtered 1066 dev samples to 1066 points.
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Loaded dataset. Found: 2 labels: ([0, 1])
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Loading transformers AutoModelForSequenceClassification: distilbert-base-uncased
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Tokenizing training data. (len: 8530)
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Tokenizing eval data (len: 1066)
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Loaded data and tokenized in 6.951146125793457s
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Training model across 4 GPUs
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***** Running training *****
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Num examples = 8530
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Batch size = 128
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Max sequence length = 128
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Num steps = 198
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Num epochs = 3
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Learning rate = 1e-05
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Eval accuracy: 81.61350844277673%
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Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/distilbert-base-uncased-rotten_tomatoes-2020-06-24-12:26/.
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Eval accuracy: 82.6454033771107%
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Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/distilbert-base-uncased-rotten_tomatoes-2020-06-24-12:26/.
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Eval accuracy: 83.95872420262664%
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Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/distilbert-base-uncased-rotten_tomatoes-2020-06-24-12:26/.
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Saved tokenizer <textattack.models.tokenizers.auto_tokenizer.AutoTokenizer object at 0x7f798097fac0> to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/distilbert-base-uncased-rotten_tomatoes-2020-06-24-12:26/.
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Wrote README to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/distilbert-base-uncased-rotten_tomatoes-2020-06-24-12:26/README.md.
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Wrote training args to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/distilbert-base-uncased-rotten_tomatoes-2020-06-24-12:26/train_args.json.
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