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:rte-2020-06-29-12:22/log.txt.
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Loading [94mnlp[0m dataset [94mglue[0m, subset [94mrte[0m, split [94mtrain[0m.
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Loading [94mnlp[0m dataset [94mglue[0m, subset [94mrte[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: 2490)
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Tokenizing eval data (len: 277)
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Loaded data and tokenized in 18.287664651870728s
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Training model across 1 GPUs
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***** Running training *****
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Num examples = 2490
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Batch size = 16
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Max sequence length = 128
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Num steps = 775
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Num epochs = 5
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Learning rate = 2e-05
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Eval accuracy: 59.92779783393502%
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Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/roberta-base-glue:rte-2020-06-29-12:22/.
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Eval accuracy: 71.48014440433214%
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Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/roberta-base-glue:rte-2020-06-29-12:22/.
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Eval accuracy: 75.45126353790613%
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Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/roberta-base-glue:rte-2020-06-29-12:22/.
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Eval accuracy: 79.42238267148014%
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Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/roberta-base-glue:rte-2020-06-29-12:22/.
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Eval accuracy: 78.33935018050542%
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Saved tokenizer <textattack.models.tokenizers.auto_tokenizer.AutoTokenizer object at 0x7f386dbd2e80> to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/roberta-base-glue:rte-2020-06-29-12:22/.
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Wrote README to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/roberta-base-glue:rte-2020-06-29-12:22/README.md.
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Wrote training args to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/roberta-base-glue:rte-2020-06-29-12:22/train_args.json.
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