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Update log.txt

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+ Writing logs to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/roberta-base-glue:wnli-2020-06-29-11:34/log.txt.
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+ Loading nlp dataset glue, subset wnli, split train.
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+ Loading nlp dataset glue, subset wnli, split validation.
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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: 635)
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+ Tokenizing eval data (len: 71)
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+ Loaded data and tokenized in 9.126316547393799s
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+ Training model across 4 GPUs
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+ ***** Running training *****
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+ Num examples = 635
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+ Batch size = 16
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+ Max sequence length = 256
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+ Num steps = 195
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+ Num epochs = 5
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+ Learning rate = 5e-05
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+ Eval accuracy: 56.33802816901409%
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+ Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/roberta-base-glue:wnli-2020-06-29-11:34/.
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+ Eval accuracy: 54.929577464788736%
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+ Eval accuracy: 56.33802816901409%
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+ Eval accuracy: 38.028169014084504%
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+ Eval accuracy: 43.66197183098591%
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+ Saved tokenizer <textattack.models.tokenizers.auto_tokenizer.AutoTokenizer object at 0x7f372d0dd970> to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/roberta-base-glue:wnli-2020-06-29-11:34/.
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+ Wrote README to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/roberta-base-glue:wnli-2020-06-29-11:34/README.md.
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+ Wrote training args to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/roberta-base-glue:wnli-2020-06-29-11:34/train_args.json.