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