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log.txt

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+Writing logs to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/bert-base-uncased-glue:mrpc-2020-06-29-12:04/log.txt.
+Loading nlp dataset glue, subset mrpc, split train.
+Loading nlp dataset glue, subset mrpc, split validation.
+Loaded dataset. Found: 2 labels: ([0, 1])
+Loading transformers AutoModelForSequenceClassification: bert-base-uncased
+Tokenizing training data. (len: 3668)
+Tokenizing eval data (len: 408)
+Loaded data and tokenized in 12.476295709609985s
+Training model across 4 GPUs
+***** Running training *****
+	Num examples = 3668
+	Batch size = 16
+	Max sequence length = 256
+	Num steps = 1145
+	Num epochs = 5
+	Learning rate = 2e-05
+Eval accuracy: 84.31372549019608%
+Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/bert-base-uncased-glue:mrpc-2020-06-29-12:04/.
+Eval accuracy: 87.74509803921569%
+Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/bert-base-uncased-glue:mrpc-2020-06-29-12:04/.
+Eval accuracy: 86.02941176470588%
+Eval accuracy: 85.7843137254902%
+Eval accuracy: 85.04901960784314%
+Saved tokenizer <textattack.models.tokenizers.auto_tokenizer.AutoTokenizer object at 0x7f3a1d1a5d00> to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/bert-base-uncased-glue:mrpc-2020-06-29-12:04/.
+Wrote README to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/bert-base-uncased-glue:mrpc-2020-06-29-12:04/README.md.
+Wrote training args to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/bert-base-uncased-glue:mrpc-2020-06-29-12:04/train_args.json.