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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-rotten_tomatoes-2020-06-25-01:28/log.txt.
+Loading nlp dataset rotten_tomatoes, split train.
+Loading nlp dataset rotten_tomatoes, split validation.
+Loaded dataset. Found: 2 labels: ([0, 1])
+Loading transformers AutoModelForSequenceClassification: bert-base-uncased
+Tokenizing training data. (len: 8530)
+Tokenizing eval data (len: 1066)
+Loaded data and tokenized in 8.81861162185669s
+Training model across 4 GPUs
+***** Running training *****
+	Num examples = 8530
+	Batch size = 16
+	Max sequence length = 128
+	Num steps = 5330
+	Num epochs = 10
+	Learning rate = 2e-05
+Eval accuracy: 85.27204502814259%
+Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/bert-base-uncased-rotten_tomatoes-2020-06-25-01:28/.
+Eval accuracy: 85.74108818011257%
+Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/bert-base-uncased-rotten_tomatoes-2020-06-25-01:28/.
+Eval accuracy: 85.45966228893059%
+Eval accuracy: 85.27204502814259%
+Eval accuracy: 87.5234521575985%
+Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/bert-base-uncased-rotten_tomatoes-2020-06-25-01:28/.
+Eval accuracy: 85.92870544090057%
+Eval accuracy: 86.21013133208255%
+Eval accuracy: 86.11632270168855%
+Eval accuracy: 86.96060037523452%
+Eval accuracy: 86.86679174484053%
+Saved tokenizer <textattack.models.tokenizers.auto_tokenizer.AutoTokenizer object at 0x7f23bb2efeb0> to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/bert-base-uncased-rotten_tomatoes-2020-06-25-01:28/.
+Wrote README to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/bert-base-uncased-rotten_tomatoes-2020-06-25-01:28/README.md.
+Wrote training args to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/bert-base-uncased-rotten_tomatoes-2020-06-25-01:28/train_args.json.