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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-imdb-2020-06-30-02:43/log.txt.
+Loading nlp dataset imdb, split train.
+Loading nlp dataset imdb, split test.
+Loaded dataset. Found: 2 labels: ([0, 1])
+Loading transformers AutoModelForSequenceClassification: bert-base-uncased
+Tokenizing training data. (len: 25000)
+Tokenizing eval data (len: 25000)
+Loaded data and tokenized in 77.80554986000061s
+Training model across 4 GPUs
+***** Running training *****
+	Num examples = 25000
+	Batch size = 16
+	Max sequence length = 128
+	Num steps = 7810
+	Num epochs = 5
+	Learning rate = 2e-05
+Eval accuracy: 88.884%
+Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/bert-base-uncased-imdb-2020-06-30-02:43/.
+Eval accuracy: 88.92%
+Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/bert-base-uncased-imdb-2020-06-30-02:43/.
+Eval accuracy: 88.716%
+Eval accuracy: 88.79599999999999%
+Eval accuracy: 89.088%
+Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/bert-base-uncased-imdb-2020-06-30-02:43/.
+Saved tokenizer <textattack.models.tokenizers.auto_tokenizer.AutoTokenizer object at 0x7f17e4b2e940> to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/bert-base-uncased-imdb-2020-06-30-02:43/.
+Wrote README to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/bert-base-uncased-imdb-2020-06-30-02:43/README.md.
+Wrote training args to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/bert-base-uncased-imdb-2020-06-30-02:43/train_args.json.