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log.txt

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+Writing logs to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/xlnet-base-cased-rotten_tomatoes-2020-06-28-16:10/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: xlnet-base-cased
+Tokenizing training data. (len: 8530)
+Tokenizing eval data (len: 1066)
+Loaded data and tokenized in 25.242671012878418s
+Training model across 1 GPUs
+***** Running training *****
+	Num examples = 8530
+	Batch size = 8
+	Max sequence length = 128
+	Num steps = 5330
+	Num epochs = 5
+	Learning rate = 2e-05
+Eval accuracy: 89.58724202626641%
+Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/xlnet-base-cased-rotten_tomatoes-2020-06-28-16:10/.
+Eval accuracy: 89.58724202626641%
+Eval accuracy: 90.33771106941839%
+Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/xlnet-base-cased-rotten_tomatoes-2020-06-28-16:10/.
+Eval accuracy: 89.8686679174484%
+Eval accuracy: 89.30581613508443%
+Saved tokenizer <textattack.models.tokenizers.auto_tokenizer.AutoTokenizer object at 0x7fe1c08b56d0> to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/xlnet-base-cased-rotten_tomatoes-2020-06-28-16:10/.
+Wrote README to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/xlnet-base-cased-rotten_tomatoes-2020-06-28-16:10/README.md.
+Wrote training args to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/xlnet-base-cased-rotten_tomatoes-2020-06-28-16:10/train_args.json.