Writing logs to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/xlnet-base-cased-glue:cola-2020-06-29-17:32/log.txt. Loading nlp dataset glue, subset cola, split train. Loading nlp dataset glue, subset cola, split validation. Loaded dataset. Found: 2 labels: ([0, 1]) Loading transformers AutoModelForSequenceClassification: xlnet-base-cased Tokenizing training data. (len: 8551) Tokenizing eval data (len: 1043) Loaded data and tokenized in 19.534267902374268s 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 = 3e-05 Eval accuracy: 69.22339405560882% Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/xlnet-base-cased-glue:cola-2020-06-29-17:32/. Eval accuracy: 79.09875359539788% Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/xlnet-base-cased-glue:cola-2020-06-29-17:32/. Eval accuracy: 79.76989453499522% Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/xlnet-base-cased-glue:cola-2020-06-29-17:32/. Eval accuracy: 79.00287631831256% Eval accuracy: 79.00287631831256% Saved tokenizer to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/xlnet-base-cased-glue:cola-2020-06-29-17:32/. Wrote README to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/xlnet-base-cased-glue:cola-2020-06-29-17:32/README.md. Wrote training args to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/xlnet-base-cased-glue:cola-2020-06-29-17:32/train_args.json.