Writing logs to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/albert-base-v2-glue:cola-2020-06-29-01:49/log.txt.
Loading [94mnlp[0m dataset [94mglue[0m, subset [94mcola[0m, split [94mtrain[0m.
Loading [94mnlp[0m dataset [94mglue[0m, subset [94mcola[0m, split [94mvalidation[0m.
Loaded dataset. Found: 2 labels: ([0, 1])
Loading transformers AutoModelForSequenceClassification: albert-base-v2
Tokenizing training data. (len: 8551)
Tokenizing eval data (len: 1043)
Loaded data and tokenized in 21.12540578842163s
Training model across 1 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: 75.26366251198466%
Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/albert-base-v2-glue:cola-2020-06-29-01:49/.
Eval accuracy: 80.72866730584852%
Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/albert-base-v2-glue:cola-2020-06-29-01:49/.
Eval accuracy: 82.45445829338448%
Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/albert-base-v2-glue:cola-2020-06-29-01:49/.
Eval accuracy: 81.39980824544583%
Eval accuracy: 81.01629913710451%
Saved tokenizer <textattack.models.tokenizers.auto_tokenizer.AutoTokenizer object at 0x7f52294d2ca0> to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/albert-base-v2-glue:cola-2020-06-29-01:49/.
Wrote README to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/albert-base-v2-glue:cola-2020-06-29-01:49/README.md.
Wrote training args to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/albert-base-v2-glue:cola-2020-06-29-01:49/train_args.json.