Writing logs to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/albert-base-v2-glue:rte-2020-06-29-13:42/log.txt.
Loading [94mnlp[0m dataset [94mglue[0m, subset [94mrte[0m, split [94mtrain[0m.
Loading [94mnlp[0m dataset [94mglue[0m, subset [94mrte[0m, split [94mvalidation[0m.
Loaded dataset. Found: 2 labels: ([0, 1])
Loading transformers AutoModelForSequenceClassification: albert-base-v2
Tokenizing training data. (len: 2490)
Tokenizing eval data (len: 277)
Loaded data and tokenized in 11.145107507705688s
Training model across 1 GPUs
***** Running training *****
	Num examples = 2490
	Batch size = 64
	Max sequence length = 128
	Num steps = 190
	Num epochs = 5
	Learning rate = 3e-05
Eval accuracy: 59.92779783393502%
Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/albert-base-v2-glue:rte-2020-06-29-13:42/.
Eval accuracy: 70.03610108303249%
Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/albert-base-v2-glue:rte-2020-06-29-13:42/.
Eval accuracy: 76.53429602888086%
Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/albert-base-v2-glue:rte-2020-06-29-13:42/.
Eval accuracy: 76.53429602888086%
Eval accuracy: 77.6173285198556%
Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/albert-base-v2-glue:rte-2020-06-29-13:42/.
Saved tokenizer <textattack.models.tokenizers.auto_tokenizer.AutoTokenizer object at 0x7fc7ec15ae80> to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/albert-base-v2-glue:rte-2020-06-29-13:42/.
Wrote README to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/albert-base-v2-glue:rte-2020-06-29-13:42/README.md.
Wrote training args to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/albert-base-v2-glue:rte-2020-06-29-13:42/train_args.json.