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+Writing logs to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/albert-base-v2-snli-2020-07-02-13:00/log.txt.
+Loading nlp dataset snli, split train.
+Loading nlp dataset snli, split validation.
+Filtering samples with labels outside of [0, 1, 2].
+Filtered 550152 train samples to 549367 points.
+Filtered 10000 dev samples to 9842 points.
+Loaded dataset. Found: 3 labels: ([0, 1, 2])
+Loading transformers AutoModelForSequenceClassification: albert-base-v2
+Tokenizing training data. (len: 549367)
+Tokenizing eval data (len: 9842)
+Loaded data and tokenized in 770.6083040237427s
+Training model across 1 GPUs
+***** Running training *****
+	Num examples = 549367
+	Batch size = 64
+	Max sequence length = 64
+	Num steps = 42915
+	Num epochs = 5
+	Learning rate = 2e-05
+Eval accuracy: 89.86994513310303%
+Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/albert-base-v2-snli-2020-07-02-13:00/.
+Eval accuracy: 89.8191424507214%
+Eval accuracy: 90.6015037593985%
+Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/albert-base-v2-snli-2020-07-02-13:00/.
+Eval accuracy: 90.27636659215607%
+Eval accuracy: 90.25604551920341%
+Saved tokenizer <textattack.models.tokenizers.auto_tokenizer.AutoTokenizer object at 0x7fd0840a5190> to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/albert-base-v2-snli-2020-07-02-13:00/.
+Wrote README to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/albert-base-v2-snli-2020-07-02-13:00/README.md.
+Wrote training args to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/albert-base-v2-snli-2020-07-02-13:00/train_args.json.