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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. |