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Writing logs to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/albert-base-v2-ag_news-2020-07-01-02:15/log.txt. Loading [94mnlp[0m dataset [94mag_news[0m, split [94mtrain[0m. Loading [94mnlp[0m dataset [94mag_news[0m, split [94mtest[0m. Loaded dataset. Found: 4 labels: ([0, 1, 2, 3]) Loading transformers AutoModelForSequenceClassification: albert-base-v2 Tokenizing training data. (len: 120000) Tokenizing eval data (len: 7600) Loaded data and tokenized in 165.6598937511444s Training model across 4 GPUs ***** Running training ***** Num examples = 120000 Batch size = 16 Max sequence length = 128 Num steps = 37500 Num epochs = 5 Learning rate = 2e-05 Eval accuracy: 92.97368421052632% Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/albert-base-v2-ag_news-2020-07-01-02:15/. Eval accuracy: 94.03947368421053% Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/albert-base-v2-ag_news-2020-07-01-02:15/. Eval accuracy: 94.35526315789474% Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/albert-base-v2-ag_news-2020-07-01-02:15/. Eval accuracy: 94.71052631578948% Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/albert-base-v2-ag_news-2020-07-01-02:15/. Eval accuracy: 94.47368421052632% Saved tokenizer <textattack.models.tokenizers.auto_tokenizer.AutoTokenizer object at 0x7fe892860880> to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/albert-base-v2-ag_news-2020-07-01-02:15/. Wrote README to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/albert-base-v2-ag_news-2020-07-01-02:15/README.md. Wrote training args to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/albert-base-v2-ag_news-2020-07-01-02:15/train_args.json. |