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Update log.txt
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Writing logs to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/roberta-base-imdb-2020-06-30-17:56/log.txt.
Loading nlp dataset imdb, split train.
Loading nlp dataset imdb, split test.
Loaded dataset. Found: 2 labels: ([0, 1])
Loading transformers AutoModelForSequenceClassification: roberta-base
Tokenizing training data. (len: 25000)
Tokenizing eval data (len: 25000)
Loaded data and tokenized in 79.24297642707825s
Training model across 4 GPUs
***** Running training *****
Num examples = 25000
Batch size = 64
Max sequence length = 128
Num steps = 1950
Num epochs = 5
Learning rate = 3e-05
Eval accuracy: 90.776%
Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/roberta-base-imdb-2020-06-30-17:56/.
Eval accuracy: 91.35600000000001%
Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/roberta-base-imdb-2020-06-30-17:56/.
Eval accuracy: 91.43599999999999%
Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/roberta-base-imdb-2020-06-30-17:56/.
Eval accuracy: 91.172%
Eval accuracy: 91.408%
Saved tokenizer <textattack.models.tokenizers.auto_tokenizer.AutoTokenizer object at 0x7f1c2495c070> to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/roberta-base-imdb-2020-06-30-17:56/.
Wrote README to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/roberta-base-imdb-2020-06-30-17:56/README.md.
Wrote training args to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/roberta-base-imdb-2020-06-30-17:56/train_args.json.