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textattack
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xlnet-base-cased-CoLA

Text Generation Transformers PyTorch xlnet Inference Endpoints
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+ Writing logs to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/xlnet-base-cased-glue:cola-2020-06-29-17:32/log.txt.
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+ Loading nlp dataset glue, subset cola, split train.
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+ Loading nlp dataset glue, subset cola, split validation.
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+ Loaded dataset. Found: 2 labels: ([0, 1])
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+ Loading transformers AutoModelForSequenceClassification: xlnet-base-cased
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+ Tokenizing training data. (len: 8551)
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+ Tokenizing eval data (len: 1043)
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+ Loaded data and tokenized in 19.534267902374268s
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+ Training model across 4 GPUs
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+ ***** Running training *****
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+ Num examples = 8551
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+ Batch size = 32
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+ Max sequence length = 128
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+ Num steps = 1335
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+ Num epochs = 5
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+ Learning rate = 3e-05
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+ Eval accuracy: 69.22339405560882%
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+ Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/xlnet-base-cased-glue:cola-2020-06-29-17:32/.
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+ Eval accuracy: 79.09875359539788%
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+ Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/xlnet-base-cased-glue:cola-2020-06-29-17:32/.
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+ Eval accuracy: 79.76989453499522%
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+ Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/xlnet-base-cased-glue:cola-2020-06-29-17:32/.
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+ Eval accuracy: 79.00287631831256%
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+ Eval accuracy: 79.00287631831256%
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+ Saved tokenizer <textattack.models.tokenizers.auto_tokenizer.AutoTokenizer object at 0x7f15171eebb0> to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/xlnet-base-cased-glue:cola-2020-06-29-17:32/.
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+ Wrote README to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/xlnet-base-cased-glue:cola-2020-06-29-17:32/README.md.
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+ Wrote training args to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/xlnet-base-cased-glue:cola-2020-06-29-17:32/train_args.json.