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xlnet-base-cased-MRPC

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:mrpc-2020-06-29-15:23/log.txt.
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+ Loading nlp dataset glue, subset mrpc, split train.
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+ Loading nlp dataset glue, subset mrpc, 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: 3668)
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+ Tokenizing eval data (len: 408)
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+ Loaded data and tokenized in 14.01921534538269s
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+ Training model across 4 GPUs
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+ ***** Running training *****
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+ Num examples = 3668
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+ Batch size = 32
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+ Max sequence length = 256
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+ Num steps = 570
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+ Num epochs = 5
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+ Learning rate = 5e-05
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+ Eval accuracy: 70.83333333333334%
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+ Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/xlnet-base-cased-glue:mrpc-2020-06-29-15:23/.
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+ Eval accuracy: 77.94117647058823%
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+ Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/xlnet-base-cased-glue:mrpc-2020-06-29-15:23/.
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+ Eval accuracy: 88.97058823529412%
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+ Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/xlnet-base-cased-glue:mrpc-2020-06-29-15:23/.
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+ Eval accuracy: 83.57843137254902%
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+ Eval accuracy: 86.51960784313727%
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+ Saved tokenizer <textattack.models.tokenizers.auto_tokenizer.AutoTokenizer object at 0x7fa8a817ac10> to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/xlnet-base-cased-glue:mrpc-2020-06-29-15:23/.
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+ Wrote README to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/xlnet-base-cased-glue:mrpc-2020-06-29-15:23/README.md.
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+ Wrote training args to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/xlnet-base-cased-glue:mrpc-2020-06-29-15:23/train_args.json.