roberta-base-RTE / log.txt
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Writing logs to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/roberta-base-glue:rte-2020-06-29-12:22/log.txt.
Loading nlp dataset glue, subset rte, split train.
Loading nlp dataset glue, subset rte, split validation.
Loaded dataset. Found: 2 labels: ([0, 1])
Loading transformers AutoModelForSequenceClassification: roberta-base
Tokenizing training data. (len: 2490)
Tokenizing eval data (len: 277)
Loaded data and tokenized in 18.287664651870728s
Training model across 1 GPUs
***** Running training *****
Num examples = 2490
Batch size = 16
Max sequence length = 128
Num steps = 775
Num epochs = 5
Learning rate = 2e-05
Eval accuracy: 59.92779783393502%
Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/roberta-base-glue:rte-2020-06-29-12:22/.
Eval accuracy: 71.48014440433214%
Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/roberta-base-glue:rte-2020-06-29-12:22/.
Eval accuracy: 75.45126353790613%
Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/roberta-base-glue:rte-2020-06-29-12:22/.
Eval accuracy: 79.42238267148014%
Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/roberta-base-glue:rte-2020-06-29-12:22/.
Eval accuracy: 78.33935018050542%
Saved tokenizer <textattack.models.tokenizers.auto_tokenizer.AutoTokenizer object at 0x7f386dbd2e80> to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/roberta-base-glue:rte-2020-06-29-12:22/.
Wrote README to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/roberta-base-glue:rte-2020-06-29-12:22/README.md.
Wrote training args to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/roberta-base-glue:rte-2020-06-29-12:22/train_args.json.