system's picture
system HF staff
Update log.txt
c5f7f51
Writing logs to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/xlnet-base-cased-rotten_tomatoes-2020-06-29-05:32/log.txt.
Loading nlp dataset rotten_tomatoes, split train.
Loading nlp dataset rotten_tomatoes, split validation.
Loaded dataset. Found: 2 labels: ([0, 1])
Loading transformers AutoModelForSequenceClassification: xlnet-base-cased
Tokenizing training data. (len: 8530)
Tokenizing eval data (len: 1066)
Loaded data and tokenized in 19.84232258796692s
Training model across 4 GPUs
***** Running training *****
Num examples = 8530
Batch size = 16
Max sequence length = 128
Num steps = 2665
Num epochs = 5
Learning rate = 2e-05
Eval accuracy: 88.83677298311444%
Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/xlnet-base-cased-rotten_tomatoes-2020-06-29-05:32/.
Eval accuracy: 89.21200750469043%
Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/xlnet-base-cased-rotten_tomatoes-2020-06-29-05:32/.
Eval accuracy: 90.71294559099438%
Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/xlnet-base-cased-rotten_tomatoes-2020-06-29-05:32/.
Eval accuracy: 89.6810506566604%
Eval accuracy: 89.6810506566604%
Saved tokenizer <textattack.models.tokenizers.auto_tokenizer.AutoTokenizer object at 0x7fc1083fcb50> to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/xlnet-base-cased-rotten_tomatoes-2020-06-29-05:32/.
Wrote README to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/xlnet-base-cased-rotten_tomatoes-2020-06-29-05:32/README.md.
Wrote training args to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/xlnet-base-cased-rotten_tomatoes-2020-06-29-05:32/train_args.json.