textattack
/

xlnet-base-cased-rotten-tomatoes

Text Generation

Transformers

PyTorch

xlnet

Inference Endpoints

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system HF staff commited on Jul 6, 2020

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c5f7f51

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1 Parent(s): 3e61560

Update log.txt

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@@ -1,26 +1,27 @@
-Writing logs to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/xlnet-base-cased-rotten_tomatoes-2020-06-28-16:10/log.txt.
 Loading [94mnlp[0m dataset [94mrotten_tomatoes[0m, split [94mtrain[0m.
 Loading [94mnlp[0m dataset [94mrotten_tomatoes[0m, split [94mvalidation[0m.
 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 25.242671012878418s
-Training model across 1 GPUs
 ***** Running training *****
 	Num examples = 8530
-	Batch size = 8
 	Max sequence length = 128
-	Num steps = 5330
 	Num epochs = 5
 	Learning rate = 2e-05
-Eval accuracy: 89.58724202626641%
-Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/xlnet-base-cased-rotten_tomatoes-2020-06-28-16:10/.
-Eval accuracy: 89.58724202626641%
-Eval accuracy: 90.33771106941839%
-Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/xlnet-base-cased-rotten_tomatoes-2020-06-28-16:10/.
-Eval accuracy: 89.8686679174484%
-Eval accuracy: 89.30581613508443%
-Saved tokenizer <textattack.models.tokenizers.auto_tokenizer.AutoTokenizer object at 0x7fe1c08b56d0> to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/xlnet-base-cased-rotten_tomatoes-2020-06-28-16:10/.
-Wrote README to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/xlnet-base-cased-rotten_tomatoes-2020-06-28-16:10/README.md.
-Wrote training args to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/xlnet-base-cased-rotten_tomatoes-2020-06-28-16:10/train_args.json.

+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 [94mnlp[0m dataset [94mrotten_tomatoes[0m, split [94mtrain[0m.
 Loading [94mnlp[0m dataset [94mrotten_tomatoes[0m, split [94mvalidation[0m.
 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.