textattack
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albert-base-v2-SST-2

Text Classification Transformers PyTorch albert Inference Endpoints

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system HF staff commited on Jul 6, 2020

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+Writing logs to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/albert-base-v2-glue:sst2-2020-06-30-00:28/log.txt.
+Loading [94mnlp[0m dataset [94mglue[0m, subset [94msst2[0m, split [94mtrain[0m.
+Loading [94mnlp[0m dataset [94mglue[0m, subset [94msst2[0m, split [94mvalidation[0m.
+Loaded dataset. Found: 2 labels: ([0, 1])
+Loading transformers AutoModelForSequenceClassification: albert-base-v2
+Tokenizing training data. (len: 67349)
+Tokenizing eval data (len: 872)
+Loaded data and tokenized in 100.11767911911011s
+Training model across 1 GPUs
+***** Running training *****
+	Num examples = 67349
+	Batch size = 32
+	Max sequence length = 64
+	Num steps = 10520
+	Num epochs = 5
+	Learning rate = 3e-05
+Eval accuracy: 91.74311926605505%
+Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/albert-base-v2-glue:sst2-2020-06-30-00:28/.
+Eval accuracy: 91.74311926605505%
+Eval accuracy: 92.54587155963303%
+Best acc found. Saved model to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/albert-base-v2-glue:sst2-2020-06-30-00:28/.
+Eval accuracy: 91.62844036697247%
+Eval accuracy: 91.97247706422019%
+Saved tokenizer <textattack.models.tokenizers.auto_tokenizer.AutoTokenizer object at 0x7fa8880a6d60> to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/albert-base-v2-glue:sst2-2020-06-30-00:28/.
+Wrote README to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/albert-base-v2-glue:sst2-2020-06-30-00:28/README.md.
+Wrote training args to /p/qdata/jm8wx/research/text_attacks/textattack/outputs/training/albert-base-v2-glue:sst2-2020-06-30-00:28/train_args.json.