| ## TextAttack Model Card |
| This `xlnet-base-cased` model was fine-tuned for sequence classification using TextAttack |
| and the glue dataset loaded using the `nlp` library. The model was fine-tuned |
| for 5 epochs with a batch size of 16, a learning |
| rate of 3e-05, and a maximum sequence length of 256. |
| Since this was a classification task, the model was trained with a cross-entropy loss function. |
| The best score the model achieved on this task was 0.5774647887323944, as measured by the |
| eval set accuracy, found after 0 epoch. |
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| For more information, check out [TextAttack on Github](https://github.com/QData/TextAttack). |
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