| ## TextAttack Model Card |
| This `albert-base-v2` 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 64, a learning |
| rate of 3e-05, and a maximum sequence length of 128. |
| 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 0.776173285198556, as measured by the |
| eval set accuracy, found after 4 epochs. |
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| For more information, check out [TextAttack on Github](https://github.com/QData/TextAttack). |
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