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## TextAttack Model Card |
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This `albert-base-v2` model was fine-tuned for sequence classification using TextAttack |
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and the snli dataset loaded using the `nlp` library. The model was fine-tuned |
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for 5 epochs with a batch size of 64, a learning |
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rate of 2e-05, and a maximum sequence length of 64. |
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Since this was a classification task, the model was trained with a cross-entropy loss function. |
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The best score the model achieved on this task was 0.9060150375939849, as measured by the |
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eval set accuracy, found after 2 epochs. |
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For more information, check out [TextAttack on Github](https://github.com/QData/TextAttack). |
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