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## TextAttack Model Card
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This `roberta-base` model was fine-tuned for sequence classification using TextAttack
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and the glue dataset loaded using the `nlp` library. The model was fine-tuned
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for 5 epochs with a batch size of 16, a learning
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rate of 5e-05, and a maximum sequence length of 256.
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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 0.5633802816901409, as measured by the
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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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