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--- |
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license: apache-2.0 |
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datasets: |
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- openai/webgpt_comparisons |
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metrics: |
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- bleu |
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library_name: flair |
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pipeline_tag: zero-shot-image-classification |
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tags: |
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- chemistry |
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- biomedical |
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- finance |
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- legal |
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- science |
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- waifu-diffusion |
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- music |
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--- |
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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 glue dataset loaded using the `nlp` library. The model was fine-tuned |
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for 5 epochs with a batch size of 32, a learning |
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rate of 2e-05, and a maximum sequence length of 128. |
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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 0.8970588235294118, as measured by the |
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eval set accuracy, found after 4 epochs. |
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For more information, check out [TextAttack on Github](https://github.com/QData/TextAttack). |
