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--- |
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tags: |
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- adapter-transformers |
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- t5 |
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datasets: |
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- amazon_polarity |
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--- |
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# Adapter `lenglaender/xlm-roberta-base-lora-cls-amazon-polarity` for google-t5/t5-base |
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An [adapter](https://adapterhub.ml) for the `google-t5/t5-base` model that was trained on the [amazon_polarity](https://huggingface.co/datasets/amazon_polarity/) dataset and includes a prediction head for classification. |
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This adapter was created for usage with the **[Adapters](https://github.com/Adapter-Hub/adapters)** library. |
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## Usage |
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First, install `adapters`: |
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``` |
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pip install -U adapters |
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``` |
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Now, the adapter can be loaded and activated like this: |
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```python |
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from adapters import AutoAdapterModel |
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model = AutoAdapterModel.from_pretrained("google-t5/t5-base") |
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adapter_name = model.load_adapter("AdapterHub/xlm-roberta-base-lora-cls-amazon-polarity", source="hf", set_active=True) |
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``` |
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## Architecture & Training |
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LoRA has r=8 and alpha=8 and was trained with dropout=0.1 |
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## Evaluation results |
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Accuracy on Amazon polarity dataset: 95.91% |
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## Author Information |
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- Author name: Leon Engländer |
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- Author links: [GitHub](https://github.com/lenglaender), [Twitter](https://x.com/LeonEnglaender) |
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