---
tags:
- adapter-transformers
- t5
datasets:
- yelp_polarity
---

# Adapter `lenglaender/xlm-roberta-base-lora-cls-yelp-polarity` for google-t5/t5-base

An [adapter](https://adapterhub.ml) for the `google-t5/t5-base` model that was trained on the [yelp_polarity](https://huggingface.co/datasets/yelp_polarity/) dataset and includes a prediction head for classification.

This adapter was created for usage with the **[Adapters](https://github.com/Adapter-Hub/adapters)** library.

## Usage

First, install `adapters`:

```
pip install -U adapters
```

Now, the adapter can be loaded and activated like this:

```python
from adapters import AutoAdapterModel

model = AutoAdapterModel.from_pretrained("google-t5/t5-base")
adapter_name = model.load_adapter("AdapterHub/xlm-roberta-base-lora-cls-yelp-polarity", source="hf", set_active=True)
```

## Architecture & Training

LoRA has r=8 and alpha=8 and was trained with dropout=0.1

## Evaluation results

Accuracy on Amazon polarity dataset: 98.15%

## Author Information
- Author name: Leon Engländer
- Author links: [GitHub](https://github.com/lenglaender), [Twitter](https://x.com/LeonEnglaender)