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---
tags:
- text-classification
- adapter-transformers
- adapterhub:sts/sts-b
- bart
license: "apache-2.0"
---
# Adapter `facebook-bart-base_sts_sts-b_houlsby` for facebook/bart-base
Adapter for bart-base in Houlsby architecture trained on the STS-B dataset for 15 epochs with early stopping and a learning rate of 1e-4.
**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("facebook/bart-base")
adapter_name = model.load_adapter("AdapterHub/facebook-bart-base_sts_sts-b_houlsby")
model.set_active_adapters(adapter_name)
```
## Architecture & Training
- Adapter architecture: houlsby
- Prediction head: classification
- Dataset: [STS-B](http://ixa2.si.ehu.es/stswiki/index.php/STSbenchmark)
## Author Information
- Author name(s): Clifton Poth
- Author email: calpt@mail.de
- Author links: [Website](https://calpt.github.io), [GitHub](https://github.com/calpt), [Twitter](https://twitter.com/@clifapt)
## Citation
```bibtex
```
*This adapter has been auto-imported from https://github.com/Adapter-Hub/Hub/blob/master/adapters/ukp/facebook-bart-base_sts_sts-b_houlsby.yaml*. |