tags: | |
- adapter-transformers | |
- question-answering | |
- adapterhub:qa/squad1 | |
- roberta | |
datasets: | |
- squad | |
license: "apache-2.0" | |
# Adapter `roberta-base_qa_squad1_pfeiffer` for roberta-base | |
Adapter for roberta-base in Pfeiffer architecture trained on the SQuAD 1.1 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("roberta-base") | |
adapter_name = model.load_adapter("AdapterHub/roberta-base_qa_squad1_pfeiffer") | |
model.set_active_adapters(adapter_name) | |
``` | |
## Architecture & Training | |
- Adapter architecture: pfeiffer | |
- Prediction head: question answering | |
- Dataset: [SQuAD 1.1](https://rajpurkar.github.io/SQuAD-explorer/) | |
## 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/roberta-base_qa_squad1_pfeiffer.yaml*. |