File size: 1,393 Bytes
85bb177 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 |
---
tags:
- bert
- adapter-transformers
- adapterhub:qa/squad2
- question-answering
datasets:
- squad_v2
license: "apache-2.0"
---
# Adapter `bert-base-uncased_qa_squad2_pfeiffer` for bert-base-uncased
Adapter for bert-base-uncased in Pfeiffer architecture trained on the SQuAD 2.0 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("bert-base-uncased")
adapter_name = model.load_adapter("AdapterHub/bert-base-uncased_qa_squad2_pfeiffer")
model.set_active_adapters(adapter_name)
```
## Architecture & Training
- Adapter architecture: pfeiffer
- Prediction head: question answering
- Dataset: [SQuAD 2.0](https://rajpurkar.github.io/SQuAD-explorer/)
## Author Information
- Author name(s): Clifton Poth
- Author email: [email protected]
- 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/bert-base-uncased_qa_squad2_pfeiffer.yaml*. |