metadata
tags:
- text-classification
- adapter-transformers
- adapterhub:lingaccept/cola
- roberta
license: apache-2.0
Adapter roberta-base-cola_houlsby
for roberta-base
Adapter (with head) trained using the run_glue.py
script with an extension that retains the best checkpoint (out of 30 epochs).
This adapter was created for usage with the Adapters library.
Usage
First, install adapters
:
pip install -U adapters
Now, the adapter can be loaded and activated like this:
from adapters import AutoAdapterModel
model = AutoAdapterModel.from_pretrained("roberta-base")
adapter_name = model.load_adapter("AdapterHub/roberta-base-cola_houlsby")
model.set_active_adapters(adapter_name)
Architecture & Training
- Adapter architecture: houlsby
- Prediction head: classification
- Dataset: CoLA
Author Information
- Author name(s): Andreas Rücklé
- Author email: [email protected]
- Author links: Website, GitHub, Twitter
Citation
@article{pfeiffer2020AdapterHub,
title={AdapterHub: A Framework for Adapting Transformers},
author={Jonas Pfeiffer,
Andreas R\"uckl\'{e},
Clifton Poth,
Aishwarya Kamath,
Ivan Vuli\'{c},
Sebastian Ruder,
Kyunghyun Cho,
Iryna Gurevych},
journal={ArXiv},
year={2020}
}
This adapter has been auto-imported from https://github.com/Adapter-Hub/Hub/blob/master/adapters/ukp/roberta-base-cola_houlsby.yaml.