Adapter bert-base-uncased-ukpsent1_pfeiffer for bert-base-uncased

Pfeiffer Adapter trained on the UKP Sentential Argument Mining dataset.

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("bert-base-uncased")
adapter_name = model.load_adapter("AdapterHub/bert-base-uncased-ukpsent1_pfeiffer")
model.set_active_adapters(adapter_name)

Architecture & Training

• Adapter architecture: pfeiffer
• Prediction head: None
• Dataset: UKP Sentential Argument Mining

Author Information

• Author name(s): Jonas Pfeiffer
• Author email: jonas@pfeiffer.ai
• Author links: Website, GitHub, Twitter

Citation

@article{Pfeiffer2020AdapterFusion,
author = {Pfeiffer, Jonas and Kamath, Aishwarya and R{\"{u}}ckl{\'{e}}, Andreas and Cho, Kyunghyun and Gurevych, Iryna},
journal = {arXiv preprint},
title = {{AdapterFusion}:  Non-Destructive Task Composition for Transfer Learning},
 url       = {https://arxiv.org/pdf/2005.00247.pdf},
year = {2020}
}

This adapter has been auto-imported from https://github.com/Adapter-Hub/Hub/blob/master/adapters/ukp/bert-base-uncased-ukpsent1_pfeiffer.yaml.