Adapter facebook-bart-base_sentiment_sst-2_pfeiffer for facebook/bart-base

Adapter for bart-base in Pfeiffer architecture trained on the SST-2 dataset for 15 epochs with early stopping and a learning rate of 1e-4.

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("facebook/bart-base")
adapter_name = model.load_adapter("AdapterHub/facebook-bart-base_sentiment_sst-2_pfeiffer")
model.set_active_adapters(adapter_name)

Architecture & Training

• Adapter architecture: pfeiffer
• Prediction head: classification
• Dataset: SST-2

Author Information

• Author name(s): Clifton Poth
• Author email: calpt@mail.de
• Author links: Website, GitHub, Twitter

Citation

This adapter has been auto-imported from https://github.com/Adapter-Hub/Hub/blob/master/adapters/ukp/facebook-bart-base_sentiment_sst-2_pfeiffer.yaml.