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.
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