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facebook-bart-base_nli_rte_pfeiffer – AI Model by AdapterHub | AlphaNeural AI

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AdapterHub/
facebook-bart-base_nli_rte_pfeiffer

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adapter-transformers

text-classification

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Adapter `facebook-bart-base_nli_rte_pfeiffer` for facebook/bart-base

Adapter for bart-base in Pfeiffer architecture trained on the RTE 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:

python

from adapters import AutoAdapterModel

model = AutoAdapterModel.from_pretrained("facebook/bart-base")
adapter_name = model.load_adapter("AdapterHub/facebook-bart-base_nli_rte_pfeiffer")
model.set_active_adapters(adapter_name)

Architecture & Training

Adapter architecture: pfeiffer
Prediction head: classification
Dataset: RTE

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_nli_rte_pfeiffer.yaml.