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bert-base-uncased_qa_squad1_pfeiffer – AI Model by AdapterHub | AlphaNeural AI

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AdapterHub/
bert-base-uncased_qa_squad1_pfeiffer

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adapter-transformers

question-answering

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Adapter `bert-base-uncased_qa_squad1_pfeiffer` for bert-base-uncased

Adapter for bert-base in Pfeiffer architecture trained on the SQuAD 1.1 dataset for 15 epochs with early stopping and a learning rate of 3e-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("bert-base-uncased")
adapter_name = model.load_adapter("AdapterHub/bert-base-uncased_qa_squad1_pfeiffer")
model.set_active_adapters(adapter_name)

Architecture & Training

Adapter architecture: pfeiffer
Prediction head: question answering
Dataset: SQuAD 1.1

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/bert-base-uncased_qa_squad1_pfeiffer.yaml.