model = AutoAdapterModel.from_pretrained("bert-base-uncased")
config = AdapterConfig.load("pfeiffer")
model.load_adapter("sts/qqp@ukp", config=config)
Description
Adapter in Pfeiffer architecture trained on the QQP task for 20 epochs with early stopping and a learning rate of 1e-4.
See https://arxiv.org/pdf/2007.07779.pdf.
@article{pfeiffer2020AdapterHub,
title={AdapterHub: A Framework for Adapting Transformers},
author={Jonas Pfeiffer and
Andreas R\"uckl\'{e} and
Clifton Poth and
Aishwarya Kamath and
Ivan Vuli\'{c} and
Sebastian Ruder and
Kyunghyun Cho and
Iryna Gurevych},
journal={arXiv preprint},
year={2020},
url={https://arxiv.org/abs/2007.07779}
}
Architecture
@misc{pfeiffer2020adapterfusion,
title={AdapterFusion: Non-Destructive Task Composition for Transfer Learning},
author={Jonas Pfeiffer and Aishwarya Kamath and Andreas Rücklé and Kyunghyun Cho and Iryna Gurevych},
year={2020},
eprint={2005.00247},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
Task
@misc{chen2018quora,
title={Quora question pairs},
author={Chen, Zihan and Zhang, Hongbo and Zhang, Xiaoji and Zhao, Leqi},
year={2018},
publisher={Quora}
}