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Uncertainty-aware fine-tuning of transformers with NLI data.

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Uncertainty-Aware NLI with Stochastic Weight Averaging

This repository contains code for running the experiments reported in our paper:

Aarne Talman, Hande Celikkanat, Sami Virpioja, Markus Heinonen, Jörg Tiedemann. 2023. Uncertainty-Aware Natural Language Inference with Stochastic Weight Averaging. Proceedings of the 24th Nordic Conference on Computational Linguistics (NoDaLiDa).

How to Install and Run

Clone this repository and install the dependencies by running

git clone git@github.com:Helsinki-NLP/uncertainty-aware-nli.git
cd uncertainty-aware-nli
pip3 install -r requirements.txt

Download and prepare data by running:

./download_data.sh

See train.sh and experiment.sh for examples on how to run the code and modify those for your environment.

Paper

Please cite our work:

@inproceedings{
    talman2023uncertaintyaware,
    title={Uncertainty-Aware Natural Language Inference with Stochastic Weight Averaging},
    author={Aarne Talman and Hande Celikkanat and Sami Virpioja and Markus Heinonen and J{\"o}rg Tiedemann},
    booktitle={The 24rd Nordic Conference on Computational Linguistics},
    year={2023},
    url={https://openreview.net/forum?id=uygq9_N7TL}
}

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Uncertainty-aware fine-tuning of transformers with NLI data.

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