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Touzen/EuroEval

 
 

The robust European language model benchmark

(formerly known as ScandEval)


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Installation and usage

See the documentation for more information.

Reproducing the evaluation datasets

All datasets used in this project are generated using the scripts located in the src/scripts folder. To reproduce a dataset, run the corresponding script with the following command

uv run src/scripts/<name-of-script>.py

Replace with the specific script you wish to execute, e.g.,

uv run src/scripts/create_allocine.py

Contributors 🙏

A huge thank you to all the contributors who have helped make this project a success!

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Contribute to EuroEval

We welcome contributions to EuroEval! Whether you're fixing bugs, adding features, or contributing new datasets, your help makes this project better for everyone.

  • General contributions: Check out our contribution guidelines for information on how to get started.
  • Adding datasets: If you're interested in adding a new dataset to EuroEval, we have a dedicated guide with step-by-step instructions.

Special thanks

  • Thanks to Google for sponsoring Gemini credits as part of their Google Cloud for Researchers Program.
  • Thanks @Mikeriess for evaluating many of the larger models on the leaderboards.
  • Thanks to OpenAI for sponsoring OpenAI credits as part of their Researcher Access Program.
  • Thanks to UWV and KU Leuven for sponsoring the Azure OpenAI credits used to evaluate GPT-4-turbo in Dutch.
  • Thanks to Miðeind for sponsoring the OpenAI credits used to evaluate GPT-4-turbo in Icelandic and Faroese.
  • Thanks to CHC for sponsoring the OpenAI credits used to evaluate GPT-4-turbo in German.

Citing EuroEval

If you want to cite the framework then feel free to use this:

@article{smart2024encoder,
  title={Encoder vs Decoder: Comparative Analysis of Encoder and Decoder Language Models on Multilingual NLU Tasks},
  author={Smart, Dan Saattrup and Enevoldsen, Kenneth and Schneider-Kamp, Peter},
  journal={arXiv preprint arXiv:2406.13469},
  year={2024}
}
@inproceedings{smart2023scandeval,
  author = {Smart, Dan Saattrup},
  booktitle = {Proceedings of the 24th Nordic Conference on Computational Linguistics (NoDaLiDa)},
  month = may,
  pages = {185--201},
  title = {{ScandEval: A Benchmark for Scandinavian Natural Language Processing}},
  year = {2023}
}

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The robust European language model benchmark.

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