Reliable, Reproducible, and Really Fast Leaderboards with Evalica

Dmitry Ustalov

Reliable, Reproducible, and Really Fast Leaderboards with Evalica: 2 upvotes on Hugging Face Daily Papers, #24 of 28 papers on 2024-12-17. Day-by-day upvote history.

The rapid advancement of natural language processing (NLP) technologies, such as instruction-tuned large language models (LLMs), urges the development of modern evaluation protocols with human and machine feedback. We introduce Evalica, an open-source toolkit that facilitates the creation of reliable and reproducible model leaderboards. This paper presents its design, evaluates its performance, and demonstrates its usability through its Web interface, command-line interface, and Python API.

Paper page on Hugging Face · arXiv

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