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Evaluate & Evaluation on the Hub: Better Best Practices for Data and Model Measurements. (arXiv:2210.01970v2 [cs.LG] UPDATED)
Oct. 7, 2022, 1:13 a.m. | Leandro von Werra, Lewis Tunstall, Abhishek Thakur, Alexandra Sasha Luccioni, Tristan Thrush, Aleksandra Piktus, Felix Marty, Nazneen Rajani, Victor M
cs.LG updates on arXiv.org arxiv.org
Evaluation is a key part of machine learning (ML), yet there is a lack of
support and tooling to enable its informed and systematic practice. We
introduce Evaluate and Evaluation on the Hub --a set of tools to facilitate the
evaluation of models and datasets in ML. Evaluate is a library to support best
practices for measurements, metrics, and comparisons of data and models. Its
goal is to support reproducibility of evaluation, centralize and document the
evaluation process, and broaden …
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