BenCzechMark : A Czech-centric Multitask and Multimetric Benchmark for Large Language Models with Duel Scoring Mechanism

Martin Fajcik, Martin Docekal, Jan Dolezal, Karel Ondrej, Karel Beneš +13 more
12/23/2024
cs.CLcs.AI

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Abstract

We present BenCzechMark (BCM), the first comprehensive Czech language benchmark designed for large language models, offering diverse tasks, multiple task formats, and multiple evaluation metrics. Its duel scoring system is grounded in statistical significance theory and uses aggregation across tasks inspired by social preference theory. Our benchmark encompasses 50 challenging tasks, with corresponding test datasets, primarily in native Czech, with 14 newly collected ones. These tasks span 8 categories and cover diverse domains, including historical Czech news, essays from pupils or language learners, and spoken word. Furthermore, we collect and clean BUT-Large Czech Collection, the largest publicly available clean Czech language corpus, and use it for (i) contamination analysis and (ii) continuous pretraining of the first Czech-centric 7B language model with Czech-specific tokenization. We use our model as a baseline for comparison with publicly available multilingual models. Lastly, we release and maintain a leaderboard with existing 50 model submissions, where new model submissions can be made at https://huggingface.co/spaces/CZLC/BenCzechMark.

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@article{fajcik2024benczechmark,
  title  = {BenCzechMark : A Czech-centric Multitask and Multimetric Benchmark for Large Language Models with Duel Scoring Mechanism},
  author = {Martin Fajcik and Martin Docekal and Jan Dolezal and Karel Ondrej and Karel Beneš and Jan Kapsa and Pavel Smrz and Alexander Polok and Michal Hradis and Zuzana Neverilova and Ales Horak and Radoslav Sabol and Michal Stefanik and Adam Jirkovsky and David Adamczyk and Petr Hyner and Jan Hula and Hynek Kydlicek},
  year   = {2024},
  eprint = {2412.17933},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2412.17933v2}
}

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