CLEVA: Chinese Language Models EVAluation Platform

Yanyang Li; Jianqiao Zhao; Duo Zheng; Zi-Yuan Hu; Zhi Chen; Xiaohui Su; Yongfeng Huang; Shijia Huang; Dahua Lin; Michael R. Lyu; Liwei Wang

arXiv · 2308.04813

CLEVA: Chinese Language Models EVAluation Platform

Yanyang Li·Jianqiao Zhao·Duo Zheng·Zi-Yuan Hu·Zhi Chen·Xiaohui Su·Yongfeng Huang·Shijia Huang·Dahua Lin·Michael R. Lyu·Liwei Wang

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Abstract

With the continuous emergence of Chinese Large Language Models (LLMs), how to evaluate a model's capabilities has become an increasingly significant issue. The absence of a comprehensive Chinese benchmark that thoroughly assesses a model's performance, the unstandardized and incomparable prompting procedure, and the prevalent risk of contamination pose major challenges in the current evaluation of Chinese LLMs. We present CLEVA, a user-friendly platform crafted to holistically evaluate Chinese LLMs. Our platform employs a standardized workflow to assess LLMs' performance across various dimensions, regularly updating a competitive leaderboard. To alleviate contamination, CLEVA curates a significant proportion of new data and develops a sampling strategy that guarantees a unique subset for each leaderboard round. Empowered by an easy-to-use interface that requires just a few mouse clicks and a model API, users can conduct a thorough evaluation with minimal coding. Large-scale experiments featuring 23 Chinese LLMs have validated CLEVA's efficacy.

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Yanyang Li, Jianqiao Zhao, Duo Zheng, Zi-Yuan Hu, Zhi Chen, Xiaohui Su, Yongfeng Huang, Shijia Huang, Dahua Lin, Michael R. Lyu, Liwei Wang. 2023-08-09. CLEVA: Chinese Language Models EVAluation Platform. https://arxiv.org/abs/2308.04813

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