F-Eval

F-Eval: Assessing Fundamental Abilities with Refined Evaluation Methods

F-Eval is a bilingual evaluation benchmark designed to assess fundamental abilities in AI models, including expression, commonsense reasoning, and logic. It consists of 2,211 instances in both English and Chinese, providing a comprehensive dataset for evaluation.

Key Features:

• Bilingual Dataset: Supports evaluation in both English and Chinese.
• Diverse Evaluation Metrics: Includes various dimensions such as expression, commonsense, and logic.
• Postprocessing Tools: Offers scripts for merging and normalizing results.

Benefits:

• Refined Evaluation Methods: Utilizes advanced techniques for more accurate assessments.
• Research Support: Facilitates academic research with a well-documented dataset and citation guidelines.
• Open Source: Available for public use and contribution, fostering collaboration in the AI community.

Highlights:

• Contains detailed instructions for dataset preparation, backend server setup, and evaluation execution.
• Provides statistical comparisons of evaluation methods, enhancing the understanding of model performance.