FLAME: Financial Large-Language Model Assessment and Metrics Evaluation

• URL: http://arxiv.org/abs/2501.06211v1
• Date: Fri, 03 Jan 2025 09:17:23 GMT
• Title: FLAME: Financial Large-Language Model Assessment and Metrics Evaluation
• Authors: Jiayu Guo, Yu Guo, Martha Li, Songtao Tan,
• Abstract summary: We introduce FLAME, a comprehensive financial LLMs evaluation system in Chinese. FLAME-Cer covers 14 types of authoritative financial certifications, with a total of approximately 16,000 carefully selected questions. FLAME-Sce consists of 10 primary core financial business scenarios, 21 secondary financial business scenarios, and a comprehensive evaluation set of nearly 100 tertiary financial application tasks.
• Score: 2.6420673380196824
• License:
• Abstract: LLMs have revolutionized NLP and demonstrated potential across diverse domains. More and more financial LLMs have been introduced for finance-specific tasks, yet comprehensively assessing their value is still challenging. In this paper, we introduce FLAME, a comprehensive financial LLMs evaluation system in Chinese, which includes two core evaluation benchmarks: FLAME-Cer and FLAME-Sce. FLAME-Cer covers 14 types of authoritative financial certifications, including CPA, CFA, and FRM, with a total of approximately 16,000 carefully selected questions. All questions have been manually reviewed to ensure accuracy and representativeness. FLAME-Sce consists of 10 primary core financial business scenarios, 21 secondary financial business scenarios, and a comprehensive evaluation set of nearly 100 tertiary financial application tasks. We evaluate 6 representative LLMs, including GPT-4o, GLM-4, ERNIE-4.0, Qwen2.5, XuanYuan3, and the latest Baichuan4-Finance, revealing Baichuan4-Finance excels other LLMs in most tasks. By establishing a comprehensive and professional evaluation system, FLAME facilitates the advancement of financial LLMs in Chinese contexts. Instructions for participating in the evaluation are available on GitHub: https://github.com/FLAME-ruc/FLAME.

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