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JinjieNi/MixEval

⭐ 254 Python repository created 2024-06-01

MixEval provides a dynamic, ground-truth-based benchmark suite for evaluating large language models (LLMs) and large multimodal models (LMMs). It is designed to be a cost-effective and efficient alternative to traditional benchmarks like Chatbot Arena, offering high correlation with human judgment (0.96 with Chatbot Arena Elo) at significantly reduced expenses and time. The suite includes two benchmarks, MixEval and MixEval-Hard, each with free-form and multiple-choice splits, which are periodically updated to prevent data contamination. The repository provides a "click-and-go" evaluation suite that supports both open-source and proprietary models, facilitating model response generation and score computation. It allows for straightforward registration of custom models and integrates with model parsers like GPT-3.5-Turbo or open-source alternatives for robust evaluation. Users can run full evaluations (inference + scoring), inference only, or scoring only, and register new models with simple configuration. MixEval emphasizes the use of stable model parsers to address the instability of traditional rule-based parsers in evaluations.

https://github.com/JinjieNi/MixEval

LLM evaluationmultimodal model evaluationbenchmarkdynamic benchmarkLLM testingmodel evaluation suite

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