What is an Evaluation Harness?
A software framework that systematically runs tests and benchmarks to assess AI model performance across multiple tasks and metrics.
Definition
An Evaluation Harness is a comprehensive software framework designed to systematically execute tests, benchmarks, and evaluations on AI models, providing standardized assessment across multiple tasks, datasets, and performance metrics.
Purpose
Evaluation harnesses enable consistent, reproducible, and comprehensive testing of AI models, making it easier to compare different models, track progress over time, and identify strengths and weaknesses.
Function
Evaluation harnesses work by automating the process of running models against various benchmarks, collecting results, computing metrics, and generating reports that provide detailed insights into model capabilities and performance.
Example
EleutherAI's Language Model Evaluation Harness allows researchers to test language models against dozens of standardized benchmarks like MMLU, HellaSwag, and ARC, producing comparable results across different models and research groups.
Related
Connected to Model Testing, Benchmarking, Performance Metrics, Research Infrastructure, and Standardized Evaluation protocols.
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