Evaluation Harness
A standardized testing framework for running AI models through suites of benchmarks and evaluation tasks. It ensures consistent, reproducible evaluation across models.
Why It Matters
Evaluation harnesses enable apples-to-apples model comparisons. Without standardized evaluation, every claim about model performance is suspect.
Example
EleutherAI's lm-evaluation-harness running a model through MMLU, HellaSwag, ARC, and 50 other benchmarks with consistent prompting and scoring methodology.
Think of it like...
Like standardized testing in education — SAT, GRE, MCAT all use consistent formats and conditions so scores are comparable across test-takers.
Related Terms
Benchmark
A standardized test or dataset used to evaluate and compare the performance of AI models. Benchmarks provide consistent metrics that allow fair comparisons between different approaches.
Evaluation
The systematic process of measuring an AI model's performance, safety, and reliability using various metrics, benchmarks, and testing methodologies.
Evaluation Framework
A structured system for measuring AI model performance across multiple dimensions including accuracy, safety, fairness, robustness, and user satisfaction.