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A held-out collection of examples used to measure model performance after training. A good eval set reflects the real distribution the model will face, includes hard cases, and is kept separate from training data. Teams often maintain multiple eval sets for capability, safety, and regression testing.
Designing and maintaining evaluation sets is one of the highest-impact skills in AI engineering. Most production failures trace to evals that did not catch the failure mode.
A held-out collection of examples used to measure model performance after training. A good eval set reflects the real distribution the model will face, includes hard cases, and is kept separate from training data. Teams often maintain multiple eval sets for capability, safety, and regression testing.
Designing and maintaining evaluation sets is one of the highest-impact skills in AI engineering. Most production failures trace to evals that did not catch the failure mode.
Definitions are original explanations written for career development purposes. For authoritative technical definitions, refer to NIST, ISO, or the relevant standards body.
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