Evals
Evals is an open-source framework developed by OpenAI for evaluating and benchmarking large language models (LLMs) and AI systems. It provides a standardized way to create, run, and analyze evaluation datasets and tasks, such as question-answering, summarization, or code generation, to measure model performance and reliability. It is commonly used in AI research and development to ensure models meet quality standards and to compare different models or versions.
Developers should learn and use Evals when working with LLMs to systematically assess model capabilities, identify weaknesses, and track improvements over time, which is crucial for deploying reliable AI applications. It is particularly valuable in research settings, model fine-tuning, and production environments where consistent evaluation against benchmarks like HELM or MMLU ensures robustness and fairness. For example, it helps in validating that a chatbot provides accurate answers or that a code-generation model produces functional code.