LLM Testing
Fine-Tuned Model Evaluation: Benchmarks, Accuracy Regression, and RLHF Testing
Fine-tuning a language model improves it on your specific task — but at a cost. Fine-tuned models can regress on capabilities the base model had, forget general knowledge, or overfit to training data in ways that hurt generalization. This guide covers how to evaluate fine-tuned models systematically: benchmark