Evaluating LLM Performance with Perplexity and ROUGE Scores
Large language models have transformed natural language processing, but their impressive capabilities mean nothing without robust evaluation methods that quantify performance objectively and comparably across models. While human evaluation remains the gold standard for assessing output quality, subjective assessments don’t scale to the thousands of model variants, hyperparameter configurations, and training checkpoints that modern LLM … Read more