Metrics for measuring LLM performance
Metrics are essential for evaluating the performance of LLMs because they provide objective and subjective means to assess how well a model is performing relative to the tasks it’s designed to complete. The following subsections present an expanded explanation of both quantitative and qualitative metrics used for LLMs.
Quantitative metrics
Quantitative metrics play a vital role in the evaluation of LLMs by providing objective, measurable indicators of performance. Let’s review those metrics:
- Perplexity: Perplexity is a key metric in language modeling:
- Definition: Perplexity is a measure of a model’s uncertainty in predicting the next token in a sequence. It’s a widely used metric in language modeling.
- Calculation: Perplexity is calculated as the exponentiated average negative log-likelihood of a sequence of words. A model that assigns higher probabilities to the actual words that appear next in the text will...
