How is perplexity calculated in language models?

Perplexity is a measurement used in language models to evaluate how well a probability distribution predicts a sample. It quantifies the uncertainty of the model when predicting the next word in a sequence. A lower perplexity indicates better predictive performance, reflecting how effectively the model understands and generates language.

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