perplexity

Perplexity is a measurement used in language modeling and natural language processing to evaluate how well a probability model predicts a sample of text. It quantifies the model’s uncertainty—the lower the perplexity, the better the model is at predicting the words in the sample. In essence, perplexity can be thought of as the weighted average branching factor of a language model.
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