Perplexity is in the context of AI and NLP a crucial metric. It measures the uncertainty of a language model when predicting the next word in a sequence. A low perplexity value indicates a high prediction accuracy and a better understanding of the model for the text data.
Perplexity is often understood as the exponential value of the cross entropy and quantifies how well a probabilistic model predicts a sample. Essentially, the value indicates how many equally probable words the model considers on average as potential next words.
Basics and calculation of perplexity
Perplexity is a decisive
