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What is the significance of perplexity in the context of training models, particularly in natural language processing? How does it influence the evaluation and performance of these models? Additionally, what are its implications for understanding model predictions and improving their accuracy in generating coherent and relevant outputs?

What role does perplexity play in training?

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What role does perplexity play in training?

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