Perplexity — это метрика, используемая для оценки того, насколько хорошо вероятностная языковая модель предсказывает последовательность. Более низкая perplexity обычно означает, что модель присваивает наблюдаемому тексту более высокую вероятность и менее неопределенна относительно вероятных продолжений.
One measure of how well a model is accomplishing its task. For example, suppose your task is to read the first few letters of a word a user is typing on a phone keyboard, and to offer a list of possible completion words. Perplexity, P, for this task is approximately the number of guesses you need to offer in order for your list to contain the actual word the user is trying to type. Perplexity is related to cross-entropy as follows:
Perplexity is a metric used to evaluate the performance of language models. It measures how likely the model is to generate a given text sequence based on the distribution of the text it was trained on. Perplexity is a commonly used metric for evaluating language models and is often used to compare the performance of different models or to track the progress of a model during training.