# PaddleNLP Metrics API Currently, PaddleNLP provides the following model evaluation metrics: | Metric | Description | API | | ------ | ----------- | --- | | [Perplexity](https://en.wikipedia.org/wiki/Perplexity) | Perplexity, commonly used to evaluate the quality of language models, and applicable to tasks such as machine translation and text generation. | `paddlenlp.metrics.Perplexity` | | [BLEU (BiLingual Evaluation Understudy)](https://en.wikipedia.org/wiki/BLEU) | A commonly used evaluation metric for machine translation. | `paddlenlp.metrics.BLEU` | | [Rouge (Recall-Oriented Understudy for Gisting Evaluation)](https://en.wikipedia.org/wiki/ROUGE_(metric)) | A metric for evaluating automatic summarization and machine translation. | `paddlenlp.metrics.RougeL`, `paddlenlp.metrics.RougeN` | | AccuracyAndF1 | Accuracy and F1-score, applicable to MRPC and QQP tasks in GLUE. | `paddlenlp.metrics.AccuracyAndF1` | | PearsonAndSpearman | Pearson correlation coefficient and Spearman's rank correlation coefficient, applicable to the STS-B task in GLUE. | `paddlenlp.metrics.PearsonAndSpearman` | | Mcc (Matthews correlation coefficient) | Matthews correlation coefficient, used to measure the classification performance of binary classification tasks. Applicable to the CoLA task in GLUE. | `paddlenlp.metrics.Mcc` | | ChunkEvaluator | Computes precision, recall, and F1-score for chunk detection. Commonly used in sequence labeling tasks such as Named Entity Recognition (NER). | `paddlenlp.metrics.ChunkEvaluator` | | Squad Evaluation | Evaluation metrics for SQuAD and DuReader-robust. | `paddlenlp.metrics.compute_predictions`, `paddlenlp.metrics.squad_evaluate` | [Distinct](https://arxiv.org/abs/1510.03055) | A diversity metric commonly used to measure the form diversity of sentences generated by text generation models. | `paddlenlp.metrics.Distinct` |