Some common evaluation metrics used in NLP include accuracy, precision, recall, F1 score, BLEU (Bilingual Evaluation Understudy) score for machine translation, ROUGE (Recall-Oriented Understudy for Gisting Evaluation) score for text summarization, and perplexity for language modeling. The choice of the metric depends on the specific NLP task and its requirements.