F1-score (also called harmonic mean) is a metric that takes into account both precision and recall:
$$ \mathrm{F1} = \frac{2*Precision*Recall}{Precision + Recall} $$It is widely used in NLP and it balances precision and recall, handling class imbalance and highlighting poor performance on minority classes.