What are some common NLP metrics used to evaluate models?
An example of an AI chatbot conversation about common NLP metrics for model evaluation.
What are some common NLP metrics used to evaluate models?
Common NLP metrics include accuracy, precision, recall, F1 score, BLEU score, and ROUGE score.
Can you explain what F1 score is?
The F1 score is the harmonic mean of precision and recall, providing a balance between the two.
How is BLEU score calculated?
BLEU score is calculated by comparing n-grams of the candidate translation to reference translations.
What is the difference between precision and recall?
Precision measures the accuracy of positive predictions, while recall measures the ability to find all positive instances.
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