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Evaluation metrics

concept · part of Model evaluation

Key metrics for evaluating fine-tuned models include accuracy, precision, recall, F1 score, and confusion matrix. Accuracy measures proportion of correct predictions; precision measures correctness of positive predictions; recall measures identification of actual positives; F1 score is harmonic mean of precision and recall; confusion matrix visualizes TP, TN, FP, FN.

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