Overfitting can hinder model performance. Discuss techniques like regularization, dropout, or data augmentation that have helped you address overfitting.
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I’m seeing 98–99% accuracy on my validation set, but when I test on truly unseen data, the performance drops significantly. Suspecting some leakage but not sure where it’s happening