You've trained a model that looks very strong on the training set, and the team wants to know whether the performance will hold up on unseen data. You need to explain how you would tell if the model is overfitting.
How would you evaluate whether a model is overfitting?
Gap between training and validation metricsCross-validation consistencyValidation log loss versus training log lossWhether performance degrades on recent holdout data