What usually has to happen before a model is expected to do well on validation and test data?

True or False: Performance on development and test data is usually lower than performance on the training set.

Training performance comes first

Interpreting Training and Held-Out Performance

Order the steps used to judge whether a better score on unseen data is believable.

Explain why training performance must come before strong validation or test performance.

Diagnose a claim of 72% training accuracy and 89% dev/test accuracy.

Why must training performance be solid before you expect strong validation or test performance?

Which reported result contradicts the training-first rule?

A model that fits the training set poorly can still be expected to do well on dev or test data.