Validation Data

A held-out slice of data used to tune settings and check progress while training, without touching the test set.

Validation data sits between training and test. You use it to choose hyperparameters and to spot overfitting early, because the model never learns from it directly. Reusing it too aggressively leaks information and quietly makes it a second training set.

In practice: If validation loss starts rising while training loss keeps falling, you are overfitting — stop.