A blacksmith shop trains a tiny network on quench stills plus temperature notes, and both the training loss and the held-out loss stay high. What does that pattern indicate?
Select an answer to reveal the explanation.
Short Explanation
When the forge model barely moves on either the practice pile or the spare pile, it never learned the pattern. That dual-high-loss story is underfitting, not a gold-star overfitting memorization. Capacity or training setup is too weak for the job.
Full Explanation
Underfitting shows poor fit on both the training set and held-out data because the architecture or training regime did not capture the underlying relationship. Overfitting would typically show strong training fit with weak holdout fit. Persistently high loss on both splits points to underfitting.