How models actually learn, from vanilla gradient descent to Adam
Optimizer diagnostics means reading the training run before changing the training recipe. A loss curve, a gradient norm, and a validation curve usually tell you whether the problem is step size, data, scale, overfitting, or a real modeling limit.
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▶ Optimizer Diagnostics