Its form determines which errors receive larger penalties and therefore what the model learns to prioritize. During training, gradients of the loss guide parameter updates across examples or batches.
A loss function converts the difference between model behavior and a training objective into a value to minimize.
Its form determines which errors receive larger penalties and therefore what the model learns to prioritize. During training, gradients of the loss guide parameter updates across examples or batches.