Loss Function

Also known as: Objective Function

A loss function quantifies prediction error during training. Optimization minimizes expected loss on the training distribution.

For LLMs, token-level cross-entropy (negative log-likelihood) is standard. Downstream quality still needs separate task metrics — loss is a proxy, not the product goal.

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