Cross-entropy loss

Cross-entropy loss is a loss function that measures the gap between predicted probabilities and the true labels. It is the standard training objective for classification and for next-token prediction in language models.

Cross-entropy loss sits in the Foundations part of the Agentik {OS} glossary, which defines the words used to build and run AI agent systems.

Also called Cross-entropy, Log loss.