Glossary · Math & training
Hyperparameter
A configuration choice that shapes model structure, optimization, data processing, or inference rather than being learned as an ordinary model parameter. Examples include learning rate, batch size, layer count, and decoding settings.
Common confusion
Some hyperparameters are selected before training, while others can be changed during a schedule or at inference time.
Related terms
Browse the learning paths to see this term in context — every lesson is free to read.