Hyperparameter

A setting that controls the training process itself, rather than being learned from data. Examples include the learning rate, number of layers, and batch size. Hyperparameters must be set before training begins and have a large impact on the final model's performance. Selecting good hyperparameters is a significant part of the practical work of building AI systems.
See also: training, gradient descent, experiment tracking.