training
Hyperparameter Tuning
The process of optimizing the configuration settings that govern the training process, such as learning rate, batch size, and number of layers. Unlike model parameters, hyperparameters are set before training and significantly impact model performance.
In practice
Grid search tests combinations like learning rates of 0.001 and 0.0001 with batch sizes of 16 and 32 to find the best setup.