Table 4.

The model parameter settings.

Parameter name	Value	Importance
Learning Rate	0.001	The learning rate affects the efficiency and performance of model training, determining the magnitude of weight updates and directly influencing convergence speed and results.
Batch size	64	The number of samples processed before updating the model impacts the stability and speed of the training.
Loss Function	Cross Entropy	The loss function measures how well the model’s predictions match the actual results.
Optimizer	Adam	Optimizer helps the model learn and improve.