optimizer_adam: Adam Optimizer

In metANN: Metaheuristic and Gradient-Based Optimization for Neural Network Training and Continuous Problems

Adam Optimizer

Description

Creates an Adam optimizer object.

Usage

optimizer_adam(
  learning_rate = 0.001,
  beta1 = 0.9,
  beta2 = 0.999,
  epsilon = 1e-08,
  epochs = 100,
  batch_size = NULL
)

Arguments

learning_rate	Learning rate.
beta1	Exponential decay rate for the first moment estimates.
beta2	Exponential decay rate for the second moment estimates.
epsilon	Small positive constant for numerical stability.
epochs	Number of training epochs.
batch_size	Mini-batch size. If NULL, full-batch training is used.

Value

An object of class "met_optimizer".

References

Kingma, D. P., and Ba, J. (2015). Adam: A Method for Stochastic Optimization. International Conference on Learning Representations.

Examples

optimizer_adam()

metANN documentation built on May 16, 2026, 1:06 a.m.