How does gradient accumulation affect optimizer dynamics?

Gradient accumulation simulates larger batch sizes, affecting convergence behavior.

Accumulating gradients over multiple steps effectively increases batch size, reducing gradient noise and stabilizing updates but potentially requiring learning rate adjustments for optimal convergence.