Learning Rate Annealing

Learning rate annealing is a technique used during machine learning training where the rate at which a model learns decreases over time. Initially, the model learns quickly by making larger adjustments to improve accuracy. As training progresses and the model approaches a good solution, the learning rate is gradually lowered to allow more refined, precise updates. This helps prevent overshooting the optimal solution, reduces errors, and improves overall performance. Think of it like slowing down when approaching a destination to avoid overshooting the spot—learning rate annealing fine-tunes the training process for better results.