Learning Rate Scheduling
Machine Learning
A technique that gradually reduces the learning rate during training to fine-tune model parameters more precisely. This helps achieve better final model performance.
Detailed Explanation
Learning Rate Decay is a technique in machine learning that gradually decreases the learning rate over time during model training. By reducing the step size, the model makes finer adjustments to its parameters, leading to improved convergence and performance. This process helps prevent overshooting minima and facilitates settling into an optimal solution for better accuracy and generalization.
Use Cases
- •Tuning training for optimal convergence by gradually lowering the learning rate during neural network training.
Related Terms
Other terms in the Machine Learning category