Learning Rate Decay
Learning Rate Decay is a training hyperparameter setting that gradually decreases the optimizer's learning rate over epochs, allowing the model to make large updates early and fine adjustments later.
Frequently Asked Questions
Why decay the learning rate?▼
To prevent the model from overshooting the global minimum of the cost function as training converges.
What are common decay strategies?▼
Exponential decay, step decay, and cosine annealing schedules.
Quick Facts
- CategoryModel Training
- Key ApplicationModel training optimization, convergence speed adjustments, and validation loss tuning.
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