Learning Rate Calculator
Calculate the final learning rate after applying step, exponential, or cosine decay schedules. Helps you plan training hyperparameters for neural networks.
How to Use the Learning Rate Calculator
- Enter your initial learning rate.
- Enter the number of training epochs.
- Select the decay type.
- Click Calculate to see the final learning rate and schedule.
حالات الاستخدام
- •Planning hyperparameter schedules for deep learning training.
- •Comparing decay strategies for convergence speed.
- •Documenting training configurations in ML experiments.
- •Teaching neural network optimization concepts.
الصيغة
Step: lr = lr0 × 0.1^floor(epoch/30). Exponential: lr = lr0 × e^(−λ×t). Cosine: lr = lr0 × 0.5 × (1 + cos(π×t/T)).
الأسئلة الشائعة
What is a learning rate schedule?
A learning rate schedule reduces the learning rate over time to help the model converge to a better minimum.
Which decay type should I use?
Cosine annealing is popular for deep learning; exponential decay is simple and effective; step decay is easy to tune.
What is a typical initial learning rate?
Common values range from 0.0001 to 0.01 depending on the optimizer and model architecture.