How can I implement dynamic learning rate schedules for Julia-based models

Question

With the help of programming, can you explain how I can implement dynamic learning rate schedules for Julia-based models?

Answer 1

To implement dynamic learning rate schedules for Julia-based models, you can adjust the learning rate dynamically during training using custom functions or predefined schedules. Here is the code snippet you can refer to:

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In the above code, we are using the following:

• Learning Rate Schedule: A function that updates the learning rate based on the current epoch using an exponential decay formula.
• Integration: Called during each epoch of the training loop to adjust the optimizer's learning rate dynamically.
• Flexibility: You can customize the schedule for other strategies (e.g., step decay, cosine annealing, or cyclical learning rates).

Hence, this approach allows the model to train efficiently by adjusting the learning rate over time.