How do I choose the right initial learning rate for my model?

How do I choose the right initial learning rate for my model?

Choosing the right initial learning rate is crucial for training your model effectively. A common approach is to start with a small value, like 0.001, and adjust based on the model's performance.

What happens if the learning rate is too high?

If the learning rate is too high, the model may converge too quickly to a suboptimal solution or even diverge, leading to poor performance.

And what if it's too low?

If the learning rate is too low, the training process can become very slow, and the model may get stuck in local minima, failing to reach the best solution.

Are there any techniques to find the best learning rate?

Yes, techniques like learning rate scheduling, grid search, or using the learning rate finder method can help you identify the optimal learning rate.