FAQ: Hyperparameter Tuning - Manual tuning: learning rate

This community-built FAQ covers the “Manual tuning: learning rate” exercise from the lesson “Hyperparameter Tuning”.

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This exercise can be found in the following Codecademy content:

Build Deep Learning Models with TensorFlow

FAQs on the exercise Manual tuning: learning rate

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How can I interpret the graph? What are the key aspects? Is it good if learning rate = validation rate?
And is it good if the graph is declining?

Having some issues with this path as well!
I’m quite lost on the shape of the layers subject.
But I think that the graphs are meant to show that the blue line (training set loss) never actually reaches the orange line (validation set loss) if the learning rate is too small. That means that the validation set isn’t converging with the training set, which means that the model will perform poorly, since any other dataset should have a close performance to the training set. Hope that’s what we are supposed to take from this exercise.

i think you guys maybe didnt see the different values on the y-axis