Model performs worse after adjusting learning rate


I’m playing with some simple vision CNNs and trying something similar to what someone tried between class1 and class2, categorizing similar looking relatives. After 6 epochs I’m seeing something like in the image below:

What is weird is that after adjusting the learning rate the performance seems to be much worse.

This seems counterintuitive. I’m likely doing something wrong but I can’t figure out what.

Separately, which pretrained models are known to perform better for face recognition? I saw mentions of VGGFace2,. Even if it’s overkill it might be good practice to try to use it with

Thank you!

If you have watched the Week-3 in the course Jeremy mentions that you should actually use LR of 10 magnitude less than the point where the loss starts increasing. So in your case you should replace le-2 with le-03 and see what happens

Will definitely try it out over the weekend. Have been trying to use face detection and transforms to crop the face + body. face detection is working, transforms not yet.