@ptrblck Thanks for reply. So far I’ve ran the entire model on these learning rates but have not tried different learning rates for parts apart from freezing the backbone and head. I’ve tried training from scratch and also fine tuning the resnet101/deeplabv3 model. Basically I’m just doing semantic segmentation on a facial dataset of 2000 training images and 10 facial classes but I’m new to this and it’s difficult to say what might work. Is there any standard technique/tricks which might help inform hyper parameter tuning or setting learning rates per layer?