python - Why does precision start dropping with MaskRCNN?

Question

I am experimenting with different optimizers and learning rate schedulers to improve the performance of a MaskRCNN model (40K images input, instance segmentation, 1 class). The baseline I am comparing with is the:

PURPLE LINE which uses 
SGD
StepLR(step_size=3, gamma=0.1)

My two attempts at improving is are the

YELLOW LINE
AdamW(lr=5e-5)
ReduceLROnPlateau(patience=3, factor=0.75

BLUE LINE
AdamW(lr=5e-5)
StepLR(step_size=3, gamma=0.1)
2x number of input images

While I'm excited to see the metrics go above the purple line, I'm very interested to show what is happening with the AP@ IoU 0.5 which start to wiggle and drop, where as AP@ IoU 0.75 seems more stable.

The losses for each Mask-RCNN metric are:

Could someone help me understand why this is happening and what it means?

Answer 1

等待大神解答