I made a detection model using Faster-RCNN from torchvision. I use as backbone timm 3 library.
Using for example mobilenetv2_110d I end up with a model size of 1.2Go by saving only the state_dict (torch.save(model.state_dict(), "model.pth").
However, using EfficientDet with the same backbone (again from Ross Rightman efficientdet-pytorch 2 ) I end up with a model of 47mb.
I understand there is a big difference between those 2 models in terms of params, but here saved model is 25x times bigger.
Is there a better way to save weights of FasterRCNN ?