This repository was archived by the owner on May 28, 2024. It is now read-only.
This repository was archived by the owner on May 28, 2024. It is now read-only.
Training on a single GPU (Losses keep fluctuating and do not converge) #31
Description
Hi,
I am training the Faster RCNN model on 10% of labelled COCO data. It seems like while training with 1 GPU, the losses don't converge and based on an earlier issue (#12), I understand that with 1 GPU and a batch size of 1 due to tensorpack constaints, the batch size may be too small for the network to train and converge. If that's the case, what are the alternatives? Is the only alternative to move away from tensorpack in order to be able to use a larger batch size?
Any inputs/suggestions are more than welcome as I am a bit stuck at the moment and do not have access to more than 1 GPU.
Regards,
Chandra