problem description

Hello everyone, I use tensorflow+yolov3 for target recognition, batch_size=32,random=0 (no multi-angle training), 5000 rounds of training, the loss value is about 4.1.
on this basis, I set random=1, which is also in the case of 5000 rounds, but the loss reaches 10. I continued to train on the basis of the original model and found that the loss converged to more than 4 o"clock midway, and then diverged globally and would not converge any more.

my inference

because batch_size is always convergent when set to 10, if set to 32, it may exceed the local best point.

my question

I would like to ask you heroes, in fact, is not trapped in the local optimal, in the local best caused by loss shock, I would like to ask what to do next?