I have a problem regarding a large variation in the result I get, by running my model multiple times. The exact same architecture and training gives anywhere from 91.5% to 93.4% accuracy on image classification (cifar 10).
The problem is that I don’t know how to use the torch random seed in order to get the better results, not the worse ones. I tried various values for the random seed, with:
torch.manual_seed(7)

and I get the lower bound of the results. Any ideas?