Closed hemanth2410 closed 2 years ago
PC specs Intel core i7 7700HQ @ 3.4 GHz 8 GB SODIMM DDR 4 RAM GTX 1050 4GB(NETBOOK)
if it's not problem in path to files, you can try add batch_size=32 or 16 or even 4 (by default its 64) to model.fit() . Neural networks are really heavy for gpu memory, so 16 worked for me, problem is, it may cause some acc and loss issues on later epochs, but without this can't run at all, so i'm curious does it affects a lot, I mean, will model be okay with such size, or its bad idea.
What is the command that you used for training ?
if it's not problem in path to files, you can try add batch_size=32 or 16 or even 4 (by default its 64) to model.fit() . Neural networks are really heavy for gpu memory, so 16 worked for me, problem is, it may cause some acc and loss issues on later epochs, but without this can't run at all, so i'm curious does it affects a lot, I mean, will model be okay with such size, or its bad idea.
how to decrease the batch size in model.fit() for version .03
while training with Tensorflow GPU i am getting resource exhausted error