if epoch >=10:
model.train(False)
for param in model.parameters():
print(param)
param.requires_grad = False
I have freeze the network after some epoch but forward pass results after that epoch are still changing (training and validation accuracy is changing).
Please help me how to overcome.
Thanks in advance.