I found that this is because the model.train() did not open again when evaluation ends.
solution: just move mode.train() to the epoch loop:
- model.train()
for epoch in range(args.start_epoch, args.epochs):
->
for epoch in range(args.start_epoch, args.epochs):
I found that this is because the model.train() did not open again when evaluation ends.
solution: just move mode.train() to the epoch loop:
for epoch in range(args.start_epoch, args.epochs):
->
for epoch in range(args.start_epoch, args.epochs):