Comments (3)
Sorry, typo in the above: But loss is not decreasing and Precision is also not improving as shown below:
from lightcnn.
The reason is that we don't save optimizer in the checkpoint. Light CNN is trained by SGD with momentum. If you resume from the saved model, the weights are loaded from the checkpoint but the status of optimizer is not.
You can modify these lines
save_checkpoint({
'epoch': epoch + 1,
'arch': args.arch,
'state_dict': model.state_dict(),
'optimizer': optimizer.state_dict(),
'prec1': prec1,
}, save_name)
And you also need to modify the lines of loading checkpoint
if args.resume:
if os.path.isfile(args.resume):
print("=> loading checkpoint '{}'".format(args.resume))
checkpoint = torch.load(args.resume)
args.start_epoch = checkpoint['epoch']
model.load_state_dict(checkpoint['state_dict'])
optimizer.load_state_dict(checkpoint['optimizer'])
print("=> loaded checkpoint '{}' (epoch {})"
.format(args.resume, checkpoint['epoch']))
else:
print("=> no checkpoint found at '{}'".format(args.resume))
from lightcnn.
Thanks a lot. Sairam
from lightcnn.
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