Hi I want to save my model during the training. My model has 9 conv layers with batch norm and softmax as activation function. I use this method to save my training modeel but when I resumed my training I sensed that it resumed from begining.
state = {
    'epoch': epoch,
    'state_dict': model.state_dict(),
    'optimizer': optimizer.state_dict(),
}
    torch.save(state, '/home/superblock/state_train.pt')

  state = torch.load('/home/superblock/state_train.pt')
  model.load_state_dict(state['state_dict'])
  optimizer.load_state_dict(state['optimizer'])

what should I do?
does it need model.eval()? I read some where that for resuming  training we dont use that
and I have another question… It’s better to save when loss is fewer in validation data or train data?