Daniel Voigt Godoy - Deep Learning with PyTorch Step-by-Step A Beginner’s Guide-leanpub

soon, so please bear with me for now.
Notebook Cell 2.7
%run -i model_training/v5.py
What does the model look like after training another 200 epochs?
print(model.state_dict())
Output
OrderedDict([('0.weight', tensor([[1.9448]], device='cuda:0')),
('0.bias', tensor([1.0295], device='cuda:0'))])
Well, it didn’t change at all, which is no surprise: The original model had converged
already; that is, the loss was at a minimum. These extra epochs served an
educational purpose only; they did not improve the model. But, since we are at it,
let’s check the evolution of the losses, before and after checkpointing:
Figure 2.8 - Losses, before and after resuming training
Clearly, the loss was already at a minimum before the checkpoint, so nothing has
changed!
It turns out, the model we saved to disk was a fully trained model, so we can use it
for…
Saving and Loading Models | 167