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

Output
OrderedDict([('0.weight', tensor([[1.9414]], device='cuda:0')),
('0.bias', tensor([1.0233], device='cuda:0'))])
Great, these are the weights of our trained model. Let’s train it a bit further.
In Chapter 2, we could only train it for another 200 epochs since the number of
epochs was hard-coded. Not anymore! Thanks to our StepByStep class, we have
the flexibility to train the model for as many epochs as we please.
But we are still missing one thing … the data! First, we need to set the data
loader(s), and then we can train our model for another, say, 50 epochs.
Notebook Cell 2.1.6
new_sbs.set_loaders(train_loader, val_loader)
new_sbs.train(n_epochs=50)
Let’s take a look at the losses:
fig = new_sbs.plot_losses()
Figure 2.1.3 - More losses!
We have loss values over 250 epochs now. The losses for the first 200 epochs were
loaded from the checkpoint, and the losses for the last 50 epochs were computed
after training was resumed. Once again, as in Chapter 2, the overall levels of the
losses didn’t change much.
Classy Pipeline | 201