So the model is incapable of outputting [0,1] at any point because of the way I’ve defined the output? Okay that’s been removed and I reran the code.
I’m still getting some strange accuracy values

But now that I’ve removed the torch.exp clause, I’m using it when evaluating the last two test images:
prediction = torch.exp(model(image))
print(prediction)
Variable containing:
 0.6477  0.3523
[torch.FloatTensor of size 1x2]

prediction = torch.exp(model(image2))
print(prediction)
Variable containing:
 0.6543  0.3457
[torch.FloatTensor of size 1x2]

I assume that’s okay to do as it’s not in the model itself?
By the way I thought I’d let you know, this is how my images are set up:
~Data:
   ¬ Training
      -Cats 159 images
      -Dogs 60 images
   ¬ Testing
      -Cats 9 images
      -Dogs 9 images
   ¬ Post-training
      - 1 cat image, 1 dog image