Hey,
I’m performing a binary classification on a 3d MRI scan dataset while using nn.CrossEntropy as my loss function.
In my training loop i calculate the loss as
loss = loss_fn(pred, y)

which is pretty standard.
What i’m trying to learn is what can be inferred from the loss value. i.e

What do these loss values represent?
What classifies as a good value?
What do these values tell me about my model, data…?

The results i’m currently getting are
loss: 530.178589  [    0/  474]
loss: 231.394638  [   70/  474]
loss: 61.357143  [  140/  474]
loss: 482.464294  [  210/  474]
loss: 452.214294  [  280/  474]
loss: 173.785721  [  350/  474]
loss: 117.030411  [  420/  474]

Which intuitively does not feel satisfactory.
Would really appreciate if someone can help me understand what is a good score (if any).
Thanks