Hello Sean!



 Seannyyy:

model_ypred: tensor([-2.0499, -0.7565,  5.0231, -1.4513], grad_fn=)
model_ypred(softmax): tensor([8.4303e-04, 3.0732e-03, 9.9455e-01, 1.5340e-03],
grad_fn=)
Or are the prediction values returned incorrectly?


These Softmax values are correct.
Softmax converts raw-score logits that run from -inf to inf
into probabilities that run from 0 to 1.  Note that your
“model_ypred(softmax)” sum to 1 as proper probabilities should.
The [2] element of “model_ypred(softmax)” is 99.46%, very nearly
100%, and corresponds to the largest (and only non-negative) value
in “model_ypred: tensor”.
Whether the results of Softmax should be understood as “large” or
“small” depends on what you do with them.
The specific formula is here:  Softmax 1
Best.
K. Frank