nn.Softmax returns very small value

I’m trying to replicate the GNNExplainer.
When evaluating a trained GNN model inside the GNNExplainer with a subset of the original training dataset, some the of node returns prediction as shown below. As i try to do a softmax on it, it returns a list of very small values, which I won’t be able to use to calculate the loss…

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=)

Sorry I’m very new to GNNs and softmax function… I would appreciate if anyone can give me some advice on the softmax function. Or are the prediction values returned incorrectly?