I found a small typo in the section Behind the pipeline - Postprocessing the output 1.


error: [0.9946, 0.0544]


correction: [0.9995, 0.0005]


The following block gives a little bit more context (see the section Postprocessing the output)
tensor([[4.0195e-02, 9.5980e-01],
        [9.9946e-01, 5.4418e-04]], grad_fn=<SoftmaxBackward>)

Now we can see that the model predicted [0.0402, 0.9598] for the first sentence and [0.9946, 0.0544] for the second one. These are recognizable probability scores.