# One hot vector output in classification task

I'm working on CNN model and I used one hot vector type of labels. The number of classes is 3: [1,0,0], [0,1,0], [0,0,1].

net(x)


I'm getting such an output: [0.8439, 0.1355, 0.0757], which is obviously 1st class. The question: why a sum of values in this vector exceeds 1? Also, I got earlier even one negative value of those 3. On what it is depending and how to know what these "outputs" could be.