calculating the top k accuracy using logits vs softmax probabilites I am working on calculating the top k accuracy of a model my model output logits (I am working on pythorch) so in order to calculate the top k accuracy using sklearn i was wondering what would be the difeerence if I calculate the top k accuracy using the logits vs the softmax probabilites ?
Thanks in advance

The accuracies will be the same. Softmax is a monotonic increasing function, so the argmax on the logit scale is the same as the argmax on the probability scale. Likewise, the top $k$ entries will be the same.
