I’m not sure how you’ve implemented your logistic regression in PyTorch, but your vanilla implementation might differ from sklearn’s default setup.
There was a discussion about these “magic” numbers and default setups on Twitter 37, where Zachary wonders, if users know that the default logistic regression uses e.g. L2 regularization.
In that sense, could you try to adapt the code bases to be as close as possible to each other?