Thanks for the fast reply.
If I deactivate the Sigmoid, the model indeed starts learning, though not really good. Besides that it starts outputting numbers outside of the interval [0,1].
But my true labels are 0 or 1 in a Tensor of shape [batch_size, 1], so coming from Keras I chose Sigmoid as I want the output to be a probability between 0 and 1.
So which loss function would I have to choose for the model to work? Or should I remodel the true labels to [batch_size, 2], i.e. using one hot encodings, and then use simple BinaryCrossEntropy loss?