Thank you very much for your suggestions!
I removed the Variables and use the tensors now directly.
When I remove the .data Attribute from the result and plt.scatter-function, there will be an error-code. How do I get around this? Deleting it from print('Epoch:', epoch, ' Total Loss:', loss.data) went without problems.
I tried a lot of learning-rates. Most of them converge against a loss of 1.5.
I also tried relu in my forward-pass but for thesis-reasons I use sigmoid.
Or do you mean the “linear-layers”? If so, could you tell me how to use a different type there? I wasn´t able to find a working alternative.
I try downsizing my model a little and will see, how the output changes.
Thank you so much so far!
Regards
Christian
EDIT:
I tried using a smaller data-model. This delivered less accurate values.
The average-loss converges now against 2.
I tried using ReLU in my __init__-part, but this error-message comes up:
TypeError: __init__() takes from 1 to 2 positional arguments but 3 were given

I don´t know why linear works while ReLU or Sigmoid won´t.