I’ve already tried “e2e=false” without NL input (see the first snippet in my previous post).
The thing is, whether I set e2e=false or e2e=true, if I include the NL input I get 1of accuracy. Therefore it seems that the e2e flag is being ignored and it tries to do the NLU evaluation in both cases.
If I change to a newer version of RASA I have to move to 1.X, which means major changes that I cannot assume right now.
Perhaps the best way would be to include the nlu part but have the input always be one of the examples. That way NLU accuracy would be (close to) 100% and the results of the evaluation would reflect only the core model.