When comparing NLU-Pipelines i wonder why i should use multiple runs. Accroding to the docs a train/test-split is done only once, so I see no benefit in multiple runs - the only thing that might changes are the random initialization weights of the model.
Am I missing something?
I am talking about this command:
rasa test nlu --config pretrained_embeddings_spacy.yml supervised_embeddings.yml --nlu data/nlu.md --runs 3 --percentages 0 25 50 70 90
from here Testing Your Assistant