This is time-wasting.
We can set an early stopping function no matter what users set.
This is just a recommendation for improving Rasa,
maybe there is already some functions I do not know? 
I am training the Rasa response selector model, but for the epochs, I am not sure what number to set.
I set 100 but the accuracy is 99% at 10 epochs,
I have to stop training and set to 10 and retrain OR waiting for the end of training.
This is time-wasting.
We can set an early stopping function no matter what users set.
This is just a recommendation for improving Rasa,
maybe there is already some functions I do not know?
This is time-wasting.
We can set an early stopping function no matter what users set.
This is just a recommendation for improving Rasa,
maybe there is already some functions I do not know?
Closest thing you can do is set checkpoint_model: True under DIET, TED, or ResponseSelector, which saves the best performing model during training.
It requires evaluate_on_number_of_examples > 0 and evaluate_every_number_of_epochs > 0 .
1 Like
@chensaics For more details do visit these Github links:
and the one which Chris suggested is this one:
Your recommendation are already considered 
@ChrisRahme @nik202 Thank you for your reply! 
1 Like
@chensaics No worries close this thread with the solution for others.