How to reduce the training time?

  • I am using rasa with the pipeline spacy_sklearn.
  • ner is the main motto of my project everything is going good but training for only two son files its taking around 1hr
  • The size of two json files are 15mb each
  • How to reduce the training time pls anyone help me out

and how to increase parallel jobs = 1 to 10

What version of rasa are you using, and how are you training your bot – via the command line, python API, etc?

I am using rasa-nlu==0.15.1 I am training the bot using rasa with pipeline space_sklearn through python I am training the bot

import spacy #nlp=spacy.load(‘en’) import subprocess from rasa_nlu.training_data import load_data from rasa_nlu.config import RasaNLUModelConfig from rasa_nlu.model import Trainer from rasa_nlu import config from rasa_nlu.model import Metadata, Interpreter import time training_data=load_data(“data/dt/geo_train.json”)

#config backend using spacy and sklearn trainer= Trainer(config.load(“config_spacy.yml”))

print (“time.ctime() : %s” % time.ctime())


print (“time.ctime() : %s” % time.ctime())

#directory to store our model model_directory= trainer.persist("./projects/")

#making predictions owth the model interpreter= Interpreter.load(model_directory)

see my code