title: Speeding up model training using MITIE with Rasa
body: <p>I'm training a model for recognizing short, one to three sentence strings of text using the MITIE back-end in Rasa. The model trains and works using spaCy, but it isn't quite as accurate as I'd like. Training on spaCy takes no more than five minutes, but training for MITIE ran for several days non-stop on my computer with 16GB of RAM. So I started training it on an Amazon EC2 r4.8xlarge instance with 255GB RAM and 32 threads, but it doesn't seem to be using all the resources available to it.</p>
  
  <p>In the Rasa config file, I have <code>num_threads: 32</code> and set <code>max_training_processes: 1</code>, which I thought would help use all the memory and computing power available. But now that it has been running for a few hours, CPU usage is sitting at 3% (100% usage but only on one thread), and memory usage stays around 25GB, one tenth of what it could be.</p>
  
  <p>Do any of you have any experience with trying to accelerate MITIE training? My model has 175 intents and a total of 6000 intent examples. Is there something to tweak in the Rasa config files? </p>