Choosing a profile
This step is not mandatory, but we highly recommend you to read it as it touches an important component of
classy, the profiles, which is needed in case you want to heavily modify your training configuration.
It might be the case that you have constraints of any sort (hardware, performance-wise, etc.), and you might be interested in knowing how to change the default underlying model / optimizer used to train in order to either fit in smaller GPUs, be faster, or achieve higher accuracy.
In classy, this is achieved through Profiles, which a user can employ as a way of changing the training configuration
of their model to fit different criteria.
classy comes with a predefined set of profiles, which you can find here.
The list includes the underlying transformer model, optimizer and a few key features that each profile shines for.
For this tutorial, we'll stick with a fast yet powerful model, DistilBERT.