# BERT : text classification and feature extractionn

I have tried multi-label text classification with BERT.

Here is the sample input: $15.00 hour, customer service, open to industries One of the labels is Billing_rate and prediction score looks quite good. Now my question is if I want to extract$15.00 hour basically feature value out of BERT. Can you please suggest what are my next step options?

You'd need to apply a tagger, either a generic NE tagger or a custom-trained one. The tagger works with each token as an instance, so that you can extract a particular sequence of tokens, e.g.:

\$15.00     Begin_Billing_rate
hour       Billing_rate
customer   _
service    _
,          _
open       _
to         _
industries _


Of course in order to train a custom tagger you will also have to annotate your data token by token.