I have a general question about Prodigy best practices. I bootstrapped a spaCy model using raw data and
ner.manual command to train a model on top of
en_core_web_md to detect a custom entity.
I evaluated my model and found some errors, so I collected more data and now want to update the old model with this new data. What is the best practice here? Should I use
ner.manual - is the only difference that one suggests annotations to speed up time?
Also before training with
prodigy train ner should I combine the two datasets into one to prevent anything like the catastrophic forgetting problem? Thanks!