I would like to train a new entity label that has no relation to the existing labels that have been pre-trained in spaCy’s model. In that light, I thought training a model from scratch (blank ner) would be a great idea to start.
I have a few questions regarding training a blank model.
I have a blank ner model on hand (created from en_core_web_lg). When using any recipe to train my label (for eg ner.match, ner.teach), do I load in this blank model as the argument in the recipe?
When I perform ner.match to annotate via pattern file, I understand that no active learning takes place. So can I assume that, the annotations only gets learnt when I perform ner.batch-train?
When running the batch training, the argument for spaCy model, do I specify the blank ner model?
After I get the trained model and saved it to a directory, whenever I like to train my model again on more data, or continue annotation from where I left off, do I just load the trained model? Is there any other arguments to put, because I notice there is a --resume functionality in ner.teach…
When training model for next time via batch-train, do I train on a brand new blank model or re-train on existing model?