I used the manual recipe and annotated data. I used the following commands:
prodigy ner.batch-train dummy_data en_core_web_sm --output /home/user --no- missing prodigy ner.teach new_dummy_data /home/user --label TESTONE,TESTTWO
In the train command why do we still use the en_core_web_sm Spacy model? When we train based on our annotations, shouldn’t the parameter name be the model name that I saved on?
What would be the difference between training in SpaCy and Prodigy? Will the results still be the same if we use training commands in SpaCy or using ner.batch-train actually makes a difference?
After the training, in the ner.teach command, shouldn’t we pass the dataset (annotations from manual process) or the model that we trained the model on?