I just finished saving a model with one label (based on 600+ manual annotations of text) using the following command:
prodigy train ner
my_annotated_data_1
en_vectors_web_lg
--init-tok2vec ../tok2vec_cd8_model289.bin
--output ./my_model_1
--eval-split 0.2`
Having obtained an F-score
of >95, I now would like to add a second label through the same steps of ner.manual
and prodigy train
.
I am not sure if should create a separate annotation dataset my_annotated_data_2 with the second label -
- and then train and save a separate model my_model_2; or
- but train and save on the same model my_model_1 by providing both my_annotated_data_1 and my_annotated_data_2 as comma separated datasets to the prodigy
train
recipe
Not sure which of these is a better practice and would help achieve the most accurate results. Is there a third alternative?