Spacy train ner using multiprocessing
Hi I did same project where I created custom NER Model using spacy3 and extracted 26 entities on large data. See it really depends like how are you passing your data. Follow the steps I am mentioning below might it could work on CPU:

Annotate your text files and save into JSON

Convert your JSON files into .spacy format because this is the format spacy accepts.

Now, here is the point to be noted that how are you passing and serializing your .spacy format in spacy doc object.


Passing all your JSON text will take more time in training. So you can split your data and pass iterating it. Don't pass consolidated data. Split it.
I am trying to train a custom ner model using spacy. Currently, I have more than 2k records for training and each text consists of more than 100 words, at least more than 2 entities for each record. I running it for 50 iterations.
It is taking more than 2 hours to train completely. 
Is there any way to train using multiprocessing? Will it improve the training time?