I have trained a new entity type 'MED' (medical diseases) on Spacy's 'en_core_web_md' model.
I managed to train the model on twitter data using the twitter API.
I have got an accuracy of 60% after 6 epochs.
And when I loaded the newly trained model in Spacy to test, I got the below result which is wrong.
nlp = spacy.load('med-model')
doc = nlp(u'John is suffering from cough')
[(ent.text, ent.label_) for ent in doc.ents]
[('John', 'MED'), ('suffering', 'MED'), ('from', 'MED'), ('cough', 'MED')]
The model has predicted all tokens in the test sentence as 'MED' entity.
Can anyone please guide ?