Hi,
I am new for Prodigy.
I recently trained one model to identify FOOD related words based on model “en_core_web_lg” and the accuracy is quite impressive.
However, when I tried some sentences below, I found sth strange.
95% onion.
------------old model----------------
[(‘95%’, ‘PERCENT’)]
------------new model----------------
[(‘95’, ‘WORK_OF_ART’), (’%’, ‘WORK_OF_ART’), (‘onion’, ‘FOOD’)]
It seems the pre-trained model “en_core_web_lg” can identify some other labels which are also important for me. And my own trained model ignored most of them and can only identify “FOOD” (which is good) and “WORK_OF_ART” (I am not sure where is that from)?
Could you please give me some explanation why it is working like that?
Cheers