Text Classification predictions default to naive "all negative"

(Blake Shurtz) #1

Hi, I’m building a text classification model in fastai. The problem is that when the model is complete, all predictions default to all negative and accuracy is about 80%. (The labels have an 80/20 frequency split.)

I can adjust the classification threshold within the nearest percentage integer to get from 0% to 71% sensitivity.

If I were using standard ML methods, I would apply some sort of hybrid sampling technique, but I’m not sure what to do here