I'm working on a Twitter classification task and while analyzing the errors I found quite a few strange predictions. I'm searching for a tool (preferably open-source) similar to https://towardsdatascience.com/how-does-bert-reason-54feb363211 that is able to compute the highest positive/negative attribution given to the words (the reason why I'm not able to use the approach presented in the aforementioned article is the price). In this way, I hope that I'll be able to better understand (and possibly correct) these misclassifications. I tried looking at the attention heads but I don't feel that I'm able to fully understand and draw conclusions based on this information.
Any help would be greatly appreciated!