Spent 3 years tweaking my dataset and the model barely moved

Last month I finally ran the new training pipeline on my NLP project in Austin, after manually cleaning 14,000 rows over those 3 years, and the accuracy went from 78% to 79%. Was I just polishing noise the whole time, or is there a point where human effort stops mattering and you should just throw more compute at it?

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