Spent 11 days fighting a model that kept flagging my own training data as garbage
I was fine tuning a small image classifier for a side project and the thing kept labeling about 30% of my own labeled samples as wrong. Turned out my data loader was pulling from the wrong folder after a cache got stale, so the model was training on old pics the whole time and I never caught it. I lost 11 days rerunning jobs on a rented GPU at $2.40 an hour before a friend asked me to just print the file paths. Now I check paths first, every single time, before I blame the model. Anyone else burn real money on a dumb pipeline bug instead of an actual AI problem?