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Pro tip: When your neural network thinks everything is a penguin
Fine-tuning an image classifier, and it kept calling everything a penguin, like cars, trees, and my coffee mug. I checked the code and hyperparameters, but all seemed fine. Turns out I left a penguin dataset in the training loop from a late night. After removing it and retraining, the problem was solved. Now I triple-check data sources before any training session, a stupid mistake that's funny in hindsight.
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julia_ward7mo ago
Can you believe how common these kinds of mistakes are? That penguin story is gold, and I totally feel your pain. I once trained a model that kept predicting everything as cats because I accidentally left a cat image filter on during data preprocessing (it was supposed to be for a different project). I wasted days tweaking parameters before I noticed the oversight, which was embarrassing but educational. Now I have a checklist for data sanitation that I follow religiously, even for quick experiments. It's funny how the dumbest errors teach you the most valuable lessons, right?
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markg597mo ago
Actually, @julia_ward, I gotta disagree. Those dumb errors just waste time, checklists make people complacent. Saw a team miss a bias issue by blindly following a list. Embracing chaos sometimes teaches more than rigid steps.
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charles_burns7mo ago
Yeah that's why I double-check training data now. @julia_ward, once trained a model on "cabybara" pics that were just guinea pigs, whole thing was useless.
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