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Shoutout to the one line of Python that fixed my whole training loop after 11 days
My image classifier kept spitting out the same guess for every input and I spent 11 days chasing it. Rebuilt the data pipeline, swapped optimizers twice, even rented a bigger GPU for a weekend. Turned out my labels were getting shuffled out of sync with my images back in step 3. One line to zip them together and it jumped from 12% to 89% accuracy in a single run. Anyone else lose a week plus to a data bug instead of the model itself?
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