When I first started working with deep learning image models, I did what most people do:
- Train a model
- Check top-1/top-5 accuracy
- Look at a few confusion matrices
On paper, everything looked great. But when I started poking at the models in slightly weird ways, I learned a very uncomfortable truth:
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