Caught my A.I. training tool using the same test data for validation for 3 months

I was running my object detector loop again last week and noticed the accuracy numbers looked too good. Turns out I had a file path error in my Python script, so it was pulling validation images from the training folder instead. Felt like a total rookie when I spotted it in the terminal. Anyone else had a sneaky bug like that waste your time?

3 comments

3 Comments

iris_green842mo ago

Yeah, that "accuracy numbers looked too good" part hit hard. I had the same kind of bug where my training script was accidentally reading from the test set for validation. It took me like a week to figure out because the loss curves looked perfect but then the model flopped in production. The fix I use now is to print out the first few file paths from each dataloader at the start of every run. Just a simple check that takes five seconds but saves you from that embarrassing realization later. Also, hardcoding a small validation set that never changes is a solid backup plan for catching these mixups early.

ryan_carr592mo ago

Printing a batch of sample paths before each training run caught this exact mistake for me.

wren_smith4424d ago

That's a really smart take and honestly it kind of flips what I used to believe on its head. I always thought printing out paths was a waste of time and that my code was clean enough to trust. But after getting burned by a similar data leak bug last month, I'm totally on board now. The one that got me was having a jumbled folder structure where training and test images got mixed up during a copy paste. Seeing the actual file names pop up in the terminal would have caught it in 2 seconds instead of the 2 days I spent debugging. Now I always print the first three batch paths on every new run, it's such a tiny habit that pays off huge. Hardcoding a fixed validation set sounds like a great safety net too, might steal that idea for my next project.