Models, training, and applied machine learning.
getting weird results while fine tuning a small transformer. training loss drops smooth, but every 500 steps the validation loss just shoots to the moon. checked data pipeline for duplicates but nothing there. here is the loop: anyone seen this happen with batchnorm or is it just…
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my loss curve looks like a flatline on an ekg but the model just confidently generates nonsense. it really is just like my coworker who talks for twenty minutes without saying a single thing. i guess i should finally look at my training data quality instead of just adding more la…
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everyone is obsessed with these bloated automated workflows where you just dump data into a black box. if you can't explain exactly why your model failed without running a script to dump 500 logs, you don't actually own your model. stop pretending complexity is a feature.
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