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I do a lot of model tuning and I’m almost ashamed to say I tell GPT what performance I’m aiming for and have it generate the hyper parameters (as in just literally give me a code block). Then I see what works, tell GPT, and try again.

I’m deeply uncomfortable with such a method…but my models perform quite well. Note I spend a TON of time generating the right training data, so it’s not random.




1/8th (soon to be 1/2) of the working world:

"I do a lot of X and I'm almost ashamed to say I tell GPT Y then I see if it works and try again".


Well, I do want to know more about how it works. Anything important I will teach myself, it’s just hard to justify the time investment during work hours when the robot does it. Which I think is also important: these tools save time, but with downsides.




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