Yeah exactly, I literally don’t know how to change my spec until I’ve gathered more data.
I was building a transaction classifier recently and I initially thought it would be a trivial “solved” problem. Throw transactions into a tiny local LLM, let it classify. But that approach was too slow, and not accurate enough. I didn’t know that though until I tried and then needed to change the spec.
So wait ... you're not even going to train based on what you want, just "throw into"? Did you actually put in work on a very clear and accurate prompt with a full manual on what to do?
You'd probably get much further along by fine tuning a small BERT style encoder model based classifier for it. IMO, even something as simple as training a linear classifier on the CLS token embeddings from a frozen encoder might work.