Shoutout to the 6 people in r/MachineLearning who said just fine-tune a small model first
I burned 3 weeks and about $200 in GPU credits chasing a bigger model for a simple text tagger before I finally listened, and a fine-tuned 7B model hit 94% accuracy on my little dataset of 4,000 rows out of the box, so who else has a story about a small model beating the giant one on a narrow job?