2 ms·
The reason to fine tune is to get a model that performs well on a specific task. It could lose 90 percent of it's knowledge and beat the unturned model at the
by robrenaud 2y ago
The reason to fine tune is to get a model that performs well on a specific task. It could lose 90 percent of it's knowledge and beat the unturned model at the narrow task at hand. That's the point, no?
- OutOfHere 2y agoIt is not really possible to lose 90% of one's brain and do well on certain narrow tasks. If the tasks truly were so narrow, you would be better off training a small model just for them from scratch.