PinguSpy
Elite Member
- Dec 7, 2007
- 3,085
- 3,029
The reason why we fine-tuning is to narrow down gpt3 to focus on certain pattern, format, or style of writing, thus.. reducing the cost.
Fine tuning also means discarding other possibilities.
Sometimes I think it doesn't make sense when you fine tune your model with thousands of articles.
Because gpt3 is already smart with hundreds of GB of data.
You don't need to feed it with another articles. Enough with good prompt engineering setup.
I think good prompt engineering setup is the key.
Is it?
Fine tuning also means discarding other possibilities.
Sometimes I think it doesn't make sense when you fine tune your model with thousands of articles.
Because gpt3 is already smart with hundreds of GB of data.
You don't need to feed it with another articles. Enough with good prompt engineering setup.
I think good prompt engineering setup is the key.
Is it?