I’m relatively new to fine tuning gpt-3 models therefore any tips would be amazing!
I created a few different robots and I wanted to let gpt-3 explain them to someone when they are asking questions about a specific robot. In the following text I will just refer to the robots as objects.
I tried to fine tune a davinci and a curie model to know and understand new objects.
(The non-finetuned models have no knowledge about them)
I have about 15 to 20 different new objects.
How can I bring davinci or curie to the point that they know the objects?
I tried it like this:
Creating a new dataset with information about the objects.
- What is object1 ?
- What does object1 do?
- What is special about object1?
- What is object2?
- What does object2 do?
- What is special about object2?
- Writing responses to the questions above
- Fine tuning
What I noticed is that both models Curie and Davinci are sometimes mixing up information.
Generating information of object2 and putting those into the text when I ask for object1.
Is there a way to make it more consistent and “bind” them more to the objects?