Earlier quoted context omitted.
>Could someone explain in simple terms exactly what fine-tuning does? Fine-tuning shows the model examples of sequences it should produce. The model is updated to become more likely to produce sequences like those examples. What precisely 'like those examples' means for brand new prompts unlike those in the training distribution is the black magic of generalization. >Does it show the model how to answer questions, or…
Thank you for this answer! > I generally recommend retrieval Yes that's what everyone's saying and it's also what we're working on. I was wondering what fine-tuning may be used for. Are there use cases where fine-tuning might be worth it (esp; given all the hard work it entails)? > akin to a student taking a test with open notes they can refer to, rather than trying to remember a textbook they read a week ago Excelle…
Re: GPT-3.5 Turbo fine-tuning and API updates
#241Yes, this is for training your own public facing chatbot. So that it does not easily break character and go wildly off-script, like bing, and start ranting at the old lady trying to check her balance. This will likely dramatically increase the number of chatgpt customer service bots in the near future, but on the up side, at least they wont all be regurgitating that "as a language model" shtick. That is if they are willing to pay to beat it out him.