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Alpaca RLHF-ed to beat ChatGPT

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Re: Alpaca RLHF-ed to beat ChatGPT

#31
post #22

Hm. Title: “beats Chat GPT” Reality: > With these evaluation instructions, we compare RLHF model responses to Davinci003 responses and measure the fraction of times the RLHF model is preferred; we call this statistic the win-rate. > Of the methods we studied, PPO proves the most effective, improving the win-rate against Davinci003 from 44% to 55% according to human evaluation, which even outperforms ChatGPT. …for the…

Yeah, and I think they are using an old version (3.0? 3.5?) of ChatGPT, not GPT4, which is way better. Can anyone verify? They confusingly list GPT4 as a separate LLM, even though ChatGPT supports GPT4.

The confusion is provided entirely by OpenAI, in my opinion.

Re: Alpaca RLHF-ed to beat ChatGPT

#32

Whenever I see a claim about GPT I get temporarily interested until I learn it’s GPT3.5 and not GPT4. 4 isn’t just marginally better at most tasks I use it for, it’s operating at an entirely different level to the point where I have little (no?) day-to-day use of 3.5 at this point.

I'm assuming you use gpt4 via ChatGPT plus. Does the message cap bother you? I heard it's something like 25 messages per 3 hours. That sounds so low I don't even bother subscribing. I guess this doesn't apply if you use it via the api.

I only hit the limit when I using some bots to interact with it. Never hit it after 2 months when normally using it.

Re: Alpaca RLHF-ed to beat ChatGPT

#34

Whenever I see a claim about GPT I get temporarily interested until I learn it’s GPT3.5 and not GPT4. 4 isn’t just marginally better at most tasks I use it for, it’s operating at an entirely different level to the point where I have little (no?) day-to-day use of 3.5 at this point.

I'm assuming you use gpt4 via ChatGPT plus. Does the message cap bother you? I heard it's something like 25 messages per 3 hours. That sounds so low I don't even bother subscribing. I guess this doesn't apply if you use it via the api.

In practice it rarely comes up. I don't even know if it's actually enforced. I'm pretty certain I do more than 25 every 3 hours.

Re: Alpaca RLHF-ed to beat ChatGPT

#35
post #22

Earlier quoted context omitted.

Yeah, and I think they are using an old version (3.0? 3.5?) of ChatGPT, not GPT4, which is way better. Can anyone verify? They confusingly list GPT4 as a separate LLM, even though ChatGPT supports GPT4.

The confusion is provided entirely by OpenAI, in my opinion.

No one using ChatGPT is confused. You have to make an explicit choice in the switch, and if you are using the API you have to put the name in as a parameter.

Re: Alpaca RLHF-ed to beat ChatGPT

#36

Whenever I see a claim about GPT I get temporarily interested until I learn it’s GPT3.5 and not GPT4. 4 isn’t just marginally better at most tasks I use it for, it’s operating at an entirely different level to the point where I have little (no?) day-to-day use of 3.5 at this point.

GPT-4 barely performs above 3.5 now. They’ve resource-constrained or otherwise hobbled it to support all the corners of Microsoft products they’re stuffing it in. The amount of errors and logic degradation after the May update is incredibly obvious for all but the most trivial use cases.

It’s going to be very funny if being turned into a next generation Clippy is what makes them lose out to their competitors

Re: Alpaca RLHF-ed to beat ChatGPT

#37

Earlier quoted context omitted.

I'm assuming you use gpt4 via ChatGPT plus. Does the message cap bother you? I heard it's something like 25 messages per 3 hours. That sounds so low I don't even bother subscribing. I guess this doesn't apply if you use it via the api.

I was initially deterred. But in practice, when using it for professional purposes, I never encounter it. Your coding speed is unlikely to be that fast, requiring 25 code segments in 3 hours. GPT-4 outputs something, you need time to double check, test, additional googling etc. Its still a massive speed boost. Using it recreationally (Especially chatting) will result in a lot more requests.

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Re: Alpaca RLHF-ed to beat ChatGPT

#38

Whenever I see a claim about GPT I get temporarily interested until I learn it’s GPT3.5 and not GPT4. 4 isn’t just marginally better at most tasks I use it for, it’s operating at an entirely different level to the point where I have little (no?) day-to-day use of 3.5 at this point.

GPT-4 barely performs above 3.5 now. They’ve resource-constrained or otherwise hobbled it to support all the corners of Microsoft products they’re stuffing it in. The amount of errors and logic degradation after the May update is incredibly obvious for all but the most trivial use cases. It’s going to be very funny if being turned into a next generation Clippy is what makes them lose out to their competitors

Microsoft hosts their own models through azure? Why would that resource constrain OpenAI?

Re: Alpaca RLHF-ed to beat ChatGPT

#39

Earlier quoted context omitted.

What does “win” mean though? It improved the simulated win rate vs human win rate? …but chatgpt had a higher win rate overall? (And gpt4 was much higher) What is the significance of the difference between simulated and human win rates?

You provide two samples side by side and see what humans prefer. You should try asking what you don’t know in a non judgemental manner

/shrug

The paper says:

> We find that PPO sim trained in AlpacaFarm only achieves a win-rate of 43%, while PPOGPT-4 sim trained on GPT-4 data achieves a win-rate of 50%. To contextualize these results, the initial SFT model has a win-rate of 44%, PPOhuman has a win-rate of 55%, and the best non-PPO human method has a win-rate of 51% (Best-of-16). Thus, training in simulation can provide good models directly for deployment, though this approach suffers a 5% performance gap relative to collecting real human annotations.

...

> However, we also observe that no single LLM-based annotator captures the heterogeneity of human annotation, and substantial amounts of noise had to be injected in the simulated preference for rankings of methods trained in AlpacaFarm to match those trained with real human feedback.

...and, in summary:

> We showed that AlpacaFarm substantially lowers the cost and iteration time of research on and development of methods for learning with pairwise feedback. AlpacaFarm provides a blueprint for constructing other useful simulators for AI research that requires human supervision, and we view it as an exciting opportunity to expand this simulation approach to support data from other domains as well as methods that learn from alternative forms of human feedback.

Ok.

...but that's no what the blog post said. The blog post said:

> Of the methods we studied, PPO proves the most effective, improving the win-rate against Davinci003 from 44% to 55% according to human evaluation, which even outperforms ChatGPT.

The closest the paper got to saying that was:

> The other mismatch is ChatGPT against PPO, where human annotators preferred PPO (55.1% vs 52.9%) unlike the simulator (46.8% vs 61.4%).

That's interesting.

> In both cases, these are not major mistakes, as we do not expect SFT52k to be much worse than SFT10k or for a 7B LLaMA model to substantially outperform ChatGPT.

?? Mistakes?

So.. I mean, yes. I'm judging. When you write a blog saying "outperforms ChatGPT" and then, the paper doesn't say that... well.

It's a bit shit isn't it?

Re: Alpaca RLHF-ed to beat ChatGPT

#40

Earlier quoted context omitted.

GPT-4 barely performs above 3.5 now. They’ve resource-constrained or otherwise hobbled it to support all the corners of Microsoft products they’re stuffing it in. The amount of errors and logic degradation after the May update is incredibly obvious for all but the most trivial use cases. It’s going to be very funny if being turned into a next generation Clippy is what makes them lose out to their competitors

Microsoft hosts their own models through azure? Why would that resource constrain OpenAI?

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