In particular, in the five tasks (MMLU, MATH, BIG-Bench, Natural2Code, WMT23) where they report going to the GPT-4 API, they report an average of ~1 point improvement. This experiment setting seems comparable, and not evidence they are underperforming GPT-4.
However, all these settings are different from how ChatGPT-like systems are mostly being used (where mostly zero-shot). So difficult to judge the success of their instruction-tuning for use in this setting.
(apologies if this point posted twice. Lesswrong was showing errors when tried to post.)
In particular, in the five tasks (MMLU, MATH, BIG-Bench, Natural2Code, WMT23) where they report going to the GPT-4 API, they report an average of ~1 point improvement. This experiment setting seems comparable, and not evidence they are underperforming GPT-4.
However, all these settings are different from how ChatGPT-like systems are mostly being used (where mostly zero-shot). So difficult to judge the success of their instruction-tuning for use in this setting.
(apologies if this point posted twice. Lesswrong was showing errors when tried to post.)