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Notes -
The calibration plots also jumped out at me. There's also this nugget:
My first instinct was also to infer that the process of "aligning" the model to be politically correct and milquetoast was making it dumber. But it's not entirely clear that that's what's going on. The fine-tuning process is not just about neutering the model's ability to produce hate speech or instructions for making bombs. It's also what makes the model work in an interactive, chatbot paradigm. The API for a vanilla language model is basically "sample some text conditioned on this prefix". If you asked the basic pretrained GPT-4 something like "Write an essay about symbolism in Richard III." it would be likely to output something like "Your essay should be between 1,000 and 1,500 words, and follow the structure described in last week's handout. Submit your essay through the online portal no later than March 24th at 10pm." It would be interesting to get more details on the different regimens of post-training and how each affected the model's calibration and performance. But given the secrecy attached to the project, it seems unlikely we'll get anything like that.
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