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You are thinking of supervised learning, in which a model is trained to generate labels for inputs. In self-supervised learning, the training target is a modif
by abrichr 3y ago
You are thinking of supervised learning, in which a model is trained to generate labels for inputs.
In self-supervised learning, the training target is a modified version of the input.
Transformers are trained in a self supervised manner. The problem they solve is "given a sequence of N tokens, what is the next most likely token?"
No labels required :)
- m3kw9 3y agoWhat about the human reinforcement part of it?
- TOMDM 3y agoThere's no traditional human reinforcement. Models like gpt3 get turned into models like ChatGPT through RLHF (reinforcement learning from human feedback), by fine-tuning the model further on prompts in the style we'd like them to respond in, typically User: question Bot: Response This is done by handcrafting or modifying data from places like stack exchange.