Understanding Reinforcement Learning with Human Feedback Part 3: Collecting Human Preferences

In the

For example, given two possible answers, a person can simply choose the better one.

Collecting preferences like this is much faster than asking people to manually write responses for every prompt.

This preference collection process is the “Human Feedback” part of RLHF.

Using Preference Data

Once we collect preference data, we can use it to train the model so that it assigns higher scores to preferred responses and lower scores to less preferred ones.

Over time, this helps the model generate responses that better match human preferences.

In the next article, we will explore how to train the model using this preference data.

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