In the previous article, we explored the part where we collect human preferences. In this article, we...
In the previous article, we explored the part where we collect human preferences. In this article, we will see how to use this data to train the models.
To train a model that gives higher scores to preferred responses, we first make a copy of the model that has already gone through supervised fine-tuning.
Modifying the Model
Next, we modify this copied model.
We remove the unembedding layer, which normally predicts the next token, and replace it with a single output value.
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