Auditing Preference Biases and Fine-Tuning Language Models with Direct Preference Optimization on Anthropic HH-RLHF Using TRL and LoRA

In this tutorial, we design an end-to-end preference-learning workflow using the Anthropic HH-RLHF dataset and Direct Preference Optimization (DPO). We begin by preparing a robust Colab environment, loading and parsing chosen–rejected response pairs, and auditing the dataset for structural and length-based preference biases. We then run lexical... Weiterlesen