Direct Preference Optimization for Chatbot Fine-Tuning: An Empirical Study

In three linesEmpirical study on Direct Preference Optimization (DPO) for chatbot fine-tuning. Results show DPO simplifies the training pipeline, improves computational efficiency, and achieves competitive performance. Evaluation using BLEU, ROUGE, and cosine similarity metrics demonstrates effective learning and convergence, though training instability remains.

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