The Evolution of Reinforcement Fine-Tuning in AI
The Data Exchange with Ben Lorica
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Reinforcement Fine-Tuning in NLP
This chapter explores entity extraction in natural language processing, focusing on the advantages of reinforcement fine-tuning (RFT) over supervised fine-tuning (SFT). It discusses methods for assessing model performance and the challenges of grading accuracy, emphasizing automated solutions to enhance extraction tasks while mitigating hallucination issues.
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