Calibrate Before Use: Improving Few-Shot Performance of Language Models
Introduction In the rapidly evolving field of artificial intelligence, language models have become indispensable tools across various applications. However, even the most sophisticated models require fine-tuning to perform optimally in real-world scenarios. Calibration plays a crucial role in this process, particularly in the context of few-shot learning. Calibration ensures that the predictions made by a […]
