How Can We Know What Language Models Know?
Table 14: Micro-averaged accuracy (%) before and after LM-aware prompt fine-tuning.
['[BOLD] Prompts', '[BOLD] Top1', '[BOLD] Top3', '[BOLD] Top5', '[BOLD] Opti.', '[BOLD] Oracle']
After fine-tuning, the oracle performance increased significantly, while the ensemble performances (both rank-based and optimization-based) dropped slightly. This indicates that LM-aware fine-tuning has the potential to discover better prompts, but some portion of the refined prompts may have over-fit to the training set upon which they were optimized.