An Empirical Study of Pre-trained Model Selection for Out-of-Distribution Generalization and Calibration

Hiroki Naganuma, Ryuichiro Hataya, Kotaro Yoshida +1

In the field of computer vision, fine-tuning pre-trained models has become a prevalent strategy for out-of-distribution (OOD) generalization tasks. Different from most prior work t…