We study model reusability evaluation (MRE) for source pre-trained models: evaluating their transfer learning performance to new target tasks. In special, we focus on the setting under which the target training datasets are small, making it difficult to produce reliable MRE scores using them. Under this situation, we propose synergistic learning for building the task-model metric, which can be realized by collecting a set of pre-trained models and asking a group of data providers to participate.…