We further establish SOCIAL IQA as a resource that enables transfer learning for other commonsense challenges, through sequential finetuning of a pretrained language model on SOCIAL IQA before other tasks.
we use SOCIAL IQA to set a new state-of-the-art on three commonsense challenge datasets: COPA (Roemmele et al., 2011) (83.4%), the original Winograd (Levesque, 2011) (72.5%), and the extended Winograd dataset from Rahman and Ng (2012) (84.0%).