Learning to Rank for Plausible Plausibility
Table 3: Experimental results on COPA test set.
['Method', 'Acc (%)']
Compared with previous state-of-the-art knowledge-driven baseline methods, a BERT model trained with a log-loss achieves better performance. When training the BERT model with a margin-loss instead of a log-loss, our method gets the new state-of-the-art result on the established COPA splits, with an accuracy of 75.4%.