BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions
Table 4: Test set results on BoolQ, “+MultiNLI” indicates models that were additionally pre-trained on MultiNLI before being fine-tuned on the train set.
['Model', 'Dev Acc.', 'Test Acc.']
For these results we train five versions of each model using different training seeds, and show the model that had the best dev-set performance.