Fast Reading Comprehension with ConvNets
Table 5: TriviaQA Performance. The scores are multiplied by 100. ∗Doc QA (Clark & Gardner, 2017) uses a different training strategy on the whole training set (containing 529K question-answer-evidence tuples), while we follow Joshi et al. (2017) training on only the first 80K question-answer-evidence tuples in the training set.
['Dataset', 'Model', 'Full EM', 'Full F1', 'Verified EM', 'Verified F1']
On Wikipedia split of TriviaQA, our proposed Conv DrQA is slight worse than our DrQA baseline which beats all previous models, it can still be on a par with the previous state-of-the-art performance of recurrent networks. The numbers are shown in