Multi-Perspective Context Matching for Machine Comprehension
Table 4: Layer ablation on the dev set.
['Models', 'EM', 'F1']
In this sub-section, we evaluate the effectiveness of various layers in our MPCM model. We built several layer ablation models by removing one layer at a time. For the Multi-Perspective Context Matching Layer, we cannot remove it entirely. Instead, we built three models (w/o Full-Matching, w/o Maxpooling-Matching, w/o Meanpooling-Matching) by eliminating each matching strategy individually. We can see that removing any components from the MPCM model decreases the performance significantly. Among all the layers, the Aggregation Layer is the most crucial layer. Among all the matching strategies, Maxpooling-Matching has the biggest effect.