Attention-over-Attention Neural Networks for Reading Comprehension
Table 3: Embedding and hidden layer dimensions for each task.
['[EMPTY]', 'Embed. # units', 'Hidden # units']
In re-ranking step, we generate 5-best list from the baseline neural network model, as we did not observe a significant variance when changing the N-best list size. All language model features are trained on the training proportion of each dataset, with 8-gram word-based setting and Kneser-Ney smoothing Kneser and Ney The results are reported with the best model, which is selected by the performance of validation set. The ensemble model is made up of four best models, which are trained using different random seed.