Understanding Image and Text Simultaneously: a Dual Vision-Language Machine Comprehension Task
Table 4: The impact of model sizes on MCIC-COCOaccuracy for the FFNN model.
['dim', 'hidden-1', 'hidden-2', 'Dev', 'Test']
For the FFNN models, contrary to expectations, bigger network sizes leads to decreasing accuracy. On the other hand, for Vec2seq+FFNNmodels, accuracy increases with increased size in model parameters, up until the embedding dimension of the RNN model matches the embedding dimension of the Inception model, at 2048.