Variational Neural Machine Translation with Normalizing Flows
Table 3: Results of different dropout rate for IWSLT and WMT setup. The best results are in bold.
['Dropout rate', '0.0', '0.1', '0.2', '0.3']
As shown, word dropout is important for both setup but it is more so for IWSLT. It seems that tasks with low resources benefit more from word dropout. We also observe that above certain rate, word dropout hurts the performance.