Attention Is All You Need for Chinese Word Segmentation
Table 7: F1 scores on models removing different components from GD-Transformer.
['GD-Transformer', '[BOLD] PKU 95.4', '[BOLD] PKU', '[BOLD] MSR 97.6', '[BOLD] MSR']
The results show that our full model GD-Transformer significantly outperforms the original Transformer by a large performance margin. Removing either Gaussian mask or directional mask will put negative impact over the performance of our model, which shows that both masks are indispensably necessary for our model performance.