Distance-based Self-Attention Network for Natural Language Inference
Table 1: Experimental results of different models on SNLI data. | θ| : number of parameters (excluding word embedding part). T(s)/epoch : average training time (second) per epoch.
['[BOLD] Model Name', '|\xa0 [ITALIC] θ|', '[BOLD] T(s)/epoch', '[BOLD] Train Acc(%)', '[BOLD] Test Acc(%)']
We also looked at the model with distance mask removed to verify the effect of the distance mask proposed in this paper. Results show that the addition of the distance mask improved the performance without significantly affecting the training time or increasing the number of parameters.