Pre-Trained and Attention-Based Neural Networks for Building Noetic Task-Oriented Dialogue Systems
Table 7: Ablation results for a single model on the validation set of subtask 4.
['[EMPTY]', '1-Scaled VI', 'ARI', 'F1', 'recall', 'precision']
After we combine feature such as user and time etc. , our model could achieve the further improvement, which indicates that manual feature still could capture some information that BERT could not capture. Even though we use the state-of-art model BERT with pre-training method, our model could only reach 46.3% F1 score, which indicates that the disentangling problem is still a hard problem to solve.