An End-to-End Dialogue State Tracking System withMachine Reading Comprehension and Wide & Deep Classification
Table 3: Slot tagging F1-score for span-based slots
['[EMPTY]', 'Development', 'Test']
We perform experiments on TPU v3 using the XLNet large model and using the same experimental parameters as \citeauthoryang2019xlnet \shortciteyang2019xlnet. On the development dataset, we get 0.9889 slot tagging F1-score. Because there are some services only appear in the development and test dataset, such as “Alarm”, we use the development dataset as a supplement and achieve the best slot tagging F1-score of 0.9835 on the test dataset.