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Thus, we conclude that the Enhanced Joint BERT-primarily based fashions, especially the BERTje and mBERT variants, can be utilized as sturdy baselines for the joint text classification and slot filling duties for the traffic event detection drawback in Belgium and within the Brussels capital area.
Hence, cross-domain slot filling has naturally arisen to cope with this knowledge scarcity drawback. Table 2 studies the performance of the totally different models for the tasks of textual content classification and slot filling on the BRU and the BE datasets, the place the 2 duties are considered independently.
CRF model outperforms all the opposite fashions on both datasets, and the score is 98.18% on the BRU dataset and 97.22% on the BE dataset. The BERT-primarily based fashions perform higher or on par with the non-BERT-based mostly fashions on both datasets. FLOATSUBSCRIPT rating of round 96%.
On both datasets, the BERT-based mostly fashions can carry out on par with the non-BERT-based mostly fashions. That method, it is able to outperform all the opposite LSTM-based mostly fashions and perform on par with the Joint BERT-primarily based models. The Enhanced Joint BERT-based mostly fashions acquire the best generalization efficiency not solely in comparison with the Joint BERT-based mostly fashions, but in addition to the opposite models proposed for fixing the task.