Machine Reading Comprehension on UIT-ViQuAD 2.0
75.5EMHuman
Evaluation results
| Method | Links | ||
|---|---|---|---|
| Human2024.03 | 75.5 | 82.85 | |
| CafeBERTLanguage Type=Monolingual2024.03 | 65.25 | 76.36 | |
| XLM-RobertalargeLanguage Type=Multilingual, Model Variant=Large2024.03 | 64.71 | 75.36 | |
| PhoBERTlargeLanguage Type=Monolingual, Model Variant=Large2024.03 | 57.27 | 70.88 | |
| mBERTLanguage Type=Multilingual2024.03 | 52.34 | 63.71 | |
| PhoBERTbaseLanguage Type=Monolingual, Model Variant=Base2024.03 | 51 | 64.29 | |
| XLM-RobertabaseLanguage Type=Multilingual, Model Variant=Base2024.03 | 50.49 | 59.23 | |
| wikiBERTLanguage Type=Monolingual2024.03 | 42.16 | 52.62 | |
| DistilBERTLanguage Type=Multilingual2024.03 | 35.78 | 53.83 |