📊 Showing 6 results | 📏 Metric: EM
| Rank | Model | Paper | EM | Date | Code |
|---|---|---|---|---|---|
| 1 | CamemBERT-Large | FQuAD: French Question Answering Dataset | 92.20 | 2020-02-14 | - |
| 2 | XLM-RoBERTa-Large | FQuAD: French Question Answering Dataset | 89.50 | 2020-02-14 | - |
| 3 | CamemBERT-Base | FQuAD: French Question Answering Dataset | 88.40 | 2020-02-14 | - |
| 4 | Camembert-Base-SquadFR-Fquad-Piaf 📚 | Project PIAF: Building a Native French Question-Answering Dataset | 88.40 | 2020-07-02 | 📦 etalab/piaf |
| 5 | XLM-RoBERTa-Base | FQuAD: French Question Answering Dataset | 85.90 | 2020-02-14 | - |
| 6 | LePetit | On the importance of pre-training data volume for compact language models | 70.71 | 2020-10-08 | - |