MLQA
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Question Answering | MLQA (test) | F1 Score76.2 | 35 | |
| Cross-lingual Question Answering | MLQA v1.0 (test) | F1 (es)75.1 | 34 | |
| Question Answering | MLQA | F1 Score76.9 | 10 | |
| Performance Prediction | MLQA | MAE2.21 | 9 | |
| Zero-shot performance prediction | MLQA | MAE2.42 | 9 | |
| Cross-lingual Question Answering | MLQA | F1 (en)84.5 | 8 | |
| Question Answering | MLQA G-XLT v1.0 (test) | Avg Score67.7 | 8 | |
| Extractive Question Answering | MLQA Chinese (test) | BERTScore F171.28 | 7 | |
| Extractive Question Answering | MLQA Arabic (test) | BERTScore F186.18 | 7 | |
| Commonsense Knowledge | MLQA Zh | Accuracy47.2 | 6 | |
| Question Answering | MLQA German (de) | F1 Score65.81 | 5 | |
| Question Answering | MLQA English (en) | F1 Score84.32 | 5 | |
| Machine Reading Comprehension | MLQA Target - English v1.0 (test) | EM (German)26.59 | 4 | |
| Machine Reading Comprehension | MLQA English - Target v1.0 (test) | German EM31.28 | 4 |
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