Question Answering On Obqa
Métriques
Accuracy
Résultats
Résultats de performance de divers modèles sur ce benchmark
Tableau comparatif
| Nom du modèle | Accuracy |
|---|---|
| llama-open-and-efficient-foundation-language-1 | 57.2 |
| llama-open-and-efficient-foundation-language-1 | 56.4 |
| finetuned-language-models-are-zero-shot | 78.2 |
| palm-scaling-language-modeling-with-pathways-1 | 53.4 |
| finetuned-language-models-are-zero-shot | 78.4 |
| palm-scaling-language-modeling-with-pathways-1 | 50.4 |
| language-models-are-few-shot-learners | 57.6 |
| llama-open-and-efficient-foundation-language-1 | 60.2 |
| llama-open-and-efficient-foundation-language-1 | 58.6 |