Update README.md

README.md

@@ -74,9 +74,11 @@ We report Matthew's Correlation Coefficient (MCC), macro-average F1-score as wel
 | **Model** | **MCC** | **Macro-F1** | **Accuracy** | **Number of Parameters** |
 | :-------- | :------------ | :--------- | :----------- | :----------- |
 | [`alexandrainst/scandi-nli-large`](https://huggingface.co/alexandrainst/scandi-nli-large) | **73.80%** | **58.41%** | **86.98%** | 354M |
+| [`MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7`](https://huggingface.co/MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7) | 68.37% | 57.10% | 83.25% | 279M |
 | `alexandrainst/scandi-nli-base` (this) | 62.44% | 55.00% | 80.42% | 178M |
-| [`alexandrainst/scandi-nli-small`](https://huggingface.co/alexandrainst/scandi-nli-small) | 47.28% | 48.88% | 73.46% | **22M** |
+| [`MoritzLaurer/mDeBERTa-v3-base-mnli-xnli`](https://huggingface.co/MoritzLaurer/mDeBERTa-v3-base-mnli-xnli) | 52.79% | 52.00% | 72.35% | 279M |
 | [`joeddav/xlm-roberta-large-xnli`](https://huggingface.co/joeddav/xlm-roberta-large-xnli) | 49.18% | 50.31% | 69.73% | 560M |
+| [`alexandrainst/scandi-nli-small`](https://huggingface.co/alexandrainst/scandi-nli-small) | 47.28% | 48.88% | 73.46% | **22M** |
 
 
 ## Training procedure