 Norwegian Evaluation  We use the test split of the machine translated version of the [MultiNLI](https://cims.nyu.edu/~sbowman/multinli/) dataset to evaluate the Norwegian performance of the models.  We acknowledge that not evaluating on a gold standard dataset is not ideal, but unfortunately we are not aware of any NLI datasets in Norwegian.  | **Model** | **MCC** | **Macro-F1** | **Accuracy** | **Number of Parameters** | | :-------- | :------------ | :--------- | :----------- | :----------- | | [`alexandrainst/scandi-nli-large`](https://huggingface.co/alexandrainst/scandi-nli-large) | **70.61%** | **80.43%** | **80.36%** | 354M | | [`joeddav/xlm-roberta-large-xnli`](https://huggingface.co/joeddav/xlm-roberta-large-xnli) | 67.99% | 78.68% | 78.60% | 560M | | [`alexandrainst/scandi-nli-base`](https://huggingface.co/alexandrainst/scandi-nli-base) | 67.53% | 78.24% | 78.33% | 178M | | [`MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7`](https://huggingface.co/MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7) | 65.33% | 76.73% | 76.65% | 279M | | [`MoritzLaurer/mDeBERTa-v3-base-mnli-xnli`](https://huggingface.co/MoritzLaurer/mDeBERTa-v3-base-mnli-xnli) | 65.18% | 76.76% | 76.77% | 279M | | [`NbAiLab/nb-bert-base-mnli`](https://huggingface.co/NbAiLab/nb-bert-base-mnli) | 63.51% | 75.42% | 75.39% | 178M | | `alexandrainst/scandi-nli-small` (this) | 58.42% | 72.22% | 72.30% | **22M** |   