Update README.md

README.md

@@ -77,12 +77,13 @@ The Scandinavian scores are the average of the Danish, Swedish and Norwegian sco
 
 | **Model** | **MCC** | **Macro-F1** | **Accuracy** | **Number of Parameters** |
 | :-------- | :------------ | :--------- | :----------- | :----------- |
-| [`alexandrainst/scandi-nli-large`](https://huggingface.co/alexandrainst/scandi-nli-large) | asd | asd | asd | 354M |
-| [`MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7`](https://huggingface.co/MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7) | asd | asd | asd | 279M |
-| [`alexandrainst/scandi-nli-base`](https://huggingface.co/alexandrainst/scandi-nli-base) | asd | asd | asd | 178M |
+| [`alexandrainst/scandi-nli-large`](https://huggingface.co/alexandrainst/scandi-nli-large) | **73.70** | **74.44** | **83.91** | 354M |
+| [`MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7`](https://huggingface.co/MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7) | 69.01% | 71.99% | 80.66% | 279M |
+| [`alexandrainst/scandi-nli-base`](https://huggingface.co/alexandrainst/scandi-nli-base) | 67.42% | 71.54% | 80.09% | 178M |
+| [`joeddav/xlm-roberta-large-xnli`](https://huggingface.co/joeddav/xlm-roberta-large-xnli) | 64.17% | 70.80% | 77.29% | 560M |
 | [`MoritzLaurer/mDeBERTa-v3-base-mnli-xnli`](https://huggingface.co/MoritzLaurer/mDeBERTa-v3-base-mnli-xnli) | 63.94% | 70.41% | 77.23% | 279M |
-| [`joeddav/xlm-roberta-large-xnli`](https://huggingface.co/joeddav/xlm-roberta-large-xnli) | asd | asd | asd | 560M |
-| `alexandrainst/scandi-nli-small` (this) | asd | asd | asd | **22M** |
+| [`NbAiLab/nb-bert-base-mnli`](https://huggingface.co/NbAiLab/nb-bert-base-mnli) | 61.71% | 68.36% | 76.08% | 178M |
+| `alexandrainst/scandi-nli-small` (this) | 56.02% | 65.30% | 73.56% | **22M** |
 
 
 ### Danish Evaluation
@@ -96,6 +97,7 @@ We use a test split of the [DanFEVER dataset](https://aclanthology.org/2021.noda
 | [`alexandrainst/scandi-nli-base`](https://huggingface.co/alexandrainst/scandi-nli-base) | 62.44% | 55.00% | 80.42% | 178M |
 | [`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 |
+| [`NbAiLab/nb-bert-base-mnli`](https://huggingface.co/NbAiLab/nb-bert-base-mnli) | 56.92% | 53.25% | 76.39% | 178M |
 | `alexandrainst/scandi-nli-small` (this) | 47.28% | 48.88% | 73.46% | **22M** |
 
 
@@ -107,12 +109,13 @@ We acknowledge that not evaluating on a gold standard dataset is not ideal, but
 
 | **Model** | **MCC** | **Macro-F1** | **Accuracy** | **Number of Parameters** |
 | :-------- | :------------ | :--------- | :----------- | :----------- |
-| [`alexandrainst/scandi-nli-large`](https://huggingface.co/alexandrainst/scandi-nli-large) | asd | asd | asd | 354M |
-| [`alexandrainst/scandi-nli-base`](https://huggingface.co/alexandrainst/scandi-nli-base) | asd | asd | asd | 178M |
+| [`alexandrainst/scandi-nli-large`](https://huggingface.co/alexandrainst/scandi-nli-large) | **76.69%** | **84.47%** | **84.38%** | 354M |
+| [`joeddav/xlm-roberta-large-xnli`](https://huggingface.co/joeddav/xlm-roberta-large-xnli) | 75.35% | 83.42% | 83.55% | 560M |
 | [`MoritzLaurer/mDeBERTa-v3-base-mnli-xnli`](https://huggingface.co/MoritzLaurer/mDeBERTa-v3-base-mnli-xnli) | 73.84% | 82.46% | 82.58% | 279M |
 | [`MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7`](https://huggingface.co/MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7) | 73.32% | 82.15% | 82.08% | 279M |
-| [`joeddav/xlm-roberta-large-xnli`](https://huggingface.co/joeddav/xlm-roberta-large-xnli) | asd | asd | asd | 560M |
-| `alexandrainst/scandi-nli-small` (this) | asd | asd | asd | **22M** |
+| [`alexandrainst/scandi-nli-base`](https://huggingface.co/alexandrainst/scandi-nli-base) | 72.29% | 81.37% | 81.51% | 178M |
+| [`NbAiLab/nb-bert-base-mnli`](https://huggingface.co/NbAiLab/nb-bert-base-mnli) | 64.69% | 76.40% | 76.47% | 178M |
+| `alexandrainst/scandi-nli-small` (this) | 62.35% | 74.79% | 74.93% | **22M** |
 
 
 ### Norwegian Evaluation
@@ -123,13 +126,13 @@ We acknowledge that not evaluating on a gold standard dataset is not ideal, but
 
 | **Model** | **MCC** | **Macro-F1** | **Accuracy** | **Number of Parameters** |
 | :-------- | :------------ | :--------- | :----------- | :----------- |
-| [`alexandrainst/scandi-nli-large`](https://huggingface.co/alexandrainst/scandi-nli-large) | asd | asd | asd | 354M |
+| [`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 |
-| [`alexandrainst/scandi-nli-base`](https://huggingface.co/alexandrainst/scandi-nli-base) | asd | asd | asd | 178M |
-| [`NbAiLab/nb-bert-base-mnli`](https://huggingface.co/NbAiLab/nb-bert-base-mnli) | asd | asd | asd | 178M |
 | [`MoritzLaurer/mDeBERTa-v3-base-mnli-xnli`](https://huggingface.co/MoritzLaurer/mDeBERTa-v3-base-mnli-xnli) | 65.18% | 76.76% | 76.77% | 279M |
-| [`joeddav/xlm-roberta-large-xnli`](https://huggingface.co/joeddav/xlm-roberta-large-xnli) | asd | asd | asd | 560M |
-| `alexandrainst/scandi-nli-small` (this) | asd | asd | asd| **22M** |
+| [`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** |
 
 
 ## Training procedure