Create README.md

README.md

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+---
+datasets:
+- rcds/MultiLegalNeg
+language:
+- de
+- fr
+- it
+- en
+tags:
+- legal
+---
+# Model Card for joelito/legal-swiss-longformer-base
+
+This model is based on [XLM-R-Base](https://huggingface.co/xlm-roberta-base). 
+It was pretrained on negation scope resolution using [NegBERT](https://github.com/adityak6798/Transformers-For-Negation-and-Speculation/blob/master/Transformers_for_Negation_and_Speculation.ipynb) ([Khandelwal and Sawant 2020](https://arxiv.org/abs/1911.04211))
+For training we used the [Multi Legal Neg Dataset](https://huggingface.co/datasets/rcds/MultiLegalNeg), a multilingual dataset of legal data annotated for negation cues and scopes, ConanDoyle-neg ([
+Morante and Blanco. 2012](https://aclanthology.org/S12-1035/)), SFU Review ([Konstantinova et al. 2012](http://www.lrec-conf.org/proceedings/lrec2012/pdf/533_Paper.pdf)), BioScope ([Szarvas et al. 2008](https://aclanthology.org/W08-0606/)) and Dalloux ([Dalloux et al. 2020](https://clementdalloux.fr/?page_id=28)).
+
+## Model Details
+
+### Model Description
+
+- **Model type:** Transformer-based language model (XLM-R-base)
+- **Languages:** de, fr, it, en
+- **License:** CC BY-SA
+- **Finetune Task:** Negation Scope Resolution
+
+## Uses
+
+See [LegalNegBERT](https://github.com/RamonaChristen/Multilingual_Negation_Scope_Resolution_on_Legal_Data/blob/main/LegalNegBERT) for details on the training process and how to use this model. 
+
+### Recommendations
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model.
+
+
+### Training Data
+
+This model was pretrained on the [Multi Legal Neg Dataset](https://huggingface.co/datasets/rcds/MultiLegalNeg)
+
+## Evaluation
+
+We evaluate neg-xlm-roberta-base on the test sets in the [Multi Legal Neg Dataset](https://huggingface.co/datasets/rcds/MultiLegalNeg).
+| \_Test Dataset             | F1-score | 
+| :------------------------- | :-------- | 
+| fr                         | 92.49     |
+| it                         | 88.81     |
+| de (DE)                    | 95.66     |
+| de (CH)                    | 87.82     |
+| SFU Review                 | 88.53     |
+| ConanDoyle-neg             | 90.47     |
+| BioScope                   | 95.59     |
+| Dalloux                    | 93.99     |
+
+```
+#### Software
+
+pytorch, transformers.
+
+## Citation
+
+```
+TBD
+```