|
--- |
|
license: mit |
|
datasets: |
|
- LennardZuendorf/legalis |
|
language: |
|
- de |
|
metrics: |
|
- accuracy |
|
library_name: transformers |
|
tags: |
|
- legal |
|
--- |
|
|
|
# Model description |
|
|
|
This is a BERT classifier, trained on a processed dataset of 2800 German court cases (see [legalis dataset](https://huggingface.co/datasets/LennardZuendorf/legalis)). It predicts the winner (defended/"Verklagt*r" or plaintiff/"Kläger*in") of a court case based on facts provided (in German). |
|
|
|
## Intended uses & limitations |
|
|
|
- This model was created as part of a university project and should be considered highly experimental. |
|
|
|
## get started with the model |
|
|
|
Try out the hosted Interference UI or the [Huggingface Space](https://huggingface.co/spaces/LennardZuendorf/legalis) |
|
|
|
# Model Card Authors |
|
|
|
This model card and the model itself are written by following authors: |
|
|
|
[@LennardZuendorf -HGF](https://huggingface.co/LennardZuendorf) |
|
[@LennardZuendorf - Github](https://github.com/LennardZuendorf) |
|
|
|
# Citation |
|
|
|
See Dataset for Sources and refer to [Github](https://github.com/LennardZuendorf/uniArchive-legalis) for the collection of all files. |
