Update README.md

README.md

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 library_name: transformers
 tags:
 - legal
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+---
+
+<h1> Legalis BERT Model </h1>
+
+<h2> Model Details </h2>
+
+<h3> Model Description </h3>
+
+This is a court case prediction model build for a university course, this particular one utalises text classification with 
+
+- **Developed by:** Lennard Zündorf
+- **Model type:** transformer-based
+- **Language(s) (NLP):** German 
+- **Finetuned from model :** [German BERT/ gbert-base](https://huggingface.co/deepset/gbert-base)
+
+<h3> Model Sources </h3>
+
+- **Repository:** [GitHub](https://github.com/LennardZuendorf/legalis)
+- **Demo:** on [Huggingface](https://huggingface.co/spaces/LennardZuendorf/legalis)
+
+<h2> Uses </h2>
+
+You can use this model to try and predict the outcome of a court case based on the legal facts.
+
+<h2> Training Details </h2>
+
+<h3>Training Data
+
+This model uses the similarly named [dataset](https://huggingface.co/models?dataset=dataset:LennardZuendorf/legalis)
+
+<h3> Testing Data & Metrics
+
+<h4> Metrics </h4>
+
+There has not been any testing yet.
+
+<h3> Results </h3>
+
+The accuracy score against the testing split is as high as 0.60