Update README.md

README.md

@@ -1,22 +1,40 @@
 ---
 library_name: transformers
-license: mit
+license: apache-2.0
 base_model: intfloat/multilingual-e5-base
 tags:
 - generated_from_trainer
+- sentence-transformers
+- text-classification
+- feature-extraction
+- generated_from_trainer
+- legal
+- taxation
+- fiscalité
+- tax
 metrics:
 - accuracy
 model-index:
 - name: lemone-router
   results: []
+language:
+- fr
+pipeline_tag: text-classification
+datasets:
+- louisbrulenaudet/code-impots
+- louisbrulenaudet/code-impots-annexe-iv
+- louisbrulenaudet/code-impots-annexe-iii
+- louisbrulenaudet/code-impots-annexe-i
+- louisbrulenaudet/code-impots-annexe-ii
+- louisbrulenaudet/livre-procedures-fiscales
+- louisbrulenaudet/bofip
 ---
 
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
+<img src="assets/thumbnail.webp">
 
-# lemone-router
+# Lemone-Router: A Series of Fine-Tuned Classification Models for French Taxation
 
-This model is a fine-tuned version of [intfloat/multilingual-e5-base](https://huggingface.co/intfloat/multilingual-e5-base) on an unknown dataset.
+This model is a fine-tuned version of [intfloat/multilingual-e5-base](https://huggingface.co/intfloat/multilingual-e5-base).
 It achieves the following results on the evaluation set:
 - Loss: 0.4096
 - Accuracy: 0.9265
@@ -57,6 +75,11 @@ The following hyperparameters were used during training:
 | 0.1273        | 4.0   | 11236 | 0.3788          | 0.9187   |
 | 0.0525        | 5.0   | 14045 | 0.4096          | 0.9265   |
 
+### Training Hardware
+- **On Cloud**: No
+- **GPU Model**: 1 x NVIDIA H100 NVL
+- **CPU Model**: AMD EPYC 9V84 96-Core Processor
+- **RAM Size**: 314.68 GB
 
 ### Framework versions
 
@@ -64,3 +87,19 @@ The following hyperparameters were used during training:
 - Pytorch 2.4.1+cu121
 - Datasets 2.21.0
 - Tokenizers 0.20.1
+
+## Citation
+If you use this code in your research, please use the following BibTeX entry.
+
+```BibTeX
+@misc{louisbrulenaudet2024,
+  author =       {Louis Brulé Naudet},
+  title =        {Lemone-Embed: A Series of Fine-Tuned Embedding Models for French Taxation},
+  year =         {2024}
+  howpublished = {\url{https://huggingface.co/datasets/louisbrulenaudet/lemone-embed-pro}},
+}
+```
+
+## Feedback
+
+If you have any feedback, please reach out at [[email protected]](mailto:[email protected]).