Update README.md

README.md

@@ -17,24 +17,24 @@ widget:
 - text: "Assurés de disputer l'Euro 2024 en Allemagne l'été prochain (du 14 juin au 14 juillet) depuis leur victoire aux Pays-Bas, les Bleus ont fait le nécessaire pour avoir des certitudes. Avec six victoires en six matchs officiels et un seul but encaissé, Didier Deschamps a consolidé les acquis de la dernière Coupe du monde. Les joueurs clés sont connus : Kylian Mbappé, Aurélien Tchouameni, Antoine Griezmann, Ibrahima Konaté ou encore Mike Maignan."
 library_name: transformers
 pipeline_tag: token-classification
-co2_eq_emissions: 35
+co2_eq_emissions: 20
 ---
 
 
-# Camembert-base-frenchNER_3entities
+# Camembert-base-frenchNER_4entities
 
 ## Model Description
 
 We present **Camembert-base-frenchNER_4entities**, which is a [CamemBERT base](https://huggingface.co/camembert-base) fine-tuned for the Name Entity Recognition task for the French language on four French NER datasets for 4 entities (LOC, PER, ORG, MISC).  
 All these datasets were concatenated and cleaned into a single dataset that we called [frenchNER_4entities](https://huggingface.co/datasets/CATIE-AQ/frenchNER_4entities).  
-There are a total of **384,773** rows, of which **328,757** are for training, **24,131** for validation and **31,885** for testing.
+There are a total of **384,773** rows, of which **328,757** are for training, **24,131** for validation and **31,885** for testing.  
 Our methodology is described in a blog post available in [English](https://blog.vaniila.ai/en/NER_en/) or [French](https://blog.vaniila.ai/NER/).
 
 
 
 ## Dataset
 
-The dataset used is [frenchNER](https://huggingface.co/datasets/CATIE-AQ/frenchNER_4entities), which represents ~385k sentences labeled in 4 categories :
+The dataset used is [frenchNER_4entities](https://huggingface.co/datasets/CATIE-AQ/frenchNER_4entities), which represents ~385k sentences labeled in 4 categories :
 * PER: personality ;
 * LOC: location ;
 * ORG: organization ;