Update README.md

README.md

@@ -41,14 +41,11 @@ language:
 should probably proofread and complete it, then remove this comment. -->
 
 # roberta-base-NER
+## Model description
 
-This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the xtreme dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.2935
-- Precision: 0.8004
-- Recall: 0.8111
-- F1: 0.8057
-- Accuracy: 0.9194
+**xlm-roberta-base-multilingual-cased-ner** is a **Named Entity Recognition** model based on a fine-tuned XLM-RoBERTa base model. 
+It has been trained to recognize three types of entities: location (LOC), organizations (ORG), and person (PER). 
+Specifically, this model is a *XLMRoreberta-base-multilingual-cased* model that was fine-tuned on an aggregation of 10 high-resourced languages.
 
 ## Intended uses & limitations
 
@@ -70,6 +67,16 @@ ner_results = nlp(example)
 print(ner_results)
 ```
 
+Abbreviation|Description
+-|-
+O|Outside of a named entity
+B-PER |Beginning of a person’s name right after another person’s name
+I-PER |Person’s name
+B-ORG |Beginning of an organisation right after another organisation
+I-ORG |Organisation
+B-LOC |Beginning of a location right after another location
+I-LOC |Location
+
 ### Training hyperparameters
 
 The following hyperparameters were used during training: