Update README.md

README.md

@@ -1,12 +1,13 @@
 ---
 license: cc-by-4.0
 ---
+# NER-fine-tuned-BETO: model fine-tuned from BETO for NER task.
 ---
-language: es
-datasets:
+Language: es
+Datasets:
 - conll2002
 - Babelscape/wikineural
-# NER-fine-tuned-BETO: model fine-tuned from BETO for NER task.
+
 ## Introduction
 [NER-fine-tuned-BETO] is a NER model that was fine-tuned from BETO on the 2002 Conll and the WikiNEuRal spanish datasets.
 Model was trained on the Conll 2002 train dataset (~8320 sentences) and a bootstrapped dataset of WikiNEuRal, where we re-evaluate the dataset and only keep the sentences where all the labels matched the predictions made.
@@ -23,10 +24,12 @@ ORG |Organization
 LOC |Location
 
 Alongside the IOB formatting, this is:
-  . B-LABEL if the word is at the beggining of the entity.
-  . I-LABEL if the word is part of the entity name, but not the first word.
+  - B-LABEL if the word is at the beggining of the entity.
+  - I-LABEL if the word is part of the entity name, but not the first word.
+  
 ## How to use NER-fine-tuned-BETO with HuggingFace
-##### Load the model and its tokenizer :
+Load the model and its tokenizer :
+
 ```python
 from transformers import AutoTokenizer, AutoModelForTokenClassification
 
@@ -48,7 +51,7 @@ nlp('Ignacio se fue de viaje por Buenos aires')
   'end': 40}]
 
 ```
-## Model performances
+## Model Performance
 Overall
 | precision | recall | f1-score |
 |-----------|--------|----------|