Update README.md

README.md

@@ -15,13 +15,13 @@ Model was evaluated on the test dataset of Conll2002.
 
 ## Training data
 Training data was classified as follow:
-Abbreviation|Description
--|-
-O |Outside of a named entity
-MISC |Miscellaneous entity
-PER |Person’s name
-ORG |Organization
-LOC |Location
+|Abbreviation|  Description  |
+|:----------:|:-------------:|
+|     O      | Outside of NE |
+|    PER     | Person’s name |
+|    ORG     | Organization  |
+|    LOC     |  Location     |
+|   MISC     | Miscellaneous |
 
 Alongside the IOB formatting, this is:
   - B-LABEL if the word is at the beggining of the entity.
@@ -54,18 +54,18 @@ nlp('Ignacio se fue de viaje por Buenos aires')
 ## Model Performance
 Overall
 | precision | recall | f1-score |
-|-----------|--------|----------|
+|:---------:|:------:|:--------:|
 | 0.9833    | 0.8950 | 0.8998   |
 
 By classes
-| class  | precision\| | recall | f1-score |
-|--------|-------------|--------|----------|
-| O      | 0.9958      | 0.9965 | 0.99     |
-| B-PER  | 0.9572      | 0.9741 | 0.9654   |
-| I-PER  | 0.9487      | 0.9921 | 0.9699   |
-| B-ORG  | 0.8823      | 0.9264 | 0.9038   |
-| I-ORG  | 0.9253      | 0.9264 | 0.9117   |
-| B-LOC  | 0.8967      | 0.8736 | 0.8850   |
-| I-LOC  | 0.8870      | 0.8215 | 0.8530   |
-| B-MISC | 0.7541      | 0.7964 | 0.7747   |
-| I-MISC | 0.9026      | 0.7827 | 0.8384   |
+| class  | precision | recall | f1-score |
+|:------:|:---------:|:------:|:--------:|
+| O      | 0.9958    | 0.9965 | 0.990    |
+| B-PER  | 0.9572    | 0.9741 | 0.9654   |
+| I-PER  | 0.9487    | 0.9921 | 0.9699   |
+| B-ORG  | 0.8823    | 0.9264 | 0.9038   |
+| I-ORG  | 0.9253    | 0.9264 | 0.9117   |
+| B-LOC  | 0.8967    | 0.8736 | 0.8850   |
+| I-LOC  | 0.8870    | 0.8215 | 0.8530   |
+| B-MISC | 0.7541    | 0.7964 | 0.7747   |
+| I-MISC | 0.9026    | 0.7827 | 0.8384   |