Update README.md

README.md

@@ -121,7 +121,7 @@ If we do not filter out instances, predicted with lower confidence score, the mo
 
 ## Intended use and limitations
 
-For reliable results, the classifier should be applied to documents of sufficient length (the rule of thumbs is at least 75 words).
+For reliable results, the classifier should be applied to documents of sufficient length (the rule of thumb is at least 75 words).
 
 
 Use example:
@@ -154,7 +154,8 @@ for result in results:
 
 The classifier uses the top-level of the [IPTC Media Topic NewsCodes](https://iptc.org/std/NewsCodes/guidelines/#_what_are_the_iptc_newscodes) schema, consisting of 17 labels.
 
-List of labels:
+### List of labels
+
 ```
 labels_list=['education', 'human interest', 'society', 'sport', 'crime, law and justice',
 'disaster, accident and emergency incident', 'arts, culture, entertainment and media', 'politics',
@@ -167,7 +168,7 @@ labels_map={0: 'education', 1: 'human interest', 2: 'society', 3: 'sport', 4: 'c
 11: 'health', 12: 'labour', 13: 'religion', 14: 'weather', 15: 'environment', 16: 'conflict, war and peace'}
 ```
 
-Description of labels:
+### Description of labels
 
 The descriptions of the labels are based on the descriptions provided in the [IPTC Media Topic NewsCodes schema](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html)
 and enriched with information which specific subtopics belong to the top-level topics, based on the IPTC Media Topic label hierarchy.
@@ -250,7 +251,7 @@ When we remove instances predicted with lower confidence (229 instances - 20%),
 | Slovenian     |   0.835443  |   0.783873 |   237 |
 | Greek     |   0.84188 |   0.785525 |   234 |
 
-### Fine-tuning hyperparameters
+## Fine-tuning hyperparameters
 
 Fine-tuning was performed with `simpletransformers`. 
 Beforehand, a brief hyperparameter optimization was performed and the presumed optimal hyperparameters are: