add stats to README

README.md

@@ -27,6 +27,21 @@ Our dataset treats ''unfair contractual term'' as the equivalent of an abusive c
 
 On the EU and at the national such as the Polish levels, agencies cannot check possible agreements by hand. Hence, we took the first step to evaluate the possibility of accelerating this process. We created a dataset and machine learning models to automate potentially abusive clauses detection partially. Consumer protection organizations and agencies can use these resources to make their work more effective and efficient. Moreover, consumers can automatically analyze contracts and understand what they agree upon.
 
+## Data splits
+
+| Subset      | Cardinality (sentences) |
+| ----------- | ----------------------: |
+| train       | 4284                    |
+| dev         | 1519                    |
+| test        | 3453                    |
+
+## Class distribution
+
+| Class                           |   train |          dev |   test |
+|:--------------------------------|--------:|-------------:|-------:|
+| BEZPIECZNE_POSTANOWIENIE_UMOWNE |  0.5458 |       0.3002 | 0.6756 |
+| KLAUZULA_ABUZYWNA               |  0.4542 |       0.6998 | 0.3244 |
+
 ## License
 
 [Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)](https://creativecommons.org/licenses/by-nc-sa/4.0/)