Update README.md

README.md

@@ -4,4 +4,13 @@ task_categories:
 - text-classification
 language:
 - en
----
+---
+
+- 36.528 English texts in  total, 12.955 NOT offensive and 23.573O OFFENSIVE texts
+- All duplicate values were removed
+- Split using sklearn into 80% train and 20% temporary test (stratified label). Then split the test set using 0.50% test and validation (stratified label)
+- Split: 80/10/10
+- Train set label distribution: 0 ==> 10.364, 1 ==> 18.858
+- Validation set label distribution: 0 ==> 1.296, 1 ==> 2.357
+- Test set label distribution: 0 ==> 1.295, 1 ==> 2.358
+- The OLID dataset and the labels "Offensive" and "Neither" from the paper's dataset "Automated Hate Speech Detection and the Problem of Offensive Language" (Davidson et al.,2017)