Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
json
Languages:
English
Size:
10K - 100K
License:
File size: 755 Bytes
9912b8b 4a86774 a0afd10 3324210 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 |
---
license: apache-2.0
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 (Zampieri et al., 2019) 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) |