dataset_info:
features:
- name: sentence
dtype: string
- name: unfairness_level
dtype: string
- name: __index_level_0__
dtype: int64
splits:
- name: train
num_bytes: 859666
num_examples: 5378
- name: validation
num_bytes: 73545
num_examples: 415
- name: test
num_bytes: 175734
num_examples: 1038
download_size: 547326
dataset_size: 1108945
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
license: mit
language:
- en
pretty_name: TOS_Dataset
TOS_Dataset
This dataset contains clauses from Terms of Service (ToS) documents with annotations indicating the fairness level of each clause. The dataset includes clauses labeled as clearly_fair
, potentially_unfair
, and clearly_unfair
.
Dataset Summary
The dataset comprises clauses extracted from various ToS documents. Each clause is annotated with a fairness level, indicating whether it is clearly fair, potentially unfair, or clearly unfair.
Supported Tasks
This dataset can be used for multi-class classification tasks, specifically for classifying the fairness of clauses in ToS documents.
Languages
The dataset is in English.
Dataset Structure
The dataset is split into three sets: train, validation, and test.
Data Fields
sentence
: The clause from the ToS document.unfairness_level
: The fairness level assigned to the clause. Possible values areclearly_fair
,potentially_unfair
, andclearly_unfair
.
Data Splits
Split | Count |
---|---|
Train | 5.38k rows |
Validation | 415 rows |
Test | 1.04k rows |
Usage
To load the dataset:
from datasets import load_dataset
dataset = load_dataset("CodeHima/TOS_Dataset")
Example
from datasets import load_dataset
dataset = load_dataset("CodeHima/TOS_Dataset")
for split in ['train', 'validation', 'test']:
print(f"Example from {split} split:")
print(dataset[split][0])
License
This dataset is licensed under the MIT. Please see the LICENSE file for more details.
Citation
If you use this dataset in your research, please cite it as follows:
@dataset{CodeHima_TOS_Dataset,
author = {CodeHima},
title = {TOS_Dataset},
year = {2024},
publisher = {Hugging Face},
url = {https://huggingface.co/datasets/CodeHima/TOS_Dataset},
}