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---
license: mit
dataset_info:
features:
- name: id
dtype: int64
- name: text
dtype: string
- name: label
dtype: string
splits:
- name: train
num_bytes: 11556956.415975923
num_examples: 74159
- name: test
num_bytes: 1284123.584024078
num_examples: 8240
download_size: 8360542
dataset_size: 12841080
language:
- en
size_categories:
- 10K<n<100K
---
# Dataset Card for Dataset Name
This is an edit of original work from [this paper](https://arxiv.org/abs/2012.15761), which I have uploaded to Huggingface [here](https://huggingface.co/datasets/LennardZuendorf/Dynamically-Generated-Hate-Speech-Dataset/edit/main/README.md). It is not my original work, I just edited it.
Data is used in the similarly named Interpretor-Model, which is part of my bachelor Thesis.
## Dataset Description
- **Homepage:** [GitHub](https://github.com/bvidgen/Dynamically-Generated-Hate-Speech-Dataset)
- **Point of Contact:** [bertievidgen@gmail.com](mailto:bertievidgen@gmail.com)
## Original Source: Dynamically-Generated-Hate-Speech-Dataset
ReadMe for v0.2 of the Dynamically Generated Hate Speech Dataset from Vidgen et al. (2021). If you use the dataset, please cite our paper in the Proceedings of ACL 2021, and available on [Arxiv](https://arxiv.org/abs/2012.15761).
Contact Dr. Bertie Vidgen if you have feedback or queries: bertievidgen@gmail.com.
The full author list is: Bertie Vidgen (The Alan Turing Institute), Tristan Thrush (Facebook AI Research), Zeerak Waseem (University of Sheffield) and Douwe Kiela (Facebook AI Research). This paper is an output of the Dynabench project: https://dynabench.org/tasks/5#overall
### Refer to the Huggingface or GitHub Repo for more information
## Additional Information
### Licensing Information
The original repository does not provide any license, but is free for use with proper citation of the original paper in the Proceedings of ACL 2021, available on [Arxiv](https://arxiv.org/abs/2012.15761)
### Citation Information
Please cite this repository and the original authors when using it.
### Contributions
I removed some fields of the data and did a new split with hugging face datasets. |