
# Dataset Card for Dataset Name

This is an edit of original work from Bertie Vidgen, Tristan Thrush, Zeerak Waseem and Douwe Kiela. 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.

## Dataset Description

- **Homepage:** [zuendorf.me](https://www.zuendorf.me)
- **Repository:** [GitHub Monorepo](https://github.com/LennardZuendorf/interpretor)
- **Author:** Lennard Zündorf

### Original Dataset Description

- **Original Source Contact:** [bertievidgen@gmail.com](mailto:bertievidgen@gmail.com)
- **Original Source:** [Dynamically-Generated-Hate-Speech-Dataset](https://github.com/bvidgen/Dynamically-Generated-Hate-Speech-Dataset)
- **Original Author List:** Bertie Vidgen (The Alan Turing Institute), Tristan Thrush (Facebook AI Research), Zeerak Waseem (University of Sheffield) and Douwe Kiela (Facebook AI Research).

**Refer to the Huggingface or GitHub Repo for more information**

### Dataset Summary
This Dataset contains dynamically generated hate-speech, processed to be used in classification tasks with i.E. BERT.

### Edit Summary

- I have edited the dataset to use it in training the similarly named [Interpretor Classifier]()
- see data/label fields below and the original dataset [here](https://huggingface.co/datasets/LennardZuendorf/Dynamically-Generated-Hate-Speech-Dataset/edit/main/README.md)
- Edits mostly include cleaning out information not needed for a simple binary classification tasks and adding a numerical binary label

## Dataset Structure


### Split

- The dataset is split into train and test, in a 90% to 10% split
- Train = ~ 74k entries
- Test = ~ 8k entries

### Data Fields


| id | text | label | label_text |
| - | - | - | - |
| numeric id | text of the comment | binary label, 0 = not hate, 1 = hate | label in text form

## Additional Information

### Licensing Information

- The original repository does not provide any license, but is free for use with proper citation of the original paper (see link above)
- This dataset can be used under the MIT license, with proper citation of both the original and this source.
- But I suggest taking data from the original source and doing your own editing.

### Citation Information

Please cite this repository and the original authors (see above) when using it.

### Contributions

I removed some data fields and did a new split with hugging face datasets.
size_categories:10K<n<100K language:en license:mit not-for-all-audiences legal region:us
{"language": ["en"], "license": "mit", "size_categories": ["10K<n<100K"], "dataset_info": {"features": [{"name": "id", "dtype": "int64"}, {"name": "text", "dtype": "string"}, {"name": "label", "dtype": "int64"}, {"name": "label_text", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 12150228.415975923, "num_examples": 74159}, {"name": "test", "num_bytes": 1350043.584024078, "num_examples": 8240}], "download_size": 8392302, "dataset_size": 13500272}, "tags": ["not-for-all-audiences", "legal"]}
TAGS
#size_categories-10K<n<100K #language-English #license-mit #not-for-all-audiences #legal #region-us 

Dataset Card for Dataset Name
=============================


This is an edit of original work from Bertie Vidgen, Tristan Thrush, Zeerak Waseem and Douwe Kiela. Which I have uploaded to Huggingface here. It is not my original work, I just edited it.
Data is used in the similarly named Interpretor Model.


Dataset Description
-------------------


* Homepage: URL
* Repository: GitHub Monorepo
* Author: Lennard Zündorf


### Original Dataset Description


* Original Source Contact: bertievidgen@URL
* Original Source: Dynamically-Generated-Hate-Speech-Dataset
* Original Author List: Bertie Vidgen (The Alan Turing Institute), Tristan Thrush (Facebook AI Research), Zeerak Waseem (University of Sheffield) and Douwe Kiela (Facebook AI Research).


Refer to the Huggingface or GitHub Repo for more information


### Dataset Summary


This Dataset contains dynamically generated hate-speech, processed to be used in classification tasks with i.E. BERT.


### Edit Summary


* I have edited the dataset to use it in training the similarly named Interpretor Classifier
* see data/label fields below and the original dataset here
* Edits mostly include cleaning out information not needed for a simple binary classification tasks and adding a numerical binary label


Dataset Structure
-----------------


### Split


* The dataset is split into train and test, in a 90% to 10% split
* Train = ~ 74k entries
* Test = ~ 8k entries


### Data Fields



Additional Information
----------------------


### Licensing Information


* The original repository does not provide any license, but is free for use with proper citation of the original paper (see link above)
* This dataset can be used under the MIT license, with proper citation of both the original and this source.
* But I suggest taking data from the original source and doing your own editing.


Please cite this repository and the original authors (see above) when using it.


### Contributions


I removed some data fields and did a new split with hugging face datasets.



### Original Dataset Description


* Original Source Contact: bertievidgen@URL
* Original Source: Dynamically-Generated-Hate-Speech-Dataset
* Original Author List: Bertie Vidgen (The Alan Turing Institute), Tristan Thrush (Facebook AI Research), Zeerak Waseem (University of Sheffield) and Douwe Kiela (Facebook AI Research).


Refer to the Huggingface or GitHub Repo for more information ### Dataset Summary


This Dataset contains dynamically generated hate-speech, processed to be used in classification tasks with i.E. BERT. ### Edit Summary


* I have edited the dataset to use it in training the similarly named Interpretor Classifier
* see data/label fields below and the original dataset here
* Edits mostly include cleaning out information not needed for a simple binary classification tasks and adding a numerical binary label


Dataset Structure
----------------- ### Split


* The dataset is split into train and test, in a 90% to 10% split
* Train = ~ 74k entries
* Test = ~ 8k entries ### Data Fields



Additional Information
---------------------- ### Licensing Information


* The original repository does not provide any license, but is free for use with proper citation of the original paper (see link above)
* This dataset can be used under the MIT license, with proper citation of both the original and this source.
* But I suggest taking data from the original source and doing your own editing.


Please cite this repository and the original authors (see above) when using it. ### Contributions


I removed some data fields and did a new split with hugging face datasets.
TAGS
#size_categories-10K<n<100K #language-English #license-mit #not-for-all-audiences #legal #region-us 
 ### Original Dataset Description


* Original Source Contact: bertievidgen@URL
* Original Source: Dynamically-Generated-Hate-Speech-Dataset
* Original Author List: Bertie Vidgen (The Alan Turing Institute), Tristan Thrush (Facebook AI Research), Zeerak Waseem (University of Sheffield) and Douwe Kiela (Facebook AI Research).


Refer to the Huggingface or GitHub Repo for more information ### Dataset Summary


This Dataset contains dynamically generated hate-speech, processed to be used in classification tasks with i.E. BERT. ### Edit Summary


* I have edited the dataset to use it in training the similarly named Interpretor Classifier
* see data/label fields below and the original dataset here
* Edits mostly include cleaning out information not needed for a simple binary classification tasks and adding a numerical binary label


Dataset Structure
----------------- ### Split


* The dataset is split into train and test, in a 90% to 10% split
* Train = ~ 74k entries
* Test = ~ 8k entries ### Data Fields



Additional Information
---------------------- ### Licensing Information


* The original repository does not provide any license, but is free for use with proper citation of the original paper (see link above)
* This dataset can be used under the MIT license, with proper citation of both the original and this source.
* But I suggest taking data from the original source and doing your own editing.


Please cite this repository and the original authors (see above) when using it. ### Contributions


I removed some data fields and did a new split with hugging face datasets.
passage: TAGS
#size_categories-10K<n<100K #language-English #license-mit #not-for-all-audiences #legal #region-us 
### Original Dataset Description


* Original Source Contact: bertievidgen@URL
* Original Source: Dynamically-Generated-Hate-Speech-Dataset
* Original Author List: Bertie Vidgen (The Alan Turing Institute), Tristan Thrush (Facebook AI Research), Zeerak Waseem (University of Sheffield) and Douwe Kiela (Facebook AI Research).


Refer to the Huggingface or GitHub Repo for more information### Dataset Summary


This Dataset contains dynamically generated hate-speech, processed to be used in classification tasks with i.E. BERT.### Edit Summary


* I have edited the dataset to use it in training the similarly named Interpretor Classifier
* see data/label fields below and the original dataset here
* Edits mostly include cleaning out information not needed for a simple binary classification tasks and adding a numerical binary label


Dataset Structure
-----------------### Split


* The dataset is split into train and test, in a 90% to 10% split
* Train = ~ 74k entries
* Test = ~ 8k entries### Data Fields



Additional Information
----------------------### Licensing Information


* The original repository does not provide any license, but is free for use with proper citation of the original paper (see link above)
* This dataset can be used under the MIT license, with proper citation of both the original and this source.
* But I suggest taking data from the original source and doing your own editing.


Please cite this repository and the original authors (see above) when using it.### Contributions


I removed some data fields and did a new split with hugging face datasets.