Update README.md

README.md

@@ -18,75 +18,59 @@ dataset_info:
     num_bytes: 1350043.584024078
     num_examples: 8240
   download_size: 8392302
-  dataset_size: 13500272.0
+  dataset_size: 13500272
 language:
 - en
 size_categories:
 - 10K<n<100K
+tags:
+- not-for-all-audiences
+- legal
 ---
 
 # 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.
+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:** [ignitr.tech](ignitr.tech/interpretor)
+- **Homepage:** [zuendorf.me](https://www.zuendorf.me)
 - **Repository:** [GitHub Monorepo](https://github.com/LennardZuendorf/interpretor)
 - **Author:** Lennard Zündorf
 
 ### Original Dataset Description
 
-- **Source Homepage:** [GitHub](https://github.com/bvidgen/Dynamically-Generated-Hate-Speech-Dataset)
-- **Source Contact:** [bertievidgen@gmail.com](mailto:bertievidgen@gmail.com)
+- **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, already split into training (90%) and testing (10%). I inteded it to be used for classifcation tasks like [this]() model.
+This Dataset contains dynamically generated hate-speech, processed to be used in classification tasks with i.E. BERT.
 
-### Languages
-The only represented language is english.
+### Edit Summary
 
-## Dataset Structure
+- 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
 
-### Data Instances
+## Dataset Structure
 
-Each entry looks like this (train and test).
 
-```
-{
-  'id': ...,
-  'text': ,
-  ''
-}
-```
+### Split
 
-Provide any additional information that is not covered in the other sections about the data here. In particular describe any relationships between data points and if these relationships are made explicit.
+- The dataset is split into train and test, in a 90% to 10% split
+- Train = ~ 74k entries
+- Test = ~ 8k entries
 
 ### Data Fields
 
-List and describe the fields present in the dataset. Mention their data type, and whether they are used as input or output in any of the tasks the dataset currently supports. If the data has span indices, describe their attributes, such as whether they are at the character level or word level, whether they are contiguous or not, etc. If the datasets contains example IDs, state whether they have an inherent meaning, such as a mapping to other datasets or pointing to relationships between data points.
-
-- `example_field`: description of `example_field`
-
-Note that the descriptions can be initialized with the **Show Markdown Data Fields** output of the [Datasets Tagging app](https://huggingface.co/spaces/huggingface/datasets-tagging), you will then only need to refine the generated descriptions.
-
-### Data Splits
-
-Describe and name the splits in the dataset if there are more than one.
-
-Describe any criteria for splitting the data, if used. If there are differences between the splits (e.g. if the training annotations are machine-generated and the dev and test ones are created by humans, or if different numbers of annotators contributed to each example), describe them here.
-
-Provide the sizes of each split. As appropriate, provide any descriptive statistics for the features, such as average length.  For example:
-
-|                         | train | validation | test |
-|-------------------------|------:|-----------:|-----:|
-| Input Sentences         |       |            |      |
-| Average Sentence Length |       |            |      |
 
+| id | text | label | label_text |
+| - | - | - | - |
+| numeric id | text of the comment | binary label, 0 = not hate, 1 = hate | label in text form
 
 ## Additional Information