# Human-vs-Machine
This is a dataset collection created in relation to a bachelor thesis written by Nicolai Thorer Sivesind and Andreas Bentzen Winje. It contains human-produced and machine-generated text samples from two domains: Wikipedia introducions and Scientific research abstracts. 

Each of the two domains are already exisitng datasets reformatted for text-classification:

[GPT-wiki-intros:](https://huggingface.co/datasets/aadityaubhat/GPT-wiki-intro)
+ Generated samples are produced using the GPT-3 model, _text-curie-001_
  + Target content set by title of real wikipedia introduction and a starter sentence.
  + Target word count of 200 words each.
+ Contains 150k data points of each class.
+ Created by Aaditya Bhat

[ChatGPT-Research-Abstracts](https://huggingface.co/datasets/NicolaiSivesind/ChatGPT-Research-Abstracts):
+ Generated samples are produced using the GPT-3.5 model, _GPT-3.5-turbo-0301_ (Snapshot of the model used in ChatGPT 1st of March, 2023).
  + Target content set by title of real abstract.
  + Target word count equal to the human-produced abstract
+ Contains 10k data points of each class.
+ Created by Nicolai Thorer Sivesind

### Credits
+ [GPT-wiki-intro](https://huggingface.co/datasets/aadityaubhat/GPT-wiki-intro), by Aaditya Bhat

### Citation
Please use the following citation:
```
@misc {sivesind_2023,
    author       = { {Nicolai Thorer Sivesind}, {Andreas Bentzen Winje}},
    title        = { Human-vs-Machine },
    year         = 2023,
    publisher    = { Hugging Face }
}
```

More information about the dataset will be added once the thesis is finished (end of may 2023).
task_categories:text-classification size_categories:100K<n<1M language:en license:cc chatgpt gpt research abstracts wikipedia introductions region:us
{"language": ["en"], "license": "cc", "size_categories": ["100K<n<1M"], "task_categories": ["text-classification"], "pretty_name": "Human vs Machine - Labled text segments produced by humans and LLMs", "tags": ["chatgpt", "gpt", "research abstracts", "wikipedia introductions"]}
TAGS
#task_categories-text-classification #size_categories-100K<n<1M #language-English #license-cc #chatgpt #gpt #research abstracts #wikipedia introductions #region-us 

# Human-vs-Machine
This is a dataset collection created in relation to a bachelor thesis written by Nicolai Thorer Sivesind and Andreas Bentzen Winje. It contains human-produced and machine-generated text samples from two domains: Wikipedia introducions and Scientific research abstracts. 

Each of the two domains are already exisitng datasets reformatted for text-classification:

GPT-wiki-intros:
+ Generated samples are produced using the GPT-3 model, _text-curie-001_
  + Target content set by title of real wikipedia introduction and a starter sentence.
  + Target word count of 200 words each.
+ Contains 150k data points of each class.
+ Created by Aaditya Bhat

ChatGPT-Research-Abstracts:
+ Generated samples are produced using the GPT-3.5 model, _GPT-3.5-turbo-0301_ (Snapshot of the model used in ChatGPT 1st of March, 2023).
  + Target content set by title of real abstract.
  + Target word count equal to the human-produced abstract
+ Contains 10k data points of each class.
+ Created by Nicolai Thorer Sivesind

### Credits
+ GPT-wiki-intro, by Aaditya Bhat

Please use the following citation:


More information about the dataset will be added once the thesis is finished (end of may 2023).
# Human-vs-Machine
This is a dataset collection created in relation to a bachelor thesis written by Nicolai Thorer Sivesind and Andreas Bentzen Winje. It contains human-produced and machine-generated text samples from two domains: Wikipedia introducions and Scientific research abstracts. 

Each of the two domains are already exisitng datasets reformatted for text-classification:

GPT-wiki-intros:
+ Generated samples are produced using the GPT-3 model, _text-curie-001_
  + Target content set by title of real wikipedia introduction and a starter sentence.
  + Target word count of 200 words each.
+ Contains 150k data points of each class.
+ Created by Aaditya Bhat

ChatGPT-Research-Abstracts:
+ Generated samples are produced using the GPT-3.5 model, _GPT-3.5-turbo-0301_ (Snapshot of the model used in ChatGPT 1st of March, 2023).
  + Target content set by title of real abstract.
  + Target word count equal to the human-produced abstract
+ Contains 10k data points of each class.
+ Created by Nicolai Thorer Sivesind ### Credits
+ GPT-wiki-intro, by Aaditya Bhat

Please use the following citation:


More information about the dataset will be added once the thesis is finished (end of may 2023).
TAGS
#task_categories-text-classification #size_categories-100K<n<1M #language-English #license-cc #chatgpt #gpt #research abstracts #wikipedia introductions #region-us 
 # Human-vs-Machine
This is a dataset collection created in relation to a bachelor thesis written by Nicolai Thorer Sivesind and Andreas Bentzen Winje. It contains human-produced and machine-generated text samples from two domains: Wikipedia introducions and Scientific research abstracts. 

Each of the two domains are already exisitng datasets reformatted for text-classification:

GPT-wiki-intros:
+ Generated samples are produced using the GPT-3 model, _text-curie-001_
  + Target content set by title of real wikipedia introduction and a starter sentence.
  + Target word count of 200 words each.
+ Contains 150k data points of each class.
+ Created by Aaditya Bhat

ChatGPT-Research-Abstracts:
+ Generated samples are produced using the GPT-3.5 model, _GPT-3.5-turbo-0301_ (Snapshot of the model used in ChatGPT 1st of March, 2023).
  + Target content set by title of real abstract.
  + Target word count equal to the human-produced abstract
+ Contains 10k data points of each class.
+ Created by Nicolai Thorer Sivesind ### Credits
+ GPT-wiki-intro, by Aaditya Bhat

Please use the following citation:


More information about the dataset will be added once the thesis is finished (end of may 2023).