task_categories:text2text-generation size_categories:100K<n<1M language:en license:openrail region:us
---
license: openrail
task_categories:
- text2text-generation
language:
- en
size_categories:
- 100K<n<1M
---
This is a dataset of paraphrases created by ChatGPT.

Model based on this dataset is avaible: [model](https://huggingface.co/humarin/chatgpt_paraphraser_on_T5_base)

## We used this prompt to generate paraphrases
Generate 5 similar paraphrases for this question, show it like a numbered list without commentaries: *{text}*

This dataset is based on the [Quora paraphrase question](https://www.kaggle.com/competitions/quora-question-pairs), texts from the [SQUAD 2.0](https://huggingface.co/datasets/squad_v2) and the [CNN news dataset](https://huggingface.co/datasets/cnn_dailymail).

We generated 5 paraphrases for each sample, totally this dataset has about 420k data rows. You can make 30 rows from a row from each sample. In this way you can make 12.6 millions train pairs (420k rows with 5 paraphrases -&gt; 6x5x420000 = 12.6 millions of bidirected or 6x5x420000/2 = 6.3 millions of unique pairs).

## We used
- 247138 questions from the Quora dataset 
- 91983 texts from the Squad 2.0 dataset
- 80076 texts from the CNN news dataset

## Structure of the dataset
- text column - an original sentence or question from the datasets
- paraphrases - a list of 5 paraphrases
- category - question / sentence
- source - quora / squad_2 / cnn_news

## Legal disclaimer

Data is based on OpenAI’s gpt-3.5-turbo, whose [terms of use](https://openai.com/policies/terms-of-use) prohibit developing models that compete with OpenAI. So if you use this dataset to train a model, don't compete with OpenAI.


### BibTeX entry and citation info

```bibtex
@inproceedings{chatgpt_paraphrases_dataset,
  author={Vladimir Vorobev, Maxim Kuznetsov},
  title={ChatGPT paraphrases dataset},
  year={2023}
}
```