
# Dataset Card for chinese_chatgpt_corpus

## Table of Contents
- [Dataset Description](#dataset-description)
    - [Dataset Summary](#dataset-summary)
    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
    - [Languages](#languages)
- [Dataset Structure](#dataset-structure)
    - [Data Instances](#data-instances)
    - [Data Fields](#data-fields)
    - [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
    - [Curation Rationale](#curation-rationale)
    - [Source Data](#source-data)
    - [Annotations](#annotations)
    - [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
    - [Social Impact of Dataset](#social-impact-of-dataset)
    - [Discussion of Biases](#discussion-of-biases)
    - [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
    - [Dataset Curators](#dataset-curators)
    - [Licensing Information](#licensing-information)
    - [Citation Information](#citation-information)
    - [Contributions](#contributions)

## Dataset Description

- **Size of downloaded dataset files:** 5.05 GB
- **Size of the generated dataset:** 0 GB
- **Total amount of disk used:** 5.05 GB

### Dataset Summary

This repo collects chinese corpus for Supervised Finetuning (SFT) and Reinforcement Learning From Human Feedback (RLHF). 

### Supported Tasks and Leaderboards

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Languages

Chinese

## Dataset Structure

### Data Instances

#### train_data_external_v1.jsonl
- **Size of downloaded dataset files:** 5.04 GB
- **Size of the generated dataset:** 0 GB
- **Total amount of disk used:** 5.04 GB

An example looks as follows:
```
{
    "prompt": "问题：有没有给未成年贷款的有的联系",
    "answers":
    [
        {
            "answer": "若通过招行办理，我行规定，贷款人年龄需年满18岁，且年龄加贷款年限不得超过70岁。如果您持有我行信用卡附属卡，可尝试办理预借现金。",
            "score": 1
        }
    ],
    "prefix": "回答："
}
```

#### dev_data_external_v1.jsonl
- **Size of downloaded dataset files:** 9.55 MB
- **Size of the generated dataset:** 0 MB
- **Total amount of disk used:** 9.55 MB

An example looks as follows:
```
{
    "prompt": "初学纹发现1/2\"的管螺纹并不是1\"的一半。不知道其中的原因，请各位指点。",
    "answers":
    [
        {
            "answer": "管螺纹的名义尺寸是“管子”的孔（内）径，而管子的壁厚不是两倍。所以，1/2\"的管螺纹并不是1\"的一半，",
            "score": 1
        }
    ],
    "prefix": "回答："
}
```

### Data Fields
The data fields are the same among all splits.

#### train_data_external_v1.jsonl
- `prompt`: prompt, `string`
- `answers`: list of answers
  - `answer`: answer, `string`
  - `score`: score of answer, `int`
- `prefix`: prefix to the answer, `string`

#### dev_data_external_v1.jsonl
- `prompt`: prompt, `string`
- `answers`: list of answers
    - `answer`: answer, `string`
    - `score`: score of answer, `int`
- `prefix`: prefix to the answer, `string`


### Data Splits

|   name   | train  |
|----------|-------:|
|train_data_external_v1.jsonl|5477982|
|dev_data_external_v1.jsonl|10000|

## Dataset Creation
### Curation Rationale
Link to github: [data_prepare](https://github.com/sunzeyeah/RLHF/blob/master/src/data_prepare.py)
### Source Data
#### Initial Data Collection and Normalization
- [百科](https://github.com/brightmart/nlp_chinese_corpus)
- [知道问答](https://github.com/SophonPlus/ChineseNlpCorpus)
- [对联](https://github.com/wb14123/couplet-dataset/releases/download/1.0/couplet.tar.gz)
- [古文](https://github.com/NiuTrans/Classical-Modern)
- [古诗词](https://github.com/chinese-poetry/chinese-poetry)
- 微博新闻评论
#### Who are the source language producers?
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Annotations
#### Annotation process
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
#### Who are the annotators?
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
### Personal and Sensitive Information
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Considerations for Using the Data
### Social Impact of Dataset
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
### Discussion of Biases
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
### Other Known Limitations
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
## Additional Information
### Dataset Curators
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
### Licensing Information
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

task_categories:text-generation task_categories:text2text-generation task_categories:question-answering task_categories:reinforcement-learning task_ids:language-modeling task_ids:masked-language-modeling annotations_creators:no-annotation language_creators:unknown multilinguality:monolingual size_categories:5M<n<10M language:zh license:unknown region:us
{"annotations_creators": ["no-annotation"], "language_creators": ["unknown"], "language": ["zh"], "license": ["unknown"], "multilinguality": ["monolingual"], "size_categories": ["5M<n<10M"], "task_categories": ["text-generation", "text2text-generation", "question-answering", "reinforcement-learning"], "task_ids": ["language-modeling", "masked-language-modeling"], "pretty_name": "Chinese-ChatGPT-Corpus"}
TAGS
#task_categories-text-generation #task_categories-text2text-generation #task_categories-question-answering #task_categories-reinforcement-learning #task_ids-language-modeling #task_ids-masked-language-modeling #annotations_creators-no-annotation #language_creators-unknown #multilinguality-monolingual #size_categories-5M<n<10M #language-Chinese #license-unknown #region-us 

Dataset Card for chinese\_chatgpt\_corpus
=========================================


Table of Contents
-----------------


* Dataset Description
	+ Dataset Summary
	+ Supported Tasks and Leaderboards
	+ Languages
* Dataset Structure
	+ Data Instances
	+ Data Fields
	+ Data Splits
* Dataset Creation
	+ Curation Rationale
	+ Source Data
	+ Annotations
	+ Personal and Sensitive Information
* Considerations for Using the Data
	+ Social Impact of Dataset
	+ Discussion of Biases
	+ Other Known Limitations
* Additional Information
	+ Dataset Curators
	+ Licensing Information
	+ Citation Information
	+ Contributions


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


* Size of downloaded dataset files: 5.05 GB
* Size of the generated dataset: 0 GB
* Total amount of disk used: 5.05 GB


### Dataset Summary


This repo collects chinese corpus for Supervised Finetuning (SFT) and Reinforcement Learning From Human Feedback (RLHF).


### Supported Tasks and Leaderboards


### Languages


Chinese


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


### Data Instances


#### train\_data\_external\_v1.jsonl


* Size of downloaded dataset files: 5.04 GB
* Size of the generated dataset: 0 GB
* Total amount of disk used: 5.04 GB


An example looks as follows:


#### dev\_data\_external\_v1.jsonl


* Size of downloaded dataset files: 9.55 MB
* Size of the generated dataset: 0 MB
* Total amount of disk used: 9.55 MB


An example looks as follows:


### Data Fields


The data fields are the same among all splits.


#### train\_data\_external\_v1.jsonl


* 'prompt': prompt, 'string'
* 'answers': list of answers
	+ 'answer': answer, 'string'
	+ 'score': score of answer, 'int'
* 'prefix': prefix to the answer, 'string'


#### dev\_data\_external\_v1.jsonl


* 'prompt': prompt, 'string'
* 'answers': list of answers
	+ 'answer': answer, 'string'
	+ 'score': score of answer, 'int'
* 'prefix': prefix to the answer, 'string'


### Data Splits



Dataset Creation
----------------


### Curation Rationale


Link to github: data\_prepare


### Source Data


#### Initial Data Collection and Normalization


* 百科
* 知道问答
* 对联
* 古文
* 古诗词
* 微博新闻评论


#### Who are the source language producers?


### Annotations


#### Annotation process


#### Who are the annotators?


### Personal and Sensitive Information


Considerations for Using the Data
---------------------------------


### Social Impact of Dataset


### Discussion of Biases


### Other Known Limitations


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


### Dataset Curators


### Licensing Information



### Dataset Summary


This repo collects chinese corpus for Supervised Finetuning (SFT) and Reinforcement Learning From Human Feedback (RLHF). ### Supported Tasks and Leaderboards ### Languages


Chinese


Dataset Structure
----------------- ### Data Instances #### train\_data\_external\_v1.jsonl


* Size of downloaded dataset files: 5.04 GB
* Size of the generated dataset: 0 GB
* Total amount of disk used: 5.04 GB


An example looks as follows: #### dev\_data\_external\_v1.jsonl


* Size of downloaded dataset files: 9.55 MB
* Size of the generated dataset: 0 MB
* Total amount of disk used: 9.55 MB


An example looks as follows: ### Data Fields


The data fields are the same among all splits. #### train\_data\_external\_v1.jsonl


* 'prompt': prompt, 'string'
* 'answers': list of answers
	+ 'answer': answer, 'string'
	+ 'score': score of answer, 'int'
* 'prefix': prefix to the answer, 'string' #### dev\_data\_external\_v1.jsonl


* 'prompt': prompt, 'string'
* 'answers': list of answers
	+ 'answer': answer, 'string'
	+ 'score': score of answer, 'int'
* 'prefix': prefix to the answer, 'string' ### Data Splits



Dataset Creation
---------------- ### Curation Rationale


Link to github: data\_prepare ### Source Data #### Initial Data Collection and Normalization


* 百科
* 知道问答
* 对联
* 古文
* 古诗词
* 微博新闻评论 #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information


Considerations for Using the Data
--------------------------------- ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations


Additional Information
---------------------- ### Dataset Curators ### Licensing Information
TAGS
#task_categories-text-generation #task_categories-text2text-generation #task_categories-question-answering #task_categories-reinforcement-learning #task_ids-language-modeling #task_ids-masked-language-modeling #annotations_creators-no-annotation #language_creators-unknown #multilinguality-monolingual #size_categories-5M<n<10M #language-Chinese #license-unknown #region-us 
 ### Dataset Summary


This repo collects chinese corpus for Supervised Finetuning (SFT) and Reinforcement Learning From Human Feedback (RLHF). ### Supported Tasks and Leaderboards ### Languages


Chinese


Dataset Structure
----------------- ### Data Instances #### train\_data\_external\_v1.jsonl


* Size of downloaded dataset files: 5.04 GB
* Size of the generated dataset: 0 GB
* Total amount of disk used: 5.04 GB


An example looks as follows: #### dev\_data\_external\_v1.jsonl


* Size of downloaded dataset files: 9.55 MB
* Size of the generated dataset: 0 MB
* Total amount of disk used: 9.55 MB


An example looks as follows: ### Data Fields


The data fields are the same among all splits. #### train\_data\_external\_v1.jsonl


* 'prompt': prompt, 'string'
* 'answers': list of answers
	+ 'answer': answer, 'string'
	+ 'score': score of answer, 'int'
* 'prefix': prefix to the answer, 'string' #### dev\_data\_external\_v1.jsonl


* 'prompt': prompt, 'string'
* 'answers': list of answers
	+ 'answer': answer, 'string'
	+ 'score': score of answer, 'int'
* 'prefix': prefix to the answer, 'string' ### Data Splits



Dataset Creation
---------------- ### Curation Rationale


Link to github: data\_prepare ### Source Data #### Initial Data Collection and Normalization


* 百科
* 知道问答
* 对联
* 古文
* 古诗词
* 微博新闻评论 #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information


Considerations for Using the Data
--------------------------------- ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations


Additional Information
---------------------- ### Dataset Curators ### Licensing Information
passage: TAGS
#task_categories-text-generation #task_categories-text2text-generation #task_categories-question-answering #task_categories-reinforcement-learning #task_ids-language-modeling #task_ids-masked-language-modeling #annotations_creators-no-annotation #language_creators-unknown #multilinguality-monolingual #size_categories-5M<n<10M #language-Chinese #license-unknown #region-us 
### Dataset Summary


This repo collects chinese corpus for Supervised Finetuning (SFT) and Reinforcement Learning From Human Feedback (RLHF).### Supported Tasks and Leaderboards### Languages


Chinese


Dataset Structure
-----------------### Data Instances#### train\_data\_external\_v1.jsonl


* Size of downloaded dataset files: 5.04 GB
* Size of the generated dataset: 0 GB
* Total amount of disk used: 5.04 GB


An example looks as follows:#### dev\_data\_external\_v1.jsonl


* Size of downloaded dataset files: 9.55 MB
* Size of the generated dataset: 0 MB
* Total amount of disk used: 9.55 MB


An example looks as follows:### Data Fields


The data fields are the same among all splits.#### train\_data\_external\_v1.jsonl


* 'prompt': prompt, 'string'
* 'answers': list of answers
	+ 'answer': answer, 'string'
	+ 'score': score of answer, 'int'
* 'prefix': prefix to the answer, 'string'#### dev\_data\_external\_v1.jsonl


* 'prompt': prompt, 'string'
* 'answers': list of answers
	+ 'answer': answer, 'string'
	+ 'score': score of answer, 'int'
* 'prefix': prefix to the answer, 'string'### Data Splits



Dataset Creation
----------------