Create README.md

README.md

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+---
+annotations_creators:
+- shibing624
+language_creators:
+- shibing624
+languages:
+- zh
+licenses:
+- cc-by-4-0
+multilinguality:
+- monolingual
+size_categories:
+- 100K<n<20M
+source_datasets:
+- extended|other-flicker-30k
+- https://github.com/IceFlameWorm/NLP_Datasets/tree/master/ATEC
+- http://icrc.hitsz.edu.cn/info/1037/1162.htm
+- http://icrc.hitsz.edu.cn/Article/show/171.html
+- https://arxiv.org/abs/1908.11828
+- https://github.com/pluto-junzeng/CNSD
+task_categories:
+- text-classification
+- text-scoring
+task_ids:
+- natural-language-inference
+- semantic-similarity-scoring
+paperswithcode_id: snli
+pretty_name: Stanford Natural Language Inference
+---
+# Dataset Card for NLI_zh
+## 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
+- **Repository:** [Chinese NLI dataset](https://github.com/shibing624/text2vec)
+- **Leaderboard:** [NLI_zh leaderboard](https://github.com/shibing624/text2vec) (located on the homepage)
+- **Size of downloaded dataset files:** 16 MB
+- **Total amount of disk used:** 42 MB
+### Dataset Summary
+
+常见中文语义匹配数据集，包含[ATEC](https://github.com/IceFlameWorm/NLP_Datasets/tree/master/ATEC)、[BQ](http://icrc.hitsz.edu.cn/info/1037/1162.htm)、[LCQMC](http://icrc.hitsz.edu.cn/Article/show/171.html)、[PAWSX](https://arxiv.org/abs/1908.11828)、[STS-B](https://github.com/pluto-junzeng/CNSD)共5个任务。
+可以从数据集对应的链接自行下载，也可以从[百度网盘(提取码:qkt6)](https://pan.baidu.com/s/1d6jSiU1wHQAEMWJi7JJWCQ)下载。其中senteval_cn目录是评测数据集汇总，senteval_cn.zip是senteval目录的打包，两者下其一就好。
+
+- ATEC: https://github.com/IceFlameWorm/NLP_Datasets/tree/master/ATEC
+- BQ: http://icrc.hitsz.edu.cn/info/1037/1162.htm
+- LCQMC: http://icrc.hitsz.edu.cn/Article/show/171.html
+- PAWSX: https://arxiv.org/abs/1908.11828
+- STS-B: https://github.com/pluto-junzeng/CNSD
+
+
+### Supported Tasks and Leaderboards
+
+Supported Tasks: 支持中文文本匹配任务，文本相似度计算等相关任务。
+
+中文匹配任务的结果目前在顶会paper上出现较少，我罗列一个我自己训练的结果：
+
+**Leaderboard:** [NLI_zh leaderboard](https://github.com/shibing624/text2vec) 
+
+### Languages
+
+数据集均是简体中文文本。
+
+## Dataset Structure
+### Data Instances
+An example of 'train' looks as follows.
+```
+{
+  "sentence1": "刘诗诗杨幂谁漂亮",
+  "sentence2": "刘诗诗和杨幂谁漂亮",
+  "label": 1,
+}
+{
+  "sentence1": "汇理财怎么样",
+  "sentence2": "怎么样去理财",
+  "label": 0,
+}
+```
+
+### Data Fields
+The data fields are the same among all splits.
+
+- `sentence1`: a `string` feature.
+- `sentence2`: a `string` feature.
+- `label`: a classification label, with possible values including `similarity` (1), `dissimilarity` (0).
+
+### Data Splits
+
+#### ATEC
+
+```shell
+$ wc -l ATEC/*
+   20000 ATEC/ATEC.test.data
+   62477 ATEC/ATEC.train.data
+   20000 ATEC/ATEC.valid.data
+  102477 total
+```
+
+#### BQ
+
+```shell
+$ wc -l BQ/*
+   10000 BQ/BQ.test.data
+  100000 BQ/BQ.train.data
+   10000 BQ/BQ.valid.data
+  120000 total
+```
+
+#### LCQMC
+
+```shell
+$ wc -l LCQMC/*
+   12500 LCQMC/LCQMC.test.data
+  238766 LCQMC/LCQMC.train.data
+    8802 LCQMC/LCQMC.valid.data
+  260068 total
+```
+
+#### PAWSX
+
+```shell
+$ wc -l PAWSX/*
+    2000 PAWSX/PAWSX.test.data
+   49401 PAWSX/PAWSX.train.data
+    2000 PAWSX/PAWSX.valid.data
+   53401 total
+```
+
+#### STS-B
+
+```shell
+$ wc -l STS-B/*
+    1361 STS-B/STS-B.test.data
+    5231 STS-B/STS-B.train.data
+    1458 STS-B/STS-B.valid.data
+    8050 total
+```
+
+## Dataset Creation
+### Curation Rationale
+作为中文NLI(natural langauge inference)数据集，这里把这个数据集上传到huggingface的datasets，方便大家使用。
+### Source Data
+#### Initial Data Collection and Normalization
+#### Who are the source language producers?
+数据集的版权归原作者所有，使用各数据集时请尊重原数据集的版权。
+
+BQ: Jing Chen, Qingcai Chen, Xin Liu, Haijun Yang, Daohe Lu, Buzhou Tang, The BQ Corpus: A Large-scale Domain-specific Chinese Corpus For Sentence Semantic Equivalence Identification EMNLP2018. 
+### Annotations
+#### Annotation process
+
+#### Who are the annotators?
+原作者。
+
+### Personal and Sensitive Information
+
+## Considerations for Using the Data
+### Social Impact of Dataset
+This dataset was developed as a benchmark for evaluating representational systems for text, especially including those induced by representation learning methods, in the task of predicting truth conditions in a given context. 
+
+Systems that are successful at such a task may be more successful in modeling semantic representations.
+### Discussion of Biases
+### Other Known Limitations
+## Additional Information
+### Dataset Curators
+
+- 苏剑林对文件名称有整理
+- 我上传到huggingface的datasets
+
+### Licensing Information
+
+用于学术研究。
+
+The BQ corpus is free to the public for academic research.
+
+
+### Contributions
+
+Thanks to [@shibing624](https://github.com/shibing624) add this dataset.