Update README.md

README.md

@@ -1,3 +1,158 @@
 ---
-license: cc-by-nc-4.0
+annotations_creators:
+- no-annotation
+language_creators:
+- found
+languages:
+- as
+- bn
+- gu
+- hi
+- kn
+- ml
+- mr
+- or
+- pa
+- ta
+- te
+licenses:
+- cc-by-nc-4.0
+multilinguality:
+- multilingual
+pretty_name: IndicParaphrase
+size_categories:
+- 1M<n<10M
+source_datasets:
+- original
+task_categories:
+- conditional-text-generation
+task_ids:
+- conditional-text-generation-other-paraphrase-generation
 ---
+# Dataset Card for "XL-Sum"
+## Table of Contents
+- [Dataset Card Creation Guide](#dataset-card-creation-guide)
+  - [Table of Contents](#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)
+      - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
+      - [Who are the source language producers?](#who-are-the-source-language-producers)
+    - [Annotations](#annotations)
+      - [Annotation process](#annotation-process)
+      - [Who are the annotators?](#who-are-the-annotators)
+    - [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
+- **Homepage:** https://indicnlp.ai4bharat.org/indicnlg-suite
+- **Paper:** [IndicNLG Suite: Multilingual Datasets for Diverse NLG Tasks in Indic Languages](https://arxiv.org/abs/2203.05437)
+- **Point of Contact:** 
+### Dataset Summary
+IndicParaphrase is the paraphrasing dataset released as part of IndicNLG Suite. Each 
+input is paired with up to 5 references. We create this dataset in eleven 
+languages including as, bn, gu, hi, kn, ml, mr, or, pa, ta, te. The total
+size of the dataset is 5.57M.
+### Supported Tasks and Leaderboards
+**Tasks:** Paraphrase generation
+
+**Leaderboards:** Currently there is no Leaderboard for this dataset.
+### Languages
+-  `Assamese (as)`
+-  `Bengali (bn)`
+-  `Gujarati (gu)`
+-  `Kannada (kn)`
+-  `Hindi (hi)`
+-  `Malayalam (ml)`
+-  `Marathi (mr)`
+-  `Oriya (or)`
+-  `Punjabi (pa)`
+-  `Tamil (ta)`
+-  `Telugu (te)`
+## Dataset Structure
+### Data Instances
+One example from the `hi` dataset is given below in JSON format. 
+  ```
+  {
+    'id': '1',
+ 'input': 'निजी क्षेत्र में प्रदेश की 75 प्रतिशत नौकरियां हरियाणा के युवाओं के लिए आरक्षित की जाएगी।',
+ 'references': ['प्रदेश के युवाओं को निजी उद्योगों में 75 प्रतिशत आरक्षण देंगे।',
+  'युवाओं के लिए हरियाणा की सभी प्राइवेट नौकरियों में 75 प्रतिशत आरक्षण लागू किया जाएगा।',
+  'निजी क्षेत्र में 75 प्रतिशत आरक्षित लागू कर प्रदेश के युवाओं का रोजगार सुनिश्चत किया जाएगा।',
+  'प्राईवेट कम्पनियों में हरियाणा के नौजवानों को 75 प्रतिशत नौकरियां में आरक्षित की जाएगी।',
+  'प्रदेश की प्राइवेट फैक्टरियों में 75 फीसदी रोजगार हरियाणा के युवाओं के लिए आरक्षित किए जाएंगे।'],
+ 'target': 'प्रदेश के युवाओं को निजी उद्योगों में 75 प्रतिशत आरक्षण देंगे।'
+}
+  ```
+### Data Fields
+-  `id (string)`: Unique identifier.
+-  `input (string)`: Input sentence 
+-  `references (list of strings)`: Paraphrases of `input` , ordered according to the least n-gram overlap
+-  `target (string)`: The first reference (most dissimilar paraphrase)
+
+### Data Splits
+We first select 10K instances each for the validation and test and put remaining in the training dataset. `Assamese (as)`, due to its low-resource nature, could only be split into validation and test sets with 4,420 examples each.
+Individual dataset with train-dev-test example counts are given below:
+Language      | ISO 639-1 Code |Train | Dev | Test |
+--------------|----------------|-------|-----|------|
+Assamese | as | - | 4,420 | 4,420 |
+Bengali | bn | 890,445 | 10,000 | 10,000 |
+Gujarati | gu |  379,202 | 10,000 | 10,000 |
+Hindi | hi | 929,507 | 10,000 | 10,000 |
+Kannada | kn |  522,148 | 10,000 | 10,000 | 
+Malayalam | ml |761,933  | 10,000 | 10,000 | 
+Marathi | mr |406,003 | 10,000 | 10,000 | 
+Oriya | or | 105,970 | 10,000 | 10,000 | 
+Punjabi | pa |  266,704 | 10,000 | 10,000 | 
+Tamil | ta | 497,798 | 10,000 | 10,000 | 
+Telugu | te | 596,283 | 10,000 | 10,000 | 
+
+## Dataset Creation
+### Curation Rationale
+[More information needed]
+### Source Data
+[Samanantar dataset](https://indicnlp.ai4bharat.org/samanantar/)
+#### Initial Data Collection and Normalization
+[Detailed in the paper](https://arxiv.org/abs/2203.05437) 
+#### Who are the source language producers?
+[Detailed in the paper](https://arxiv.org/abs/2203.05437) 
+
+### Personal and Sensitive Information
+[More information needed]
+## Considerations for Using the Data
+### Social Impact of Dataset
+[More information needed]
+### Discussion of Biases
+[More information needed]
+### Other Known Limitations
+[More information needed]
+## Additional Information
+### Dataset Curators
+[More information needed]
+### Licensing Information
+Contents of this repository are restricted to only non-commercial research purposes under the [Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0)](https://creativecommons.org/licenses/by-nc-sa/4.0/). Copyright of the dataset contents belongs to the original copyright holders.
+### Citation Information
+If you use any of the datasets, models or code modules, please cite the following paper:
+```
+@inproceedings{Kumar2022IndicNLGSM,
+  title={IndicNLG Suite: Multilingual Datasets for Diverse NLG Tasks in Indic Languages},
+  author={Aman Kumar and Himani Shrotriya and Prachi Sahu and Raj Dabre and Ratish Puduppully and Anoop Kunchukuttan and Amogh Mishra and Mitesh M. Khapra and Pratyush Kumar},
+  year={2022},
+  url = "https://arxiv.org/abs/2203.05437"
+```
+### Contributions