Update README.md

README.md

@@ -29,7 +29,9 @@ task_categories:
 task_ids:
 - conditional-text-generation-other-paraphrase-generation
 ---
-# Dataset Card for "XL-Sum"
+
+# Dataset Card for "IndicParaphrase"
+
 ## Table of Contents
 - [Dataset Card Creation Guide](#dataset-card-creation-guide)
   - [Table of Contents](#table-of-contents)
@@ -59,19 +61,27 @@ task_ids:
     - [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.
+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)`
@@ -84,8 +94,11 @@ size of the dataset is 5.57M.
 -  `Punjabi (pa)`
 -  `Tamil (ta)`
 -  `Telugu (te)`
+
 ## Dataset Structure
+
 ### Data Instances
+
 One example from the `hi` dataset is given below in JSON format. 
   ```
   {
@@ -99,15 +112,20 @@ One example from the `hi` dataset is given below in JSON format.
  '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)
+-  `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 |
@@ -120,39 +138,76 @@ 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 | 
+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) 
+
+[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) 
+
+[Detailed in the paper](https://arxiv.org/abs/2203.05437)
+
+
+### Annotations
+[More information needed]
+#### Annotation process
+[More information needed]
+
+#### Who are the annotators?
+
+[More information needed]
 
 ### 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"
+  url = "https://arxiv.org/abs/2203.05437",     
 ```
+
+
 ### Contributions
+