updated dataset card

README.md

@@ -15,17 +15,41 @@ language:
     
 license: "Apache License 2.0"
 ---
-# Dataset Summary
+
+# Dataset Card for AfriBERTa's Corpus
+
+## Table of Contents
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+  - [Loading Dataset](#loading-dataset)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-fields)
+  - [Data Splits](#data-splits)
+- [Considerations for Using the Data](#considerations-for-using-the-data)
+  - [Discussion of Biases](#discussion-of-biases)
+- [Additional Information](#additional-information)
+  - [Citation Information](#citation-information)
+  - [Contributions](#contributions)
+## Dataset Description
+- **Homepage:** https://github.com/keleog/afriberta
+- **Models:** https://huggingface.co/castorini/afriberta_large
+- **Paper:** https://aclanthology.org/2021.mrl-1.11/
+- **Point of Contact:** kelechi.ogueji@uwaterloo.ca
+
+### Dataset Summary
 This is the corpus on which [AfriBERTa] (https://huggingface.co/castorini/afriberta_large) was trained on.
-The dataset contains 11 languages - Afaan Oromoo (also called Oromo), Amharic, Gahuza (a mixed language containing Kinyarwanda and Kirundi), Hausa, Igbo, Nigerian Pidgin, Somali, Swahili, Tigrinya and Yorùbá.
 The dataset is mostly from the BBC news website, but some languages also have data from Common Crawl.  
 
 
-# Supported Tasks and Leaderboards
+### Supported Tasks and Leaderboards
 The AfriBERTa corpus was mostly intended to pre-train language models.
 
-
-# Load Dataset
+### Languages
+Afaan Oromoo (also called Oromo), Amharic, Gahuza (a mixed language containing Kinyarwanda and Kirundi), Hausa, Igbo, Nigerian Pidgin, Somali, Swahili, Tigrinya and Yorùbá.
+### Loading Dataset
 An example to load the train split of the Somali corpus:
 ```
 dataset = load_dataset("castorini/afriberta", "somali", split="train")
@@ -36,25 +60,35 @@ An example to load the test split of the Pidgin corpus:
 dataset = load_dataset("castorini/afriberta", "pidgin", split="test")
 ```
 
-# Data Fields
+## Dataset Structure
+
+### Data Instances
+Each data point is a line of text. 
+An example from the `igbo` dataset:
+```
+{"id": "0", "text": "Ngwá ọrụ na-echebe ma na-ebuli gị na kọmputa."}
+```
+
+### Data Fields
 
 The data fields are:
 
 - id: id of the example
 - text: content as a string
 
-# Data Splits
+### Data Splits
 Each language has a train and test split, with varying sizes. 
 
-# Considerations for Using the Data
+## Considerations for Using the Data
 
-## Discussion of Biases
+### Discussion of Biases
 Since majority of the data is obtained from the BBC's news website, models trained on this dataset are likely going to 
 be biased towards the news domain.
 
 Also, since some of the data is obtained from Common Crawl, care should be taken (especially for text generation models) since personal and sensitive information might be present.
 
-# Citation Information
+## Additional Information
+### Citation Information
 ```
 @inproceedings{ogueji-etal-2021-small,
     title = "Small Data? No Problem! Exploring the Viability of Pretrained Multilingual Language Models for Low-resourced Languages",
@@ -71,5 +105,5 @@ Also, since some of the data is obtained from Common Crawl, care should be taken
 }
 ```
 
-# Contributions
-Thanks to [keleog](https://github.com/keleog)
+### Contributions
+Thanks to [Kelechi Ogueji](https://github.com/keleog) for adding this dataset.