Update README.md

README.md

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 ---
-license: mit
+annotations_creators:
+- machine-generated
+- manual-partial-validation
+language_creators:
+- expert-generated
+language:
+- id
+license: unknown
+multilinguality:
+- monolingual
+size_categories:
+- 10K<n<100K
+source_datasets:
+- IDK-MRC
+task_categories:
+- text-classification
+task_ids:
+- natural-language-inference
+pretty_name: IDK-MRC-NLI
+dataset_info:
+  features:
+  - name: premise
+    dtype: string
+  - name: hypothesis
+    dtype: string
+  - name: label
+    dtype:
+      class_label:
+        names:
+          '0': entailment
+          '1': neutral
+          '2': contradiction
+  config_name: idkmrc-nli
+  splits:
+  - name: train
+    num_bytes: 5916125
+    num_examples: 18665
+  - name: validation
+    num_bytes: 473125
+    num_examples: 1529
+  - name: test
+    num_bytes: 521375
+    num_examples: 1689
+  download_size: 6910625
+  dataset_size: 21883
 ---
+
+# Dataset Card for IDK-MRC-NLI
+
+## 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:** [Hugging Face](https://huggingface.co/datasets/muhammadravi251001/idkmrc-nli)
+- **Point of Contact:** [Hugging Face](https://huggingface.co/datasets/muhammadravi251001/idkmrc-nli)
+- **Experiment:** [Github](https://github.com/muhammadravi251001/multilingual-qas-with-nli)
+
+### Dataset Summary
+
+The IDKMRC-NLI dataset is derived from the IDKMRC question answering dataset, utilizing named entity recognition (NER), chunking tags, Regex, and embedding similarity techniques to determine its contradiction sets. 
+Collected through this process, the dataset comprises various columns beyond premise, hypothesis, and label, including properties aligned with NER and chunking tags. 
+This dataset is designed to facilitate Natural Language Inference (NLI) tasks and contains information extracted from diverse sources to provide comprehensive coverage. 
+Each data instance encapsulates premise, hypothesis, label, and additional properties pertinent to NLI evaluation.
+
+### Supported Tasks and Leaderboards
+
+- Natural Language Inference for Indonesian
+
+### Languages
+
+Indonesian
+
+## Dataset Structure
+
+### Data Instances
+
+An example of `test` looks as follows.
+
+```
+{
+  "premise": "Karangkancana adalah sebuah kecamatan di Kabupaten Kuningan, Provinsi Jawa Barat, Indonesia.", 
+  "hypothesis": "Dimanakah letak Desa Karang kancana? Kabupaten Kuningan, Provinsi Jawa Barat, Indonesia.", 
+  "label": 0
+}
+```
+### Data Fields
+
+The data fields are:
+- `premise`: a `string` feature
+- `hypothesis`: a `string` feature
+- `label`: a classification label, with possible values including `entailment` (0), `neutral` (1), `contradiction` (2).
+
+### Data Splits #TODO
+
+The data is split across `train`, `valid`, and `test`. 
+
+|   split   | # examples |
+|----------|-------:|
+|train|   18665|
+|valid|   1529|
+|test|   1689|
+
+## Dataset Creation
+
+### Curation Rationale
+
+Indonesian NLP is considered under-resourced. We need NLI dataset to fine-tuning the NLI model to utilizing them for QA models in order to improving the performance of the QA's.
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+We collect the data from the prominent QA dataset in Indonesian. The annotation fully by the original dataset's researcher.
+
+#### Who are the source language producers?
+
+This synthetic data was produced by machine, but the original data was produced by human.
+
+### Personal and Sensitive Information
+
+There might be some personal information coming from Wikipedia and news, especially the information of famous/important people.
+
+## Considerations for Using the Data
+
+### Discussion of Biases
+
+The QA dataset (so the NLI-derived from them) is created using premise sentences taken from Wikipedia and news. These data sources may contain some bias.
+
+### Other Known Limitations
+
+No other known limitations
+
+## Additional Information
+
+### Dataset Curators
+
+This dataset is the result of the collaborative work of Indonesian researchers from the University of Indonesia, Mohamed bin Zayed University of Artificial Intelligence, and the Korea Advanced Institute of Science & Technology.
+
+### Licensing Information
+
+The license is Unknown. Please contact authors for any information on the dataset.