Added files

README.md

@@ -0,0 +1,190 @@
+---
+annotations_creators:
+- machine-generated
+language_creators:
+- found
+multilinguality:
+- monolingual
+size_categories:
+- 100K<n<1M
+source_datasets:
+- extended
+task_categories:
+- text-classification
+task_ids:
+- natural-language-inference
+languages:
+- bn
+licenses:
+- cc-by-nc-sa-4.0
+---
+
+# Dataset Card for `xnli_bn`
+
+## Table of Contents
+- [Dataset Card for `xnli_bn`](#dataset-card-for-xnli_bn)
+  - [Table of Contents](#table-of-contents)
+  - [Dataset Description](#dataset-description)
+    - [Dataset Summary](#dataset-summary)
+    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+    - [Languages](#languages)
+    - [Usage](#usage)
+  - [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
+
+- **Repository:** [https://github.com/csebuetnlp/banglabert](https://github.com/csebuetnlp/banglabert)
+- **Paper:** [**"BanglaBERT: Combating Embedding Barrier in Multilingual Models for Low-Resource Language Understanding"**](https://arxiv.org/abs/2101.00204)
+- **Point of Contact:** [Tahmid Hasan](mailto:tahmidhasan@cse.buet.ac.bd)
+
+### Dataset Summary
+
+This is a Natural Language Inference (NLI) dataset for Bengali, curated using the subset of
+MNLI data used in XNLI and state-of-the-art English to Bengali translation model introduced **[here](https://aclanthology.org/2020.emnlp-main.207/).**
+
+
+### Supported Tasks and Leaderboards
+
+[More information needed](https://github.com/csebuetnlp/banglabert)
+
+### Languages
+
+* `Bengali`
+
+### Usage
+```python
+from datasets import load_dataset
+dataset = load_dataset("csebuetnlp/xnli_bn")
+```
+## Dataset Structure
+
+### Data Instances
+
+One example from the dataset is given below in JSON format. 
+  ```
+  {
+    "sentence1": "আসলে, আমি এমনকি এই বিষয়ে চিন্তাও করিনি, কিন্তু আমি এত হতাশ হয়ে পড়েছিলাম যে, শেষ পর্যন্ত আমি আবার তার সঙ্গে কথা বলতে শুরু করেছিলাম",
+    "sentence2": "আমি তার সাথে আবার কথা বলিনি।",
+    "label": "contradiction"
+}
+  ```
+
+### Data Fields
+
+The data fields are as follows:
+
+- `sentence1`: a `string` feature indicating the premise.
+- `sentence2`: a `string` feature indicating the hypothesis.
+- `label`: a classification label, where possible values are `entailment`, `neutral`, `contradiction`.
+
+### Data Splits
+|   split   |count  |
+|----------|--------|
+|`train`|  381449 |
+|`validation`| 2419  |
+|`test`| 4895 |
+
+
+
+
+## Dataset Creation
+
+The dataset curation procedure was the same as the [XNLI](https://aclanthology.org/D18-1269/) dataset: we translated the [MultiNLI](https://aclanthology.org/N18-1101/) training data using the English to Bangla translation model introduced [here](https://aclanthology.org/2020.emnlp-main.207/). Due to the possibility of incursions of error during automatic translation, we used the [Language-Agnostic BERT Sentence Embeddings (LaBSE)](https://arxiv.org/abs/2007.01852) of the translations and original sentences to compute their similarity. All sentences below a similarity thresholdof 0.70 were discarded.
+
+### Curation Rationale
+
+[More information needed](https://github.com/csebuetnlp/banglabert)
+
+### Source Data
+
+[XNLI](https://aclanthology.org/D18-1269/)
+
+#### Initial Data Collection and Normalization
+
+[More information needed](https://github.com/csebuetnlp/banglabert)
+
+
+#### Who are the source language producers?
+
+[More information needed](https://github.com/csebuetnlp/banglabert)
+
+
+### Annotations
+
+[More information needed](https://github.com/csebuetnlp/banglabert)
+
+
+#### Annotation process
+
+[More information needed](https://github.com/csebuetnlp/banglabert)
+
+#### Who are the annotators?
+
+[More information needed](https://github.com/csebuetnlp/banglabert)
+
+### Personal and Sensitive Information
+
+[More information needed](https://github.com/csebuetnlp/banglabert)
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[More information needed](https://github.com/csebuetnlp/banglabert)
+
+### Discussion of Biases
+
+[More information needed](https://github.com/csebuetnlp/banglabert)
+
+### Other Known Limitations
+
+[More information needed](https://github.com/csebuetnlp/banglabert)
+
+## Additional Information
+
+### Dataset Curators
+
+[More information needed](https://github.com/csebuetnlp/banglabert)
+
+### 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 the dataset, please cite the following paper:
+```
+@misc{bhattacharjee2021banglabert,
+      title={BanglaBERT: Combating Embedding Barrier in Multilingual Models for Low-Resource Language Understanding},
+      author={Abhik Bhattacharjee and Tahmid Hasan and Kazi Samin and Md Saiful Islam and M. Sohel Rahman and Anindya Iqbal and Rifat Shahriyar},
+      year={2021},
+      eprint={2101.00204},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+```
+
+
+### Contributions
+
+Thanks to [@abhik1505040](https://github.com/abhik1505040) and [@Tahmid](https://github.com/Tahmid04) for adding this dataset.

dataset_infos.json

@@ -0,0 +1 @@
+{"xnli_bn": {"description": "This is a Natural Language Inference (NLI) dataset for Bengali, curated using the subset of\nMNLI data used in XNLI and state-of-the-art English to Bengali translation model.\n", "citation": "@misc{bhattacharjee2021banglabert,\n      title={BanglaBERT: Combating Embedding Barrier in Multilingual Models for Low-Resource Language Understanding},\n      author={Abhik Bhattacharjee and Tahmid Hasan and Kazi Samin and Md Saiful Islam and M. Sohel Rahman and Anindya Iqbal and Rifat Shahriyar},\n      year={2021},\n      eprint={2101.00204},\n      archivePrefix={arXiv},\n      primaryClass={cs.CL}\n}\n", "homepage": "https://github.com/csebuetnlp/banglabert", "license": "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0)", "features": {"sentence1": {"dtype": "string", "id": null, "_type": "Value"}, "sentence2": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 3, "names": ["contradiction", "entailment", "neutral"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "xnli_bn", "config_name": "xnli_bn", "version": {"version_str": "0.0.1", "description": null, "major": 0, "minor": 0, "patch": 1}, "splits": {"train": {"name": "train", "num_bytes": 175660643, "num_examples": 381449, "dataset_name": "xnli_bn"}, "test": {"name": "test", "num_bytes": 2127035, "num_examples": 4895, "dataset_name": "xnli_bn"}, "validation": {"name": "validation", "num_bytes": 1046988, "num_examples": 2419, "dataset_name": "xnli_bn"}}, "download_checksums": {"https://huggingface.co/datasets/csebuetnlp/xnli_bn/resolve/main/data/xnli_bn.tar.bz2": {"num_bytes": 21437836, "checksum": "a91b4d3f8433a98fd6251396976b17b2385ef49ffbb207fabe8124fc6b066207"}}, "download_size": 21437836, "post_processing_size": null, "dataset_size": 178834666, "size_in_bytes": 200272502}}

xnli_bn.py

@@ -1,10 +1,13 @@
 """XNLI Bengali dataset"""
 import json
 import os
+
 import datasets
+
+
 _CITATION = """\
 @misc{bhattacharjee2021banglabert,
-      title={BanglaBERT: Combating Embedding Barrier in Multilingual Models for Low-Resource Language Understanding}, 
+      title={BanglaBERT: Combating Embedding Barrier in Multilingual Models for Low-Resource Language Understanding},
       author={Abhik Bhattacharjee and Tahmid Hasan and Kazi Samin and Md Saiful Islam and M. Sohel Rahman and Anindya Iqbal and Rifat Shahriyar},
       year={2021},
       eprint={2101.00204},
@@ -13,25 +16,32 @@ _CITATION = """\
 }
 """
 _DESCRIPTION = """\
-This is a Natural Language Inference (NLI) dataset for Bengali, curated using the subset of 
-MNLI data used in XNLI and state-of-the-art English to Bengali translation model. 
+This is a Natural Language Inference (NLI) dataset for Bengali, curated using the subset of
+MNLI data used in XNLI and state-of-the-art English to Bengali translation model.
 """
 _HOMEPAGE = "https://github.com/csebuetnlp/banglabert"
 _LICENSE = "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0)"
 _URL = "https://huggingface.co/datasets/csebuetnlp/xnli_bn/resolve/main/data/xnli_bn.tar.bz2"
 _VERSION = datasets.Version("0.0.1")
 
+
 class XnliBn(datasets.GeneratorBasedBuilder):
     """XNLI Bengali dataset"""
 
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name="xnli_bn",
+            version=_VERSION,
+            description=_DESCRIPTION,
+        )
+    ]
+
     def _info(self):
         features = datasets.Features(
             {
                 "sentence1": datasets.Value("string"),
                 "sentence2": datasets.Value("string"),
-                "label": datasets.features.ClassLabel(
-                    names=["contradiction", "entailment", "neurtral"]
-                ),
+                "label": datasets.features.ClassLabel(names=["contradiction", "entailment", "neutral"]),
             }
         )
         return datasets.DatasetInfo(
@@ -40,12 +50,12 @@ class XnliBn(datasets.GeneratorBasedBuilder):
             homepage=_HOMEPAGE,
             license=_LICENSE,
             citation=_CITATION,
-            version=_VERSION
+            version=_VERSION,
         )
 
     def _split_generators(self, dl_manager):
         """Returns SplitGenerators."""
-        data_dir = dl_manager.download_and_extract(_URL)
+        data_dir = os.path.join(dl_manager.download_and_extract(_URL), "xnli_bn")
         return [
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
@@ -72,8 +82,4 @@ class XnliBn(datasets.GeneratorBasedBuilder):
         with open(filepath, encoding="utf-8") as f:
             for idx_, row in enumerate(f):
                 data = json.loads(row)
-                yield idx_, {
-                    "sentence1": data["sentence1"],
-                    "sentence2": data["sentence2"],
-                    "label": data["label"]
-                }
+                yield idx_, {"sentence1": data["sentence1"], "sentence2": data["sentence2"], "label": data["label"]}