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adding masakhanews

README.md

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 ---
-license: afl-3.0
+annotations_creators:
+- expert-generated
+language:
+- am
+- en
+- fr
+- ha
+- ig
+- ln
+- lg
+- om
+- pcm
+- rn
+- sn
+- so
+- sw
+- ti
+- xh
+- yo
+language_creators:
+- expert-generated
+license:
+- afl-3.0
+multilinguality:
+- multilingual
+pretty_name: masakhanews
+size_categories:
+- 1K<n<10K
+source_datasets:
+- original
+tags:
+- news-topic
+- masakhanews
+- masakhane
+task_categories:
+- text-classification
+task_ids:
+- topic-classification
+
 ---
+
+
+# Dataset Card for [Dataset Name]
+
+## Table of Contents
+- [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)
+  - [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
+
+- **Homepage:** [homepage](https://github.com/masakhane-io/masakhane-news)
+- **Repository:** [github](https://github.com/masakhane-io/masakhane-news)
+- **Paper:** [paper]()
+- **Point of Contact:** [Masakhane](https://www.masakhane.io/) or didelani@lsv.uni-saarland.de
+
+### Dataset Summary
+
+MasakhaNEWS is the largest publicly available dataset for news topic classification in 16 languages widely spoken in Africa.
+
+
+The train/validation/test sets are available for all the 16 languages.
+
+
+
+### Supported Tasks and Leaderboards
+
+[More Information Needed]
+
+- `named-entity-recognition`: The performance in this task is measured with [F1](https://huggingface.co/metrics/f1) (higher is better). A named entity is correct only if it is an exact match of the corresponding entity in the data.
+
+### Languages
+
+There are 16 languages available :
+- Amharic (amh)
+- English (eng)
+- French (fra)
+- Hausa (hau)
+- Igbo (ibo)
+- Lingala (lin)
+- Luganda (lug)
+- Oromo (orm)
+- Nigerian Pidgin (pcm)
+- Rundi (run)
+- chShona (sna)
+- Somali (som)
+- Kiswahili (swą)
+- Tigrinya (tir)
+- isiXhosa (xho)
+- Yorùbá (yor)
+
+## Dataset Structure
+
+### Data Instances
+
+The examples look like this for Yorùbá:
+
+```
+from datasets import load_dataset
+data = load_dataset('masakhanews', 'yor') 
+
+# Please, specify the language code
+
+# A data point example is below:
+
+{
+'label': 0, 
+'headline': "'The barriers to entry have gone - go for it now'", 
+'text': "j Lalvani, CEO of Vitabiotics and former Dragons' Den star, shares his business advice for our CEO Secrets series.\nProduced, filmed and edited by Dougal Shaw", 
+'headline_text': "'The barriers to entry have gone - go for it now' j Lalvani, CEO of Vitabiotics and former Dragons' Den star, shares his business advice for our CEO Secrets series.\nProduced, filmed and edited by Dougal Shaw", 
+'url': '/news/business-61880859'
+}
+```
+
+### Data Fields
+
+- `label`: news topic id
+- `headline`: news title/headline
+- `text`: news body
+- `headline_text`: concatenation of headline and news body
+- `url`: website address
+
+The news topics correspond to this list:
+```
+"business", "entertainment", "health", "politics", "religion", "sports", "technology"
+```
+
+### Data Splits
+
+For all languages, there are three splits.
+
+The original splits were named `train`, `dev` and `test` and they correspond to the `train`, `validation` and `test` splits.
+
+The splits have the following sizes :
+
+| Language        | train | validation | test |
+|-----------------|------:|-----------:|-----:|
+| Amharic         |  1311 |        188 |  376 |
+| English         |  3309 |        472 |  948 |
+| French          |  1476 |        211 |  422 |
+| Hausa           |  2219 |        317 |  637 |
+| Igbo            |  1356 |        194 |  390 |
+| Lingala     	  |   608 |         87 |  175 |
+| Luganda         |   771 |        110 |  223 |
+| Oromo           |  1015 |        145 |  292 |
+| Nigerian-Pidgin |  1060 |        152 |  305 |
+| Rundi           |  1117 |        159 |  322 |
+| chiShona        |  1288 |        185 |  369 |
+| Somali          |  1021 |        148 |  294 |
+| Kiswahili       |  1658 |        237 |  476 |
+| Tigrinya        |   947 |        137 |  272 |
+| isiXhosa        |  1032 |        147 |  297 |
+| Yoruba          |  1433 |        206 |  411 |
+
+## Dataset Creation
+
+### Curation Rationale
+
+The dataset was introduced to introduce new resources to 20 languages that were under-served for natural language processing.
+
+[More Information Needed]
+
+### Source Data
+
+The source of the data is from the news domain, details can be found here ****
+
+#### Initial Data Collection and Normalization
+
+The articles were word-tokenized, information on the exact pre-processing pipeline is unavailable.
+
+#### Who are the source language producers?
+
+The source language was produced by journalists and writers employed by the news agency and newspaper mentioned above.
+
+### Annotations
+
+#### Annotation process
+
+Details can be found here **
+
+#### Who are the annotators?
+
+Annotators were recruited from [Masakhane](https://www.masakhane.io/)
+
+### Personal and Sensitive Information
+
+The data is sourced from newspaper source and only contains mentions of public figures or individuals
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+[More Information Needed]
+
+
+### Discussion of Biases
+[More Information Needed]
+
+
+### Other Known Limitations
+
+Users should keep in mind that the dataset only contains news text, which might limit the applicability of the developed systems to other domains.
+
+## Additional Information
+
+### Dataset Curators
+
+
+### Licensing Information
+
+The licensing status of the data is CC 4.0 Non-Commercial
+
+### Citation Information
+
+Provide the [BibTex](http://www.bibtex.org/)-formatted reference for the dataset. For example:
+```
+@article{Adelani2023MasakhaNEWS,
+  title={MasakhaNEWS: News Topic Classification for African languages},
+  author={David Ifeoluwa Adelani and  Marek Masiak and  Israel Abebe Azime and  Jesujoba Oluwadara Alabi and  Atnafu Lambebo Tonja and  Christine Mwase and  Odunayo Ogundepo and  Bonaventure F. P. Dossou and  Akintunde Oladipo and  Doreen Nixdorf and  Chris Chinenye Emezue and  Sana Sabah al-azzawi and  Blessing K. Sibanda and  Davis David and  Lolwethu Ndolela and  Jonathan Mukiibi and  Tunde Oluwaseyi Ajayi and  Tatiana Moteu Ngoli and  Brian Odhiambo and  Abraham Toluwase Owodunni and  Nnaemeka C. Obiefuna and  Shamsuddeen Hassan Muhammad and  Saheed Salahudeen Abdullahi and  Mesay Gemeda Yigezu and  Tajuddeen Gwadabe and  Idris Abdulmumin and  Mahlet Taye Bame and  Oluwabusayo Olufunke Awoyomi and  Iyanuoluwa Shode and  Tolulope Anu Adelani and  Habiba Abdulganiy Kailani and  Abdul-Hakeem Omotayo and  Adetola Adeeko and  Afolabi Abeeb and  Anuoluwapo Aremu and  Olanrewaju Samuel and  Clemencia Siro and  Wangari Kimotho and  Onyekachi Raphael Ogbu and  Chinedu E. Mbonu and  Chiamaka I. Chukwuneke and  Samuel Fanijo and  Jessica Ojo and  Oyinkansola F. Awosan and  Tadesse Kebede Guge and  Sakayo Toadoum Sari and  Pamela Nyatsine and  Freedmore Sidume and  Oreen Yousuf and  Mardiyyah Oduwole and  Ussen Kimanuka and  Kanda Patrick Tshinu and  Thina Diko and  Siyanda Nxakama and   Abdulmejid Tuni Johar and  Sinodos Gebre and  Muhidin Mohamed and  Shafie Abdi Mohamed and  Fuad Mire Hassan and  Moges Ahmed Mehamed and  Evrard Ngabire and  and Pontus Stenetorp},
+  journal={ArXiv},
+  year={2023},
+  volume={}
+}
+```
+
+### Contributions
+
+Thanks to [@dadelani](https://github.com/dadelani) for adding this dataset.

masakhanews.py

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+# coding=utf-8
+# Copyright 2020 HuggingFace Datasets Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# Lint as: python3
+"""MasakhaNEWS: News Topic Classification for African languages"""
+
+import datasets
+import pandas
+import pandas as pd
+
+logger = datasets.logging.get_logger(__name__)
+
+
+_CITATION = """\
+@article{Adelani2023MasakhaNEWS,
+  title={MasakhaNEWS: News Topic Classification for African languages},
+  author={David Ifeoluwa Adelani and  Marek Masiak and  Israel Abebe Azime and  Jesujoba Oluwadara Alabi and  Atnafu Lambebo Tonja and  Christine Mwase and  Odunayo Ogundepo and  Bonaventure F. P. Dossou and  Akintunde Oladipo and  Doreen Nixdorf and  Chris Chinenye Emezue and  Sana Sabah al-azzawi and  Blessing K. Sibanda and  Davis David and  Lolwethu Ndolela and  Jonathan Mukiibi and  Tunde Oluwaseyi Ajayi and  Tatiana Moteu Ngoli and  Brian Odhiambo and  Abraham Toluwase Owodunni and  Nnaemeka C. Obiefuna and  Shamsuddeen Hassan Muhammad and  Saheed Salahudeen Abdullahi and  Mesay Gemeda Yigezu and  Tajuddeen Gwadabe and  Idris Abdulmumin and  Mahlet Taye Bame and  Oluwabusayo Olufunke Awoyomi and  Iyanuoluwa Shode and  Tolulope Anu Adelani and  Habiba Abdulganiy Kailani and  Abdul-Hakeem Omotayo and  Adetola Adeeko and  Afolabi Abeeb and  Anuoluwapo Aremu and  Olanrewaju Samuel and  Clemencia Siro and  Wangari Kimotho and  Onyekachi Raphael Ogbu and  Chinedu E. Mbonu and  Chiamaka I. Chukwuneke and  Samuel Fanijo and  Jessica Ojo and  Oyinkansola F. Awosan and  Tadesse Kebede Guge and  Sakayo Toadoum Sari and  Pamela Nyatsine and  Freedmore Sidume and  Oreen Yousuf and  Mardiyyah Oduwole and  Ussen Kimanuka and  Kanda Patrick Tshinu and  Thina Diko and  Siyanda Nxakama and   Abdulmejid Tuni Johar and  Sinodos Gebre and  Muhidin Mohamed and  Shafie Abdi Mohamed and  Fuad Mire Hassan and  Moges Ahmed Mehamed and  Evrard Ngabire and  and Pontus Stenetorp},
+  journal={ArXiv},
+  year={2023},
+  volume={}
+}
+"""
+
+_DESCRIPTION = """\
+MasakhaNEWS is the largest publicly available dataset for news topic classification in 16 languages widely spoken in Africa.
+
+The languages are:
+- Amharic (amh)
+- English (eng)
+- French (fra)
+- Hausa (hau)
+- Igbo (ibo)
+- Lingala (lin)
+- Luganda (lug)
+- Oromo (orm)
+- Nigerian Pidgin (pcm)
+- Rundi (run)
+- chShona (sna)
+- Somali (som)
+- Kiswahili (swą)
+- Tigrinya (tir)
+- isiXhosa (xho)
+- Yorùbá (yor)
+
+The train/validation/test sets are available for all the 16 languages.
+
+For more details see *** arXiv link **
+"""
+_URL = "https://github.com/masakhane-io/masakhane-news/raw/main/data/"
+_TRAINING_FILE = "train.tsv"
+_DEV_FILE = "dev.tsv"
+_TEST_FILE = "test.tsv"
+
+
+class MasakhanewsConfig(datasets.BuilderConfig):
+    """BuilderConfig for Masakhanews"""
+
+    def __init__(self, **kwargs):
+        """BuilderConfig for Masakhanews.
+
+        Args:
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(MasakhanewsConfig, self).__init__(**kwargs)
+
+
+class Masakhanews(datasets.GeneratorBasedBuilder):
+    """Masakhanews dataset."""
+
+    BUILDER_CONFIGS = [
+        MasakhanewsConfig(name="amh", version=datasets.Version("1.0.0"), description="Masakhanews Amharic dataset"),
+        MasakhanewsConfig(name="eng", version=datasets.Version("1.0.0"), description="Masakhanews English dataset"),
+        MasakhanewsConfig(name="fra", version=datasets.Version("1.0.0"), description="Masakhanews French dataset"),
+        MasakhanewsConfig(name="hau", version=datasets.Version("1.0.0"), description="Masakhanews Hausa dataset"),
+        MasakhanewsConfig(name="ibo", version=datasets.Version("1.0.0"), description="Masakhanews Igbo dataset"),
+        MasakhanewsConfig(name="lin", version=datasets.Version("1.0.0"), description="Masakhanews Lingala dataset"),
+        MasakhanewsConfig(name="lug", version=datasets.Version("1.0.0"), description="Masakhanews Luganda dataset"),
+        MasakhanewsConfig(name="orm", version=datasets.Version("1.0.0"), description="Masakhanews Oromo dataset"),
+        MasakhanewsConfig(
+            name="pcm", version=datasets.Version("1.0.0"), description="Masakhanews Nigerian-Pidgin dataset"
+        ),
+        MasakhanewsConfig(name="run", version=datasets.Version("1.0.0"), description="Masakhanews Rundi dataset"),
+        MasakhanewsConfig(name="sna", version=datasets.Version("1.0.0"), description="Masakhanews Shona dataset"),
+        MasakhanewsConfig(name="som", version=datasets.Version("1.0.0"), description="Masakhanews Somali dataset"),
+        MasakhanewsConfig(name="swa", version=datasets.Version("1.0.0"), description="Masakhanews Swahili dataset"),
+        MasakhanewsConfig(name="tir", version=datasets.Version("1.0.0"), description="Masakhanews Tigrinya dataset"),
+        MasakhanewsConfig(name="xho", version=datasets.Version("1.0.0"), description="Masakhanews Xhosa dataset"),
+        MasakhanewsConfig(name="yor", version=datasets.Version("1.0.0"), description="Masakhanews Yoruba dataset"),
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "label": datasets.features.ClassLabel(
+                        names=["business", "entertainment", "health", "politics", "religion", "sports", "technology"]
+                    ),
+                    "headline": datasets.Value("string"),
+                    "text": datasets.Value("string"),
+                    "headline_text": datasets.Value("string"),
+                    "url": datasets.Value("string"),
+                }
+            ),
+            supervised_keys=None,
+            homepage="https://github.com/masakhane-io/masakhane-news",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        urls_to_download = {
+            "train": f"{_URL}{self.config.name}/{_TRAINING_FILE}",
+            "dev": f"{_URL}{self.config.name}/{_DEV_FILE}",
+            "test": f"{_URL}{self.config.name}/{_TEST_FILE}",
+        }
+        downloaded_files = dl_manager.download_and_extract(urls_to_download)
+
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
+            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}),
+            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]}),
+        ]
+
+    def _generate_examples(self, filepath):
+        logger.info("⏳ Generating examples from = %s", filepath)
+        df = pd.read_csv(filepath, sep='\t')
+        N = df.shape[0]
+
+        for id_ in range(N):
+            yield id_, {
+                "label": df['category'].iloc[id_],
+                "headline": df['headline'].iloc[id_],
+                "text": df['text'].iloc[id_],
+                "headline_text":  df['headline'].iloc[id_] + ' ' + df['text'].iloc[id_],
+                "url": df['url'].iloc[id_],
+            }
+
+
+