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.gitignore

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-
-hftrain_en.json
-hfeval_es.json

README.md

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----
-YAML tags:
-annotations_creators:
-- automatically-generated
-language_creators:
-- found
-language:
-- es
-license:
-- cc-by-sa-3.0
-multilinguality:
-- monolingual
-pretty_name: wikicat_esv2
-size_categories:
-- unknown
-source_datasets: []
-task_categories:
-- text-classification
-task_ids:
-- multi-class-classification
----
-
-# WikiCAT_ca: Spanish Text Classification dataset
-
-
-## Dataset Description
-
-- **Paper:** 
-
-- **Point of Contact:** [email protected]
-
-
-**Repository**
-
-
-
-
-### Dataset Summary
-
-WikiCAT_ca is a Spanish corpus for thematic Text Classification tasks. It is created automatically from Wikipedia and Wikidata sources, and contains 8401 articles from the Viquipedia classified under 12 different categories.
-
-This dataset was developed by BSC TeMU as part of the PlanTL project, and intended as an evaluation of LT capabilities to generate useful synthetic corpus.
-
-### Supported Tasks and Leaderboards
-
-Text classification, Language Model
-
-### Languages
-
-ES- Spanish
-
-## Dataset Structure
-
-### Data Instances
-
-Two json files, one for each split.
-
-### Data Fields
-
-We used a simple model with the article text and associated labels, without further metadata.
-
-#### Example:
-
-<pre>
-{'sentence': 'La economía de Reunión se ha basado tradicionalmente en la agricultura. La caña de azúcar ha sido el cultivo principal durante más de un siglo, y en algunos años representa el 85% de las exportaciones. El gobierno ha estado impulsando el desarrollo de una industria turística para aliviar el alto desempleo, que representa más del 40% de la fuerza laboral.(...) El PIB total de la isla fue de 18.800 millones de dólares EE.UU. en 2007., 'label': 'Economía'}
-
-
-</pre>
-
-#### Labels
-
-'Religión', 'Entretenimiento', 'Música', 'Ciencia_y_Tecnología', 'Política', 'Economía', 'Matemáticas', 'Humanidades', 'Deporte', 'Derecho', 'Historia', 'Filosofía'
-
-### Data Splits
-
-* hfeval_esv5.json: 1681 label-document pairs
-* hftrain_esv5.json: 6716  label-document pairs
-
-
-## Dataset Creation
-
-### Methodology
-
-La páginas de "Categoría" representan los temas.
-para cada tema, extraemos las páginas asociadas a ese primer nivel de la jerarquía, y utilizamos el resúmen ("summary") como texto representativo.
-
-### Curation Rationale
-
-
-
-### Source Data
-
-#### Initial Data Collection and Normalization
-
-The source data are thematic categories in the different Wikipedias
-
-#### Who are the source language producers?
-
-
-### Annotations
-
-#### Annotation process
-Automatic annotation
-
-#### Who are the annotators?
-
-[N/A]
-
-### Personal and Sensitive Information
-
-No personal or sensitive information included.
-
-## Considerations for Using the Data
-
-### Social Impact of Dataset
-
-We hope this corpus contributes to the development of language models in Spanish.
-
-### Discussion of Biases
-
-We are aware that this data might contain biases. We have not applied any steps to reduce their impact.
-
-### Other Known Limitations
-
-[N/A]
-
-## Additional Information
-
-### Dataset Curators
-
-Text Mining Unit (TeMU) at the Barcelona Supercomputing Center ([email protected]). 
-
-For further information, send an email to ([email protected]).
-
-This work was funded by the [Spanish State Secretariat for Digitalization and Artificial Intelligence (SEDIA)](https://avancedigital.mineco.gob.es/en-us/Paginas/index.aspx) within the framework of the [Plan-TL](https://plantl.mineco.gob.es/Paginas/index.aspx).
-
-### Licensing Information
-
-This work is licensed under [CC Attribution 4.0 International](https://creativecommons.org/licenses/by/4.0/) License.
-
-Copyright by the Spanish State Secretariat for Digitalization and Artificial Intelligence (SEDIA) (2022)
-
-### Contributions
-
-[N/A]

WikiCAT_esv2.py

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-# Loading script for the TeCla dataset.
-import json
-import datasets
-
-logger = datasets.logging.get_logger(__name__)
-
-_CITATION = """
-
-            """
-
-_DESCRIPTION = """
-                   WikiCAT: Text Classification Spanish dataset from the Viquipedia
-
-               """
-
-_HOMEPAGE = """   """
-
-# TODO: upload datasets to github
-_URL = "https://huggingface.co/datasets/crodri/WikiCAT_esv2/resolve/main/"
-_TRAINING_FILE = "hftrain_esv5.json"
-_DEV_FILE = "hfeval_esv5.json"
-#_TEST_FILE = "test.json"
-
-
-class wikiCAT_esConfig(datasets.BuilderConfig):
-    """ Builder config for the Topicat dataset """
-
-    def __init__(self, **kwargs):
-        """BuilderConfig for wikiCAT_es.
-        Args:
-          **kwargs: keyword arguments forwarded to super.
-        """
-        super(wikiCAT_esConfig, self).__init__(**kwargs)
-
-
-class wikiCAT_es(datasets.GeneratorBasedBuilder):
-    """ wikiCAT_es Dataset """
-
-    BUILDER_CONFIGS = [
-        wikiCAT_esConfig(
-            name="wikiCAT_es",
-            version=datasets.Version("1.1.0"),
-            description="wikiCAT_es",
-        ),
-    ]
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "text": datasets.Value("string"),
-                    "label": datasets.features.ClassLabel
-                        (names= ['Religión', 'Entretenimiento', 'Música', 'Ciencia_y_Tecnología', 'Política', 'Economía', 'Matemáticas', 'Humanidades', 'Deporte', 'Derecho', 'Historia', 'Filosofía']
-                    ),
-                }
-            ),
-            homepage=_HOMEPAGE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        urls_to_download = {
-            "train": f"{_URL}{_TRAINING_FILE}",
-            "dev": f"{_URL}{_DEV_FILE}",
-#            "test": f"{_URL}{_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):
-        """This function returns the examples in the raw (text) form."""
-        logger.info("generating examples from = %s", filepath)
-        with open(filepath, encoding="utf-8") as f:
-            wikiCAT_es = json.load(f)
-            for id_, article in enumerate(wikiCAT_es["data"]):
-                text = article["sentence"]
-                label = article["label"]
-                yield id_, {
-                    "text": text,
-                    "label": label,
-                }

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