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README.md

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----
-annotations_creators:
-- crowdsourced
-language_creators:
-- machine-generated
-- expert-generated
-language:
-- ko
-license:
-- cc-by-sa-4.0
-multilinguality:
-- monolingual
-size_categories:
-- 100K<n<1M
-source_datasets:
-- extended|multi_nli
-- extended|snli
-- extended|xnli
-task_categories:
-- text-classification
-task_ids:
-- natural-language-inference
-- multi-input-text-classification
-paperswithcode_id: kornli
-pretty_name: KorNLI
-dataset_info:
-- config_name: multi_nli
-  features:
-  - name: premise
-    dtype: string
-  - name: hypothesis
-    dtype: string
-  - name: label
-    dtype:
-      class_label:
-        names:
-          0: entailment
-          1: neutral
-          2: contradiction
-  splits:
-  - name: train
-    num_bytes: 84729207
-    num_examples: 392702
-  download_size: 42113232
-  dataset_size: 84729207
-- config_name: snli
-  features:
-  - name: premise
-    dtype: string
-  - name: hypothesis
-    dtype: string
-  - name: label
-    dtype:
-      class_label:
-        names:
-          0: entailment
-          1: neutral
-          2: contradiction
-  splits:
-  - name: train
-    num_bytes: 80137097
-    num_examples: 550152
-  download_size: 42113232
-  dataset_size: 80137097
-- config_name: xnli
-  features:
-  - name: premise
-    dtype: string
-  - name: hypothesis
-    dtype: string
-  - name: label
-    dtype:
-      class_label:
-        names:
-          0: entailment
-          1: neutral
-          2: contradiction
-  splits:
-  - name: validation
-    num_bytes: 518830
-    num_examples: 2490
-  - name: test
-    num_bytes: 1047437
-    num_examples: 5010
-  download_size: 42113232
-  dataset_size: 1566267
----
-
-# Dataset Card for "kor_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
-
-- **Homepage:** [https://github.com/kakaobrain/KorNLUDatasets](https://github.com/kakaobrain/KorNLUDatasets)
-- **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-- **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-- **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-- **Size of downloaded dataset files:** 120.49 MB
-- **Size of the generated dataset:** 158.72 MB
-- **Total amount of disk used:** 279.21 MB
-
-### Dataset Summary
-
-Korean Natural Language Inference datasets.
-
-### Supported Tasks and Leaderboards
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-### Languages
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-## Dataset Structure
-
-### Data Instances
-
-#### multi_nli
-
-- **Size of downloaded dataset files:** 40.16 MB
-- **Size of the generated dataset:** 80.80 MB
-- **Total amount of disk used:** 120.97 MB
-
-An example of 'train' looks as follows.
-```
-
-```
-
-#### snli
-
-- **Size of downloaded dataset files:** 40.16 MB
-- **Size of the generated dataset:** 76.42 MB
-- **Total amount of disk used:** 116.59 MB
-
-An example of 'train' looks as follows.
-```
-
-```
-
-#### xnli
-
-- **Size of downloaded dataset files:** 40.16 MB
-- **Size of the generated dataset:** 1.49 MB
-- **Total amount of disk used:** 41.66 MB
-
-An example of 'validation' looks as follows.
-```
-
-```
-
-### Data Fields
-
-The data fields are the same among all splits.
-
-#### multi_nli
-- `premise`: a `string` feature.
-- `hypothesis`: a `string` feature.
-- `label`: a classification label, with possible values including `entailment` (0), `neutral` (1), `contradiction` (2).
-
-#### snli
-- `premise`: a `string` feature.
-- `hypothesis`: a `string` feature.
-- `label`: a classification label, with possible values including `entailment` (0), `neutral` (1), `contradiction` (2).
-
-#### xnli
-- `premise`: a `string` feature.
-- `hypothesis`: a `string` feature.
-- `label`: a classification label, with possible values including `entailment` (0), `neutral` (1), `contradiction` (2).
-
-### Data Splits
-
-#### multi_nli
-
-|         |train |
-|---------|-----:|
-|multi_nli|392702|
-
-#### snli
-
-|    |train |
-|----|-----:|
-|snli|550152|
-
-#### xnli
-
-|    |validation|test|
-|----|---------:|---:|
-|xnli|      2490|5010|
-
-## Dataset Creation
-
-### Curation Rationale
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-### Source Data
-
-#### Initial Data Collection and Normalization
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-#### Who are the source language producers?
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-### Annotations
-
-#### Annotation process
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-#### Who are the annotators?
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-### Personal and Sensitive Information
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-## Considerations for Using the Data
-
-### Social Impact of Dataset
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-### Discussion of Biases
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-### Other Known Limitations
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-## Additional Information
-
-### Dataset Curators
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-### Licensing Information
-
-The dataset is licensed under Creative Commons [Attribution-ShareAlike license (CC BY-SA 4.0)](http://creativecommons.org/licenses/by-sa/4.0/).
-
-### Citation Information
-
-```
-@article{ham2020kornli,
-  title={KorNLI and KorSTS: New Benchmark Datasets for Korean Natural Language Understanding},
-  author={Ham, Jiyeon and Choe, Yo Joong and Park, Kyubyong and Choi, Ilji and Soh, Hyungjoon},
-  journal={arXiv preprint arXiv:2004.03289},
-  year={2020}
-}
-
-```
-
-
-### Contributions
-
-Thanks to [@thomwolf](https://github.com/thomwolf), [@lhoestq](https://github.com/lhoestq), [@lewtun](https://github.com/lewtun), [@patrickvonplaten](https://github.com/patrickvonplaten) for adding this dataset.

dataset_infos.json

@@ -1 +0,0 @@
-{"multi_nli": {"description": " Korean Natural  Language Inference datasets\n", "citation": "@article{ham2020kornli,\n  title={KorNLI and KorSTS: New Benchmark Datasets for Korean Natural Language Understanding},\n  author={Ham, Jiyeon and Choe, Yo Joong and Park, Kyubyong and Choi, Ilji and Soh, Hyungjoon},\n  journal={arXiv preprint arXiv:2004.03289},\n  year={2020}\n}\n", "homepage": "https://github.com/kakaobrain/KorNLUDatasets", "license": "", "features": {"premise": {"dtype": "string", "id": null, "_type": "Value"}, "hypothesis": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 3, "names": ["entailment", "neutral", "contradiction"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": null, "builder_name": "kor_nli", "config_name": "multi_nli", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 84729207, "num_examples": 392702, "dataset_name": "kor_nli"}}, "download_checksums": {"https://github.com/kakaobrain/KorNLUDatasets/archive/master.zip": {"num_bytes": 42113232, "checksum": "b1184d5e78a7d988400eabe3374b8a7e2abf182896f54e6e311c5173bb2c9bf5"}}, "download_size": 42113232, "post_processing_size": null, "dataset_size": 84729207, "size_in_bytes": 126842439}, "snli": {"description": " Korean Natural  Language Inference datasets\n", "citation": "@article{ham2020kornli,\n  title={KorNLI and KorSTS: New Benchmark Datasets for Korean Natural Language Understanding},\n  author={Ham, Jiyeon and Choe, Yo Joong and Park, Kyubyong and Choi, Ilji and Soh, Hyungjoon},\n  journal={arXiv preprint arXiv:2004.03289},\n  year={2020}\n}\n", "homepage": "https://github.com/kakaobrain/KorNLUDatasets", "license": "", "features": {"premise": {"dtype": "string", "id": null, "_type": "Value"}, "hypothesis": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 3, "names": ["entailment", "neutral", "contradiction"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": null, "builder_name": "kor_nli", "config_name": "snli", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 80137097, "num_examples": 550152, "dataset_name": "kor_nli"}}, "download_checksums": {"https://github.com/kakaobrain/KorNLUDatasets/archive/master.zip": {"num_bytes": 42113232, "checksum": "b1184d5e78a7d988400eabe3374b8a7e2abf182896f54e6e311c5173bb2c9bf5"}}, "download_size": 42113232, "post_processing_size": null, "dataset_size": 80137097, "size_in_bytes": 122250329}, "xnli": {"description": " Korean Natural  Language Inference datasets\n", "citation": "@article{ham2020kornli,\n  title={KorNLI and KorSTS: New Benchmark Datasets for Korean Natural Language Understanding},\n  author={Ham, Jiyeon and Choe, Yo Joong and Park, Kyubyong and Choi, Ilji and Soh, Hyungjoon},\n  journal={arXiv preprint arXiv:2004.03289},\n  year={2020}\n}\n", "homepage": "https://github.com/kakaobrain/KorNLUDatasets", "license": "", "features": {"premise": {"dtype": "string", "id": null, "_type": "Value"}, "hypothesis": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 3, "names": ["entailment", "neutral", "contradiction"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": null, "builder_name": "kor_nli", "config_name": "xnli", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"validation": {"name": "validation", "num_bytes": 518830, "num_examples": 2490, "dataset_name": "kor_nli"}, "test": {"name": "test", "num_bytes": 1047437, "num_examples": 5010, "dataset_name": "kor_nli"}}, "download_checksums": {"https://github.com/kakaobrain/KorNLUDatasets/archive/master.zip": {"num_bytes": 42113232, "checksum": "b1184d5e78a7d988400eabe3374b8a7e2abf182896f54e6e311c5173bb2c9bf5"}}, "download_size": 42113232, "post_processing_size": null, "dataset_size": 1566267, "size_in_bytes": 43679499}}

kor_nli.py

@@ -1,121 +0,0 @@
-"""TODO(kor_nli): Add a description here."""
-
-
-import os
-
-import datasets
-
-
-# TODO(kor_nli): BibTeX citation
-_CITATION = """\
-@article{ham2020kornli,
-  title={KorNLI and KorSTS: New Benchmark Datasets for Korean Natural Language Understanding},
-  author={Ham, Jiyeon and Choe, Yo Joong and Park, Kyubyong and Choi, Ilji and Soh, Hyungjoon},
-  journal={arXiv preprint arXiv:2004.03289},
-  year={2020}
-}
-"""
-
-# TODO(kor_nli):
-_DESCRIPTION = """ Korean Natural  Language Inference datasets
-"""
-_URL = "https://github.com/kakaobrain/KorNLUDatasets/archive/master.zip"
-
-
-class KorNLIConfig(datasets.BuilderConfig):
-    """BuilderConfig for KorNLI."""
-
-    def __init__(self, **kwargs):
-        """BuilderConfig for KorNLI.
-
-        Args:
-
-          **kwargs: keyword arguments forwarded to super.
-        """
-        # Version 1.1.0 remove empty document and summary strings.
-        super(KorNLIConfig, self).__init__(version=datasets.Version("1.0.0"), **kwargs)
-
-
-class KorNli(datasets.GeneratorBasedBuilder):
-    """TODO(kor_nli): Short description of my dataset."""
-
-    # TODO(kor_nli): Set up version.
-    VERSION = datasets.Version("1.0.0")
-    BUILDER_CONFIGS = [
-        KorNLIConfig(name="multi_nli", description="Korean multi NLI datasets"),
-        KorNLIConfig(name="snli", description="Korean SNLI dataset"),
-        KorNLIConfig(name="xnli", description="Korean XNLI dataset"),
-    ]
-
-    def _info(self):
-        # TODO(kor_nli): Specifies the datasets.DatasetInfo object
-        return datasets.DatasetInfo(
-            # This is the description that will appear on the datasets page.
-            description=_DESCRIPTION,
-            # datasets.features.FeatureConnectors
-            features=datasets.Features(
-                {
-                    # These are the features of your dataset like images, labels ...
-                    "premise": datasets.Value("string"),
-                    "hypothesis": datasets.Value("string"),
-                    "label": datasets.ClassLabel(names=["entailment", "neutral", "contradiction"]),
-                }
-            ),
-            # If there's a common (input, target) tuple from the features,
-            # specify them here. They'll be used if as_supervised=True in
-            # builder.as_dataset.
-            supervised_keys=None,
-            # Homepage of the dataset for documentation
-            homepage="https://github.com/kakaobrain/KorNLUDatasets",
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        # TODO(kor_nli): Downloads the data and defines the splits
-        # dl_manager is a datasets.download.DownloadManager that can be used to
-        # download and extract URLs
-        dl_dir = dl_manager.download_and_extract(_URL)
-        dl_dir = os.path.join(dl_dir, "KorNLUDatasets-master", "KorNLI")
-        if self.config.name == "multi_nli":
-            return [
-                datasets.SplitGenerator(
-                    name=datasets.Split.TRAIN,
-                    # These kwargs will be passed to _generate_examples
-                    gen_kwargs={"filepath": os.path.join(dl_dir, "multinli.train.ko.tsv")},
-                ),
-            ]
-        elif self.config.name == "snli":
-            return [
-                datasets.SplitGenerator(
-                    name=datasets.Split.TRAIN,
-                    # These kwargs will be passed to _generate_examples
-                    gen_kwargs={"filepath": os.path.join(dl_dir, "snli_1.0_train.ko.tsv")},
-                ),
-            ]
-        else:
-            return [
-                datasets.SplitGenerator(
-                    name=datasets.Split.VALIDATION,
-                    # These kwargs will be passed to _generate_examples
-                    gen_kwargs={"filepath": os.path.join(dl_dir, "xnli.dev.ko.tsv")},
-                ),
-                datasets.SplitGenerator(
-                    name=datasets.Split.TEST,
-                    # These kwargs will be passed to _generate_examples
-                    gen_kwargs={"filepath": os.path.join(dl_dir, "xnli.test.ko.tsv")},
-                ),
-            ]
-
-    def _generate_examples(self, filepath):
-        """Yields examples."""
-        # TODO(kor_nli): Yields (key, example) tuples from the dataset
-        with open(filepath, encoding="utf-8") as f:
-            next(f)  # skip headers
-            columns = ("premise", "hypothesis", "label")
-            for id_, row in enumerate(f):
-                row = row.strip().split("\t")
-                if len(row) != 3:
-                    continue
-                row = dict(zip(columns, row))
-                yield id_, row

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