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README.md

@@ -1,327 +0,0 @@
----
-annotations_creators:
-- expert-generated
-language:
-- en
-language_creators:
-- found
-license:
-- other
-multilinguality:
-- monolingual
-pretty_name: RACE
-size_categories:
-- 10K<n<100K
-source_datasets:
-- original
-task_categories:
-- multiple-choice
-task_ids:
-- multiple-choice-qa
-paperswithcode_id: race
-dataset_info:
-- config_name: high
-  features:
-  - name: example_id
-    dtype: string
-  - name: article
-    dtype: string
-  - name: answer
-    dtype: string
-  - name: question
-    dtype: string
-  - name: options
-    sequence: string
-  splits:
-  - name: test
-    num_bytes: 6989121
-    num_examples: 3498
-  - name: train
-    num_bytes: 126243396
-    num_examples: 62445
-  - name: validation
-    num_bytes: 6885287
-    num_examples: 3451
-  download_size: 25443609
-  dataset_size: 140117804
-- config_name: middle
-  features:
-  - name: example_id
-    dtype: string
-  - name: article
-    dtype: string
-  - name: answer
-    dtype: string
-  - name: question
-    dtype: string
-  - name: options
-    sequence: string
-  splits:
-  - name: test
-    num_bytes: 1786297
-    num_examples: 1436
-  - name: train
-    num_bytes: 31065322
-    num_examples: 25421
-  - name: validation
-    num_bytes: 1761937
-    num_examples: 1436
-  download_size: 25443609
-  dataset_size: 34613556
-- config_name: all
-  features:
-  - name: example_id
-    dtype: string
-  - name: article
-    dtype: string
-  - name: answer
-    dtype: string
-  - name: question
-    dtype: string
-  - name: options
-    sequence: string
-  splits:
-  - name: test
-    num_bytes: 8775394
-    num_examples: 4934
-  - name: train
-    num_bytes: 157308694
-    num_examples: 87866
-  - name: validation
-    num_bytes: 8647200
-    num_examples: 4887
-  download_size: 25443609
-  dataset_size: 174731288
----
-
-# Dataset Card for "race"
-
-## 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:** [http://www.cs.cmu.edu/~glai1/data/race/](http://www.cs.cmu.edu/~glai1/data/race/)
-- **Repository:** https://github.com/qizhex/RACE_AR_baselines
-- **Paper:** [RACE: Large-scale ReAding Comprehension Dataset From Examinations](https://arxiv.org/abs/1704.04683)
-- **Point of Contact:** [Guokun Lai](mailto:guokun@cs.cmu.edu), [Qizhe Xie](mailto:qzxie@cs.cmu.edu)
-- **Size of downloaded dataset files:** 72.79 MB
-- **Size of the generated dataset:** 333.27 MB
-- **Total amount of disk used:** 406.07 MB
-
-### Dataset Summary
-
-RACE is a large-scale reading comprehension dataset with more than 28,000 passages and nearly 100,000 questions. The
- dataset is collected from English examinations in China, which are designed for middle school and high school students.
-The dataset can be served as the training and test sets for machine comprehension.
-
-### 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
-
-#### all
-
-- **Size of downloaded dataset files:** 24.26 MB
-- **Size of the generated dataset:** 166.64 MB
-- **Total amount of disk used:** 190.90 MB
-
-An example of 'train' looks as follows.
-```
-This example was too long and was cropped:
-
-{
-    "answer": "A",
-    "article": "\"Schoolgirls have been wearing such short skirts at Paget High School in Branston that they've been ordered to wear trousers ins...",
-    "example_id": "high132.txt",
-    "options": ["short skirts give people the impression of sexualisation", "short skirts are too expensive for parents to afford", "the headmaster doesn't like girls wearing short skirts", "the girls wearing short skirts will be at the risk of being laughed at"],
-    "question": "The girls at Paget High School are not allowed to wear skirts in that    _  ."
-}
-```
-
-#### high
-
-- **Size of downloaded dataset files:** 24.26 MB
-- **Size of the generated dataset:** 133.63 MB
-- **Total amount of disk used:** 157.89 MB
-
-An example of 'train' looks as follows.
-```
-This example was too long and was cropped:
-
-{
-    "answer": "A",
-    "article": "\"Schoolgirls have been wearing such short skirts at Paget High School in Branston that they've been ordered to wear trousers ins...",
-    "example_id": "high132.txt",
-    "options": ["short skirts give people the impression of sexualisation", "short skirts are too expensive for parents to afford", "the headmaster doesn't like girls wearing short skirts", "the girls wearing short skirts will be at the risk of being laughed at"],
-    "question": "The girls at Paget High School are not allowed to wear skirts in that    _  ."
-}
-```
-
-#### middle
-
-- **Size of downloaded dataset files:** 24.26 MB
-- **Size of the generated dataset:** 33.01 MB
-- **Total amount of disk used:** 57.27 MB
-
-An example of 'train' looks as follows.
-```
-This example was too long and was cropped:
-
-{
-    "answer": "B",
-    "article": "\"There is not enough oil in the world now. As time goes by, it becomes less and less, so what are we going to do when it runs ou...",
-    "example_id": "middle3.txt",
-    "options": ["There is more petroleum than we can use now.", "Trees are needed for some other things besides making gas.", "We got electricity from ocean tides in the old days.", "Gas wasn't used to run cars in the Second World War."],
-    "question": "According to the passage, which of the following statements is TRUE?"
-}
-```
-
-### Data Fields
-
-The data fields are the same among all splits.
-
-#### all
-- `example_id`: a `string` feature.
-- `article`: a `string` feature.
-- `answer`: a `string` feature.
-- `question`: a `string` feature.
-- `options`: a `list` of `string` features.
-
-#### high
-- `example_id`: a `string` feature.
-- `article`: a `string` feature.
-- `answer`: a `string` feature.
-- `question`: a `string` feature.
-- `options`: a `list` of `string` features.
-
-#### middle
-- `example_id`: a `string` feature.
-- `article`: a `string` feature.
-- `answer`: a `string` feature.
-- `question`: a `string` feature.
-- `options`: a `list` of `string` features.
-
-### Data Splits
-
-| name |train|validation|test|
-|------|----:|---------:|---:|
-|all   |87866|      4887|4934|
-|high  |62445|      3451|3498|
-|middle|25421|      1436|1436|
-
-## 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
-
-http://www.cs.cmu.edu/~glai1/data/race/
-
-1. RACE dataset is available for non-commercial research purpose only.
-
-2. All passages are obtained from the Internet which is not property of Carnegie Mellon University. We are not responsible for the content nor the meaning of these passages.
-
-3. You agree not to reproduce, duplicate, copy, sell, trade, resell or exploit for any commercial purpose, any portion of the contexts and any portion of derived data.
-
-4. We reserve the right to terminate your access to the RACE dataset at any time.
-
-### Citation Information
-
-```
-@inproceedings{lai-etal-2017-race,
-    title = "{RACE}: Large-scale {R}e{A}ding Comprehension Dataset From Examinations",
-    author = "Lai, Guokun  and
-      Xie, Qizhe  and
-      Liu, Hanxiao  and
-      Yang, Yiming  and
-      Hovy, Eduard",
-    booktitle = "Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing",
-    month = sep,
-    year = "2017",
-    address = "Copenhagen, Denmark",
-    publisher = "Association for Computational Linguistics",
-    url = "https://aclanthology.org/D17-1082",
-    doi = "10.18653/v1/D17-1082",
-    pages = "785--794",
-}
-```
-
-
-### Contributions
-
-Thanks to [@abarbosa94](https://github.com/abarbosa94), [@patrickvonplaten](https://github.com/patrickvonplaten), [@lewtun](https://github.com/lewtun), [@thomwolf](https://github.com/thomwolf), [@mariamabarham](https://github.com/mariamabarham) for adding this dataset.

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race.py

@@ -1,111 +0,0 @@
-"""TODO(race): Add a description here."""
-
-
-import json
-
-import datasets
-
-
-_CITATION = """\
-@article{lai2017large,
-    title={RACE: Large-scale ReAding Comprehension Dataset From Examinations},
-    author={Lai, Guokun and Xie, Qizhe and Liu, Hanxiao and Yang, Yiming and Hovy, Eduard},
-    journal={arXiv preprint arXiv:1704.04683},
-    year={2017}
-}
-"""
-
-_DESCRIPTION = """\
-Race is a large-scale reading comprehension dataset with more than 28,000 passages and nearly 100,000 questions. The
- dataset is collected from English examinations in China, which are designed for middle school and high school students.
-The dataset can be served as the training and test sets for machine comprehension.
-
-"""
-
-_URL = "http://www.cs.cmu.edu/~glai1/data/race/RACE.tar.gz"
-
-
-class Race(datasets.GeneratorBasedBuilder):
-    """ReAding Comprehension Dataset From Examination dataset from CMU"""
-
-    VERSION = datasets.Version("0.1.0")
-
-    BUILDER_CONFIGS = [
-        datasets.BuilderConfig(name="high", description="Exams designed for high school students", version=VERSION),
-        datasets.BuilderConfig(
-            name="middle", description="Exams designed for middle school students", version=VERSION
-        ),
-        datasets.BuilderConfig(
-            name="all", description="Exams designed for both high school and middle school students", version=VERSION
-        ),
-    ]
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            # This is the description that will appear on the datasets page.
-            description=_DESCRIPTION,
-            # datasets.features.FeatureConnectors
-            features=datasets.Features(
-                {
-                    "example_id": datasets.Value("string"),
-                    "article": datasets.Value("string"),
-                    "answer": datasets.Value("string"),
-                    "question": datasets.Value("string"),
-                    "options": datasets.features.Sequence(datasets.Value("string"))
-                    # These are the features of your dataset like images, labels ...
-                }
-            ),
-            # 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="http://www.cs.cmu.edu/~glai1/data/race/",
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        # Downloads the data and defines the splits
-        # dl_manager is a datasets.download.DownloadManager that can be used to
-        archive = dl_manager.download(_URL)
-        case = str(self.config.name)
-        if case == "all":
-            case = ""
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={"train_test_or_eval": f"RACE/test/{case}", "files": dl_manager.iter_archive(archive)},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={"train_test_or_eval": f"RACE/train/{case}", "files": dl_manager.iter_archive(archive)},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={"train_test_or_eval": f"RACE/dev/{case}", "files": dl_manager.iter_archive(archive)},
-            ),
-        ]
-
-    def _generate_examples(self, train_test_or_eval, files):
-        """Yields examples."""
-        for file_idx, (path, f) in enumerate(files):
-            if path.startswith(train_test_or_eval) and path.endswith(".txt"):
-                data = json.loads(f.read().decode("utf-8"))
-                questions = data["questions"]
-                answers = data["answers"]
-                options = data["options"]
-                for i in range(len(questions)):
-                    question = questions[i]
-                    answer = answers[i]
-                    option = options[i]
-                    yield f"{file_idx}_{i}", {
-                        "example_id": data["id"],
-                        "article": data["article"],
-                        "question": question,
-                        "answer": answer,
-                        "options": option,
-                    }