Duplicate from EdinburghNLP/xsum

Co-authored-by: Parquet-converter (BOT) <parquet-converter@users.noreply.huggingface.co>

.gitattributes

@@ -0,0 +1,27 @@
+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bin.* filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zstandard filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,213 @@
+---
+annotations_creators:
+- found
+language_creators:
+- found
+language:
+- en
+license:
+- unknown
+multilinguality:
+- monolingual
+pretty_name: Extreme Summarization (XSum)
+paperswithcode_id: xsum
+size_categories:
+- 100K<n<1M
+source_datasets:
+- original
+task_categories:
+- summarization
+task_ids:
+- news-articles-summarization
+train-eval-index:
+- config: default
+  task: summarization
+  task_id: summarization
+  splits:
+    train_split: train
+    eval_split: test
+  col_mapping:
+    document: text
+    summary: target
+  metrics:
+  - type: rouge
+    name: Rouge
+dataset_info:
+  features:
+  - name: document
+    dtype: string
+  - name: summary
+    dtype: string
+  - name: id
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 479206608
+    num_examples: 204045
+  - name: validation
+    num_bytes: 26292901
+    num_examples: 11332
+  - name: test
+    num_bytes: 26756165
+    num_examples: 11334
+  download_size: 257302866
+  dataset_size: 532255674
+---
+
+# Dataset Card for "xsum"
+
+## 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:**
+- **Repository:** https://github.com/EdinburghNLP/XSum
+- **Paper:** [Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization](https://arxiv.org/abs/1808.08745)
+- **Point of Contact:** [Shashi Narayan](mailto:shashi.narayan@ed.ac.uk)
+- **Size of downloaded dataset files:** 257.30 MB
+- **Size of the generated dataset:** 532.26 MB
+- **Total amount of disk used:** 789.56 MB
+
+### Dataset Summary
+
+Extreme Summarization (XSum) Dataset.
+
+There are three features:
+  - document: Input news article.
+  - summary: One sentence summary of the article.
+  - id: BBC ID of the article.
+
+### 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
+
+#### default
+
+- **Size of downloaded dataset files:** 257.30 MB
+- **Size of the generated dataset:** 532.26 MB
+- **Total amount of disk used:** 789.56 MB
+
+An example of 'validation' looks as follows.
+```
+{
+    "document": "some-body",
+    "id": "29750031",
+    "summary": "some-sentence"
+}
+```
+
+### Data Fields
+
+The data fields are the same among all splits.
+
+#### default
+- `document`: a `string` feature.
+- `summary`: a `string` feature.
+- `id`: a `string` feature.
+
+### Data Splits
+
+| name  |train |validation|test |
+|-------|-----:|---------:|----:|
+|default|204045|     11332|11334|
+
+## 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
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+### Citation Information
+
+```
+@article{Narayan2018DontGM,
+  title={Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization},
+  author={Shashi Narayan and Shay B. Cohen and Mirella Lapata},
+  journal={ArXiv},
+  year={2018},
+  volume={abs/1808.08745}
+}
+```
+
+
+### Contributions
+
+Thanks to [@thomwolf](https://github.com/thomwolf), [@lewtun](https://github.com/lewtun), [@mariamabarham](https://github.com/mariamabarham), [@jbragg](https://github.com/jbragg), [@lhoestq](https://github.com/lhoestq), [@patrickvonplaten](https://github.com/patrickvonplaten) for adding this dataset.

data/XSUM-EMNLP18-Summary-Data-Original.tar.gz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:10b48aa187fc9c904b30f76ca97e2da0de8d3a1238acc26acadef93e2001af90
+size 254582292

xsum.py

@@ -0,0 +1,170 @@
+# coding=utf-8
+# Copyright 2020 The TensorFlow Datasets Authors and the 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
+"""XSum dataset."""
+
+
+import json
+import os
+
+import datasets
+
+
+_CITATION = """
+@article{Narayan2018DontGM,
+  title={Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization},
+  author={Shashi Narayan and Shay B. Cohen and Mirella Lapata},
+  journal={ArXiv},
+  year={2018},
+  volume={abs/1808.08745}
+}
+"""
+
+_DESCRIPTION = """
+Extreme Summarization (XSum) Dataset.
+
+There are three features:
+  - document: Input news article.
+  - summary: One sentence summary of the article.
+  - id: BBC ID of the article.
+
+"""
+
+# From https://github.com/EdinburghNLP/XSum/issues/12
+_URL_DATA = "data/XSUM-EMNLP18-Summary-Data-Original.tar.gz"
+_URL_SPLITS = (
+    "https://raw.githubusercontent.com/EdinburghNLP/XSum/master/XSum-Dataset/XSum-TRAINING-DEV-TEST-SPLIT-90-5-5.json"
+)
+
+_DOCUMENT = "document"
+_SUMMARY = "summary"
+_ID = "id"
+
+_REMOVE_LINES = set(
+    [
+        "Share this with\n",
+        "Email\n",
+        "Facebook\n",
+        "Messenger\n",
+        "Twitter\n",
+        "Pinterest\n",
+        "WhatsApp\n",
+        "Linkedin\n",
+        "LinkedIn\n",
+        "Copy this link\n",
+        "These are external links and will open in a new window\n",
+    ]
+)
+
+
+class Xsum(datasets.GeneratorBasedBuilder):
+    """Extreme Summarization (XSum) Dataset."""
+
+    # Version 1.2.0 expands coverage, includes ids, and removes web contents.
+    VERSION = datasets.Version("1.2.0")
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    _DOCUMENT: datasets.Value("string"),
+                    _SUMMARY: datasets.Value("string"),
+                    _ID: datasets.Value("string"),
+                }
+            ),
+            supervised_keys=(_DOCUMENT, _SUMMARY),
+            homepage="https://github.com/EdinburghNLP/XSum/tree/master/XSum-Dataset",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+
+        files_to_download = {"data": _URL_DATA, "splits": _URL_SPLITS}
+        downloaded_files = dl_manager.download(files_to_download)
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "split_path": downloaded_files["splits"],
+                    "split_name": "train",
+                    "data_dir": "bbc-summary-data",
+                    "files": dl_manager.iter_archive(downloaded_files["data"]),
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                    "split_path": downloaded_files["splits"],
+                    "split_name": "validation",
+                    "data_dir": "bbc-summary-data",
+                    "files": dl_manager.iter_archive(downloaded_files["data"]),
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "split_path": downloaded_files["splits"],
+                    "split_name": "test",
+                    "data_dir": "bbc-summary-data",
+                    "files": dl_manager.iter_archive(downloaded_files["data"]),
+                },
+            ),
+        ]
+
+    def _generate_examples(self, split_path, split_name, data_dir, files):
+        """Yields examples."""
+
+        with open(split_path, "r", encoding="utf-8") as f:
+            split_ids = json.load(f)
+        split_ids = {k: set(v) for k, v in split_ids.items()}
+
+        for path, f in files:
+            if not split_ids[split_name]:
+                break
+            elif path.startswith(data_dir) and path.endswith(".summary"):
+                i = os.path.basename(path).split(".")[0]
+                if i in split_ids[split_name]:
+                    split_ids[split_name].remove(i)
+                    text = "".join(
+                        [
+                            line.decode("utf-8")
+                            for line in f.readlines()
+                            if line.decode("utf-8") not in _REMOVE_LINES and line.strip()
+                        ]
+                    )
+                    # Each file follows below format:
+                    # [SN]URL[SN]
+                    # http://somelink
+                    #
+                    # [SN]TITLE[SN]
+                    # some intro
+                    #
+                    # [SN]FIRST-SENTENCE[SN]
+                    # some intro
+                    #
+                    # [SN]RESTBODY[SN]
+                    # text line.
+                    # another text line.
+                    # "another text line."
+
+                    # According to the following issue, FIRST-SENTENCE
+                    # is the reference summary and TITLE is unused:
+                    # https://github.com/EdinburghNLP/XSum/issues/22
+                    segs = text.split("[SN]")
+                    yield i, {_DOCUMENT: segs[8].strip(), _SUMMARY: segs[6].strip(), _ID: i}