Update parquet files

.gitattributes

@@ -1,27 +0,0 @@
-*.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

@@ -1,256 +0,0 @@
----
-annotations_creators:
-- found
-language_creators:
-- found
-language:
-- en
-license:
-- unknown
-multilinguality:
-- monolingual
-size_categories:
-- 100K<n<1M
-source_datasets:
-- original
-task_categories:
-- text-classification
-task_ids:
-- topic-classification
-paperswithcode_id: ag-news
-pretty_name: AG’s News Corpus
-train-eval-index:
-- config: default
-  task: text-classification
-  task_id: multi_class_classification
-  splits:
-    train_split: train
-    eval_split: test
-  col_mapping:
-    text: text
-    label: target
-  metrics:
-  - type: accuracy
-    name: Accuracy
-  - type: f1
-    name: F1 macro
-    args:
-      average: macro
-  - type: f1
-    name: F1 micro
-    args:
-      average: micro
-  - type: f1
-    name: F1 weighted
-    args:
-      average: weighted
-  - type: precision
-    name: Precision macro
-    args:
-      average: macro
-  - type: precision
-    name: Precision micro
-    args:
-      average: micro
-  - type: precision
-    name: Precision weighted
-    args:
-      average: weighted
-  - type: recall
-    name: Recall macro
-    args:
-      average: macro
-  - type: recall
-    name: Recall micro
-    args:
-      average: micro
-  - type: recall
-    name: Recall weighted
-    args:
-      average: weighted
-dataset_info:
-  features:
-  - name: text
-    dtype: string
-  - name: label
-    dtype:
-      class_label:
-        names:
-          0: World
-          1: Sports
-          2: Business
-          3: Sci/Tech
-  splits:
-  - name: train
-    num_bytes: 29817351
-    num_examples: 120000
-  - name: test
-    num_bytes: 1879478
-    num_examples: 7600
-  download_size: 31327765
-  dataset_size: 31696829
----
-
-# Dataset Card for "ag_news"
-
-## 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://groups.di.unipi.it/~gulli/AG_corpus_of_news_articles.html](http://groups.di.unipi.it/~gulli/AG_corpus_of_news_articles.html)
-- **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:** 29.88 MB
-- **Size of the generated dataset:** 30.23 MB
-- **Total amount of disk used:** 60.10 MB
-
-### Dataset Summary
-
-AG is a collection of more than 1 million news articles. News articles have been
-gathered from more than 2000 news sources by ComeToMyHead in more than 1 year of
-activity. ComeToMyHead is an academic news search engine which has been running
-since July, 2004. The dataset is provided by the academic comunity for research
-purposes in data mining (clustering, classification, etc), information retrieval
-(ranking, search, etc), xml, data compression, data streaming, and any other
-non-commercial activity. For more information, please refer to the link
-http://www.di.unipi.it/~gulli/AG_corpus_of_news_articles.html .
-
-The AG's news topic classification dataset is constructed by Xiang Zhang
-(xiang.zhang@nyu.edu) from the dataset above. It is used as a text
-classification benchmark in the following paper: Xiang Zhang, Junbo Zhao, Yann
-LeCun. Character-level Convolutional Networks for Text Classification. Advances
-in Neural Information Processing Systems 28 (NIPS 2015).
-
-### 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:** 29.88 MB
-- **Size of the generated dataset:** 30.23 MB
-- **Total amount of disk used:** 60.10 MB
-
-An example of 'train' looks as follows.
-```
-{
-    "label": 3,
-    "text": "New iPad released Just like every other September, this one is no different. Apple is planning to release a bigger, heavier, fatter iPad that..."
-}
-```
-
-### Data Fields
-
-The data fields are the same among all splits.
-
-#### default
-- `text`: a `string` feature.
-- `label`: a classification label, with possible values including `World` (0), `Sports` (1), `Business` (2), `Sci/Tech` (3).
-
-### Data Splits
-
-| name  |train |test|
-|-------|-----:|---:|
-|default|120000|7600|
-
-## 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
-
-```
-@inproceedings{Zhang2015CharacterlevelCN,
-  title={Character-level Convolutional Networks for Text Classification},
-  author={Xiang Zhang and Junbo Jake Zhao and Yann LeCun},
-  booktitle={NIPS},
-  year={2015}
-}
-
-```
-
-
-### Contributions
-
-Thanks to [@jxmorris12](https://github.com/jxmorris12), [@thomwolf](https://github.com/thomwolf), [@lhoestq](https://github.com/lhoestq), [@lewtun](https://github.com/lewtun) for adding this dataset.

ag_news.py

@@ -1,94 +0,0 @@
-# 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
-"""AG News topic classification dataset."""
-
-
-import csv
-
-import datasets
-from datasets.tasks import TextClassification
-
-
-_DESCRIPTION = """\
-AG is a collection of more than 1 million news articles. News articles have been
-gathered from more than 2000 news sources by ComeToMyHead in more than 1 year of
-activity. ComeToMyHead is an academic news search engine which has been running
-since July, 2004. The dataset is provided by the academic comunity for research
-purposes in data mining (clustering, classification, etc), information retrieval
-(ranking, search, etc), xml, data compression, data streaming, and any other
-non-commercial activity. For more information, please refer to the link
-http://www.di.unipi.it/~gulli/AG_corpus_of_news_articles.html .
-
-The AG's news topic classification dataset is constructed by Xiang Zhang
-(xiang.zhang@nyu.edu) from the dataset above. It is used as a text
-classification benchmark in the following paper: Xiang Zhang, Junbo Zhao, Yann
-LeCun. Character-level Convolutional Networks for Text Classification. Advances
-in Neural Information Processing Systems 28 (NIPS 2015).
-"""
-
-_CITATION = """\
-@inproceedings{Zhang2015CharacterlevelCN,
-  title={Character-level Convolutional Networks for Text Classification},
-  author={Xiang Zhang and Junbo Jake Zhao and Yann LeCun},
-  booktitle={NIPS},
-  year={2015}
-}
-"""
-
-_TRAIN_DOWNLOAD_URL = "https://raw.githubusercontent.com/mhjabreel/CharCnn_Keras/master/data/ag_news_csv/train.csv"
-_TEST_DOWNLOAD_URL = "https://raw.githubusercontent.com/mhjabreel/CharCnn_Keras/master/data/ag_news_csv/test.csv"
-
-
-class AGNews(datasets.GeneratorBasedBuilder):
-    """AG News topic classification dataset."""
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "text": datasets.Value("string"),
-                    "label": datasets.features.ClassLabel(names=["World", "Sports", "Business", "Sci/Tech"]),
-                }
-            ),
-            homepage="http://groups.di.unipi.it/~gulli/AG_corpus_of_news_articles.html",
-            citation=_CITATION,
-            task_templates=[TextClassification(text_column="text", label_column="label")],
-        )
-
-    def _split_generators(self, dl_manager):
-        train_path = dl_manager.download_and_extract(_TRAIN_DOWNLOAD_URL)
-        test_path = dl_manager.download_and_extract(_TEST_DOWNLOAD_URL)
-        return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": train_path}),
-            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": test_path}),
-        ]
-
-    def _generate_examples(self, filepath):
-        """Generate AG News examples."""
-        with open(filepath, encoding="utf-8") as csv_file:
-            csv_reader = csv.reader(
-                csv_file, quotechar='"', delimiter=",", quoting=csv.QUOTE_ALL, skipinitialspace=True
-            )
-            for id_, row in enumerate(csv_reader):
-                label, title, description = row
-                # Original labels are [1, 2, 3, 4] ->
-                #                   ['World', 'Sports', 'Business', 'Sci/Tech']
-                # Re-map to [0, 1, 2, 3].
-                label = int(label) - 1
-                text = " ".join((title, description))
-                yield id_, {"text": text, "label": label}

dataset_infos.json

@@ -1 +0,0 @@
-{"default": {"description": "AG is a collection of more than 1 million news articles. News articles have been\ngathered from more than 2000 news sources by ComeToMyHead in more than 1 year of\nactivity. ComeToMyHead is an academic news search engine which has been running\nsince July, 2004. The dataset is provided by the academic comunity for research\npurposes in data mining (clustering, classification, etc), information retrieval\n(ranking, search, etc), xml, data compression, data streaming, and any other\nnon-commercial activity. For more information, please refer to the link\nhttp://www.di.unipi.it/~gulli/AG_corpus_of_news_articles.html .\n\nThe AG's news topic classification dataset is constructed by Xiang Zhang\n(xiang.zhang@nyu.edu) from the dataset above. It is used as a text\nclassification benchmark in the following paper: Xiang Zhang, Junbo Zhao, Yann\nLeCun. Character-level Convolutional Networks for Text Classification. Advances\nin Neural Information Processing Systems 28 (NIPS 2015).\n", "citation": "@inproceedings{Zhang2015CharacterlevelCN,\n  title={Character-level Convolutional Networks for Text Classification},\n  author={Xiang Zhang and Junbo Jake Zhao and Yann LeCun},\n  booktitle={NIPS},\n  year={2015}\n}\n", "homepage": "http://groups.di.unipi.it/~gulli/AG_corpus_of_news_articles.html", "license": "", "features": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 4, "names": ["World", "Sports", "Business", "Sci/Tech"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": null, "task_templates": [{"task": "text-classification", "text_column": "text", "label_column": "label", "labels": ["Business", "Sci/Tech", "Sports", "World"]}], "builder_name": "ag_news", "config_name": "default", "version": {"version_str": "0.0.0", "description": null, "major": 0, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 29817351, "num_examples": 120000, "dataset_name": "ag_news"}, "test": {"name": "test", "num_bytes": 1879478, "num_examples": 7600, "dataset_name": "ag_news"}}, "download_checksums": {"https://raw.githubusercontent.com/mhjabreel/CharCnn_Keras/master/data/ag_news_csv/train.csv": {"num_bytes": 29470338, "checksum": "76a0a2d2f92b286371fe4d4044640910a04a803fdd2538e0f3f29a5c6f6b672e"}, "https://raw.githubusercontent.com/mhjabreel/CharCnn_Keras/master/data/ag_news_csv/test.csv": {"num_bytes": 1857427, "checksum": "521465c2428ed7f02f8d6db6ffdd4b5447c1c701962353eb2c40d548c3c85699"}}, "download_size": 31327765, "post_processing_size": null, "dataset_size": 31696829, "size_in_bytes": 63024594}}

default/ag_news-test.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:29c40feec94e92d8d609aaec0d9927bb35c16532540cb9c9555f28973cec0360
+size 1234828

default/ag_news-train.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:17c8ed585491d9f7636026b7a51cf09264e6794e75f3e4049c720bff74b5420e
+size 18585437