Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
topic-classification
Languages:
English
Size:
100K - 1M
License:
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 | |
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: 29817303 | |
num_examples: 120000 | |
- name: test | |
num_bytes: 1879474 | |
num_examples: 7600 | |
download_size: 19820267 | |
dataset_size: 31696777 | |
configs: | |
- config_name: default | |
data_files: | |
- split: train | |
path: data/train-* | |
- split: test | |
path: data/test-* | |
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 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:** 31.33 MB | |
- **Size of the generated dataset:** 31.70 MB | |
- **Total amount of disk used:** 63.02 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 | |
([email protected]) 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:** 31.33 MB | |
- **Size of the generated dataset:** 31.70 MB | |
- **Total amount of disk used:** 63.02 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. |