Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
sentiment-classification
Languages:
English
Size:
100K - 1M
ArXiv:
language: | |
- en | |
pretty_name: YelpPolarity | |
dataset_info: | |
features: | |
- name: text | |
dtype: string | |
- name: label | |
dtype: | |
class_label: | |
names: | |
'0': '1' | |
'1': '2' | |
config_name: plain_text | |
splits: | |
- name: train | |
num_bytes: 413558837 | |
num_examples: 560000 | |
- name: test | |
num_bytes: 27962097 | |
num_examples: 38000 | |
download_size: 166373201 | |
dataset_size: 441520934 | |
train-eval-index: | |
- config: plain_text | |
task: text-classification | |
task_id: binary_classification | |
splits: | |
train_split: train | |
eval_split: test | |
col_mapping: | |
text: text | |
label: target | |
metrics: | |
- type: accuracy | |
name: Accuracy | |
- type: f1 | |
name: F1 binary | |
args: | |
average: binary | |
- 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 "yelp_polarity" | |
## 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://course.fast.ai/datasets](https://course.fast.ai/datasets) | |
- **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:** 158.67 MB | |
- **Size of the generated dataset:** 421.28 MB | |
- **Total amount of disk used:** 579.95 MB | |
### Dataset Summary | |
Large Yelp Review Dataset. | |
This is a dataset for binary sentiment classification. We provide a set of 560,000 highly polar yelp reviews for training, and 38,000 for testing. | |
ORIGIN | |
The Yelp reviews dataset consists of reviews from Yelp. It is extracted | |
from the Yelp Dataset Challenge 2015 data. For more information, please | |
refer to http://www.yelp.com/dataset_challenge | |
The Yelp reviews polarity dataset is constructed by | |
Xiang Zhang (xiang.zhang@nyu.edu) from the above dataset. | |
It is first 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). | |
DESCRIPTION | |
The Yelp reviews polarity dataset is constructed by considering stars 1 and 2 | |
negative, and 4 and 5 positive. For each polarity 280,000 training samples and | |
19,000 testing samples are take randomly. In total there are 560,000 trainig | |
samples and 38,000 testing samples. Negative polarity is class 1, | |
and positive class 2. | |
The files train.csv and test.csv contain all the training samples as | |
comma-sparated values. There are 2 columns in them, corresponding to class | |
index (1 and 2) and review text. The review texts are escaped using double | |
quotes ("), and any internal double quote is escaped by 2 double quotes (""). | |
New lines are escaped by a backslash followed with an "n" character, | |
that is " | |
". | |
### 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 | |
#### plain_text | |
- **Size of downloaded dataset files:** 158.67 MB | |
- **Size of the generated dataset:** 421.28 MB | |
- **Total amount of disk used:** 579.95 MB | |
An example of 'train' looks as follows. | |
``` | |
This example was too long and was cropped: | |
{ | |
"label": 0, | |
"text": "\"Unfortunately, the frustration of being Dr. Goldberg's patient is a repeat of the experience I've had with so many other doctor..." | |
} | |
``` | |
### Data Fields | |
The data fields are the same among all splits. | |
#### plain_text | |
- `text`: a `string` feature. | |
- `label`: a classification label, with possible values including `1` (0), `2` (1). | |
### Data Splits | |
| name |train |test | | |
|----------|-----:|----:| | |
|plain_text|560000|38000| | |
## 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{zhangCharacterlevelConvolutionalNetworks2015, | |
archivePrefix = {arXiv}, | |
eprinttype = {arxiv}, | |
eprint = {1509.01626}, | |
primaryClass = {cs}, | |
title = {Character-Level {{Convolutional Networks}} for {{Text Classification}}}, | |
abstract = {This article offers an empirical exploration on the use of character-level convolutional networks (ConvNets) for text classification. We constructed several large-scale datasets to show that character-level convolutional networks could achieve state-of-the-art or competitive results. Comparisons are offered against traditional models such as bag of words, n-grams and their TFIDF variants, and deep learning models such as word-based ConvNets and recurrent neural networks.}, | |
journal = {arXiv:1509.01626 [cs]}, | |
author = {Zhang, Xiang and Zhao, Junbo and LeCun, Yann}, | |
month = sep, | |
year = {2015}, | |
} | |
``` | |
### Contributions | |
Thanks to [@patrickvonplaten](https://github.com/patrickvonplaten), [@lewtun](https://github.com/lewtun), [@mariamabarham](https://github.com/mariamabarham), [@thomwolf](https://github.com/thomwolf), [@julien-c](https://github.com/julien-c) for adding this dataset. |