|
--- |
|
language: |
|
- en |
|
pretty_name: YelpPolarity |
|
task_categories: |
|
- text-classification |
|
task_ids: |
|
- sentiment-classification |
|
paperswithcode_id: yelp-review-polarity |
|
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:** 166.38 MB |
|
- **Size of the generated dataset:** 441.74 MB |
|
- **Total amount of disk used:** 608.12 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 3 and 4 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:** 166.38 MB |
|
- **Size of the generated dataset:** 441.74 MB |
|
- **Total amount of disk used:** 608.12 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. |