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 ([email protected]) 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:** 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. |