
# Dataset Card for "movie_rationales"

## 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:**
- **Repository:** https://github.com/jayded/eraserbenchmark
- **Paper:** [ERASER: A Benchmark to Evaluate Rationalized NLP Models](https://aclanthology.org/2020.acl-main.408/)
- **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:** 3.90 MB
- **Size of the generated dataset:** 8.73 MB
- **Total amount of disk used:** 12.62 MB

### Dataset Summary

The movie rationale dataset contains human annotated rationales for movie
reviews.

### 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:** 3.90 MB
- **Size of the generated dataset:** 8.73 MB
- **Total amount of disk used:** 12.62 MB

An example of 'validation' looks as follows.
```
{
    "evidences": ["Fun movie"],
    "label": 1,
    "review": "Fun movie\n"
}
```

### Data Fields

The data fields are the same among all splits.

#### default
- `review`: a `string` feature.
- `label`: a classification label, with possible values including `NEG` (0), `POS` (1).
- `evidences`: a `list` of `string` features.

### Data Splits

| name  |train|validation|test|
|-------|----:|---------:|---:|
|default| 1600|       200| 199|

## 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{deyoung-etal-2020-eraser,
    title = "{ERASER}: {A} Benchmark to Evaluate Rationalized {NLP} Models",
    author = "DeYoung, Jay  and
      Jain, Sarthak  and
      Rajani, Nazneen Fatema  and
      Lehman, Eric  and
      Xiong, Caiming  and
      Socher, Richard  and
      Wallace, Byron C.",
    booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics",
    month = jul,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2020.acl-main.408",
    doi = "10.18653/v1/2020.acl-main.408",
    pages = "4443--4458",
}
@InProceedings{zaidan-eisner-piatko-2008:nips,
  author    =  {Omar F. Zaidan  and  Jason Eisner  and  Christine Piatko},
  title     =  {Machine Learning with Annotator Rationales to Reduce Annotation Cost},
  booktitle =  {Proceedings of the NIPS*2008 Workshop on Cost Sensitive Learning},
  month     =  {December},
  year      =  {2008}
}
```


### Contributions

Thanks to [@thomwolf](https://github.com/thomwolf), [@patrickvonplaten](https://github.com/patrickvonplaten), [@lewtun](https://github.com/lewtun) for adding this dataset.
task_categories:text-classification task_ids:sentiment-classification annotations_creators:crowdsourced language_creators:found multilinguality:monolingual size_categories:1K<n<10K source_datasets:original language:en license:unknown region:us
{"annotations_creators": ["crowdsourced"], "language_creators": ["found"], "language": ["en"], "license": ["unknown"], "multilinguality": ["monolingual"], "size_categories": ["1K<n<10K"], "source_datasets": ["original"], "task_categories": ["text-classification"], "task_ids": ["sentiment-classification"], "pretty_name": "MovieRationales", "dataset_info": {"features": [{"name": "review", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "NEG", "1": "POS"}}}}, {"name": "evidences", "sequence": "string"}], "splits": [{"name": "test", "num_bytes": 1046377, "num_examples": 199}, {"name": "train", "num_bytes": 6853624, "num_examples": 1600}, {"name": "validation", "num_bytes": 830417, "num_examples": 200}], "download_size": 3899487, "dataset_size": 8730418}}
TAGS
#task_categories-text-classification #task_ids-sentiment-classification #annotations_creators-crowdsourced #language_creators-found #multilinguality-monolingual #size_categories-1K<n<10K #source_datasets-original #language-English #license-unknown #region-us 

Dataset Card for "movie\_rationales"
====================================


Table of Contents
-----------------


* Dataset Description
	+ Dataset Summary
	+ Supported Tasks and Leaderboards
	+ Languages
* Dataset Structure
	+ Data Instances
	+ Data Fields
	+ Data Splits
* Dataset Creation
	+ Curation Rationale
	+ Source Data
	+ Annotations
	+ Personal and Sensitive Information
* Considerations for Using the Data
	+ Social Impact of Dataset
	+ Discussion of Biases
	+ Other Known Limitations
* Additional Information
	+ Dataset Curators
	+ Licensing Information
	+ Citation Information
	+ Contributions


Dataset Description
-------------------


* Homepage:
* Repository: URL
* Paper: ERASER: A Benchmark to Evaluate Rationalized NLP Models
* Point of Contact:
* Size of downloaded dataset files: 3.90 MB
* Size of the generated dataset: 8.73 MB
* Total amount of disk used: 12.62 MB


### Dataset Summary


The movie rationale dataset contains human annotated rationales for movie
reviews.


### Supported Tasks and Leaderboards


### Languages


Dataset Structure
-----------------


### Data Instances


#### default


* Size of downloaded dataset files: 3.90 MB
* Size of the generated dataset: 8.73 MB
* Total amount of disk used: 12.62 MB


An example of 'validation' looks as follows.


### Data Fields


The data fields are the same among all splits.


#### default


* 'review': a 'string' feature.
* 'label': a classification label, with possible values including 'NEG' (0), 'POS' (1).
* 'evidences': a 'list' of 'string' features.


### Data Splits



Dataset Creation
----------------


### Curation Rationale


### Source Data


#### Initial Data Collection and Normalization


#### Who are the source language producers?


### Annotations


#### Annotation process


#### Who are the annotators?


### Personal and Sensitive Information


Considerations for Using the Data
---------------------------------


### Social Impact of Dataset


### Discussion of Biases


### Other Known Limitations


Additional Information
----------------------


### Dataset Curators


### Licensing Information


### Contributions


Thanks to @thomwolf, @patrickvonplaten, @lewtun for adding this dataset.



### Dataset Summary


The movie rationale dataset contains human annotated rationales for movie
reviews. ### Supported Tasks and Leaderboards ### Languages


Dataset Structure
----------------- ### Data Instances #### default


* Size of downloaded dataset files: 3.90 MB
* Size of the generated dataset: 8.73 MB
* Total amount of disk used: 12.62 MB


An example of 'validation' looks as follows. ### Data Fields


The data fields are the same among all splits. #### default


* 'review': a 'string' feature.
* 'label': a classification label, with possible values including 'NEG' (0), 'POS' (1).
* 'evidences': a 'list' of 'string' features. ### Data Splits



Dataset Creation
---------------- ### Curation Rationale ### Source Data #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information


Considerations for Using the Data
--------------------------------- ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations


Additional Information
---------------------- ### Dataset Curators ### Licensing Information ### Contributions


Thanks to @thomwolf, @patrickvonplaten, @lewtun for adding this dataset.
TAGS
#task_categories-text-classification #task_ids-sentiment-classification #annotations_creators-crowdsourced #language_creators-found #multilinguality-monolingual #size_categories-1K<n<10K #source_datasets-original #language-English #license-unknown #region-us 
 ### Dataset Summary


The movie rationale dataset contains human annotated rationales for movie
reviews. ### Supported Tasks and Leaderboards ### Languages


Dataset Structure
----------------- ### Data Instances #### default


* Size of downloaded dataset files: 3.90 MB
* Size of the generated dataset: 8.73 MB
* Total amount of disk used: 12.62 MB


An example of 'validation' looks as follows. ### Data Fields


The data fields are the same among all splits. #### default


* 'review': a 'string' feature.
* 'label': a classification label, with possible values including 'NEG' (0), 'POS' (1).
* 'evidences': a 'list' of 'string' features. ### Data Splits



Dataset Creation
---------------- ### Curation Rationale ### Source Data #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information


Considerations for Using the Data
--------------------------------- ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations


Additional Information
---------------------- ### Dataset Curators ### Licensing Information ### Contributions


Thanks to @thomwolf, @patrickvonplaten, @lewtun for adding this dataset.