Datasets:
Tasks:
Text Classification
Sub-tasks:
sentiment-classification
Languages:
English
Size:
1K<n<10K
License:
File size: 6,647 Bytes
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---
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
---
# 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. |