
# Dataset Card for "imdb_dutch"

## 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:** [http://ai.stanford.edu/~amaas/data/sentiment/](http://ai.stanford.edu/~amaas/data/sentiment/)
- **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)

### Dataset Summary

Large Movie Review Dataset translated to Dutch.

This is a dataset for binary sentiment classification containing substantially more data than previous benchmark datasets.
We provide a set of 24,992 highly polar movie reviews for training, and 24,992 for testing. There is additional unlabeled data for use as well.

### Translation to Dutch

The dataset was translated with [yhavinga/ul2-large-en-nl](https://huggingface.co/yhavinga/ul2-large-en-nl).
The translation code is available in the src directory.

### Supported Tasks and Leaderboards

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Languages

This dataset contains Dutch and English data.

## Dataset Structure

### Data Instances

#### plain_text

- **Size of downloaded dataset files:** 108 MiB
- **Size of the generated dataset:** 277 MiB

An example of 'train' looks as follows.
```
{
    "label": 0,
    "text": "Holy shit. Dit was de slechtste film die ik in lange tijd heb gezien."
    "text_en": "Holy crap. This was the worst film I have seen in a long time."
}
```

### Data Fields

The data fields are the same among all splits.

#### plain_text
- `text`: a `string` feature.
- `text_en`: a `string` feature.
- `label`: a classification label, with possible values including `neg` (0), `pos` (1).

### Data Splits

|   name   |train|unsupervised|test |
|----------|----:|-----------:|----:|
|plain_text|24992|       49984|24992|

## 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{maas-EtAl:2011:ACL-HLT2011,
  author    = {Maas, Andrew L.  and  Daly, Raymond E.  and  Pham, Peter T.  and  Huang, Dan  and  Ng, Andrew Y.  and  Potts, Christopher},
  title     = {Learning Word Vectors for Sentiment Analysis},
  booktitle = {Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies},
  month     = {June},
  year      = {2011},
  address   = {Portland, Oregon, USA},
  publisher = {Association for Computational Linguistics},
  pages     = {142--150},
  url       = {http://www.aclweb.org/anthology/P11-1015}
}

```


### Contributions

Thanks to [@ghazi-f](https://github.com/ghazi-f), [@patrickvonplaten](https://github.com/patrickvonplaten), [@lhoestq](https://github.com/lhoestq), [@thomwolf](https://github.com/thomwolf) for adding
the English `imdb` dataset.
This project would not have been possible without compute generously provided by Google through the
[TPU Research Cloud](https://sites.research.google/trc/).

Created by [Yeb Havinga](https://www.linkedin.com/in/yeb-havinga-86530825/)

task_categories:text-classification task_ids:sentiment-classification annotations_creators:expert-generated language_creators:expert-generated multilinguality:multilingual size_categories:10K<n<100K source_datasets:original language:nl language:en license:other region:us
{"annotations_creators": ["expert-generated"], "language_creators": ["expert-generated"], "language": ["nl", "en"], "license": ["other"], "multilinguality": ["multilingual"], "size_categories": ["10K<n<100K"], "source_datasets": ["original"], "task_categories": ["text-classification"], "task_ids": ["sentiment-classification"], "paperswithcode_id": "imdb-movie-reviews", "pretty_name": "IMDB", "dataset_info": {"features": [{"name": "text", "dtype": "string"}, {"name": "text_en", "dtype": "string"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "neg", "1": "pos"}}}}], "config_name": "plain_text", "splits": [{"name": "train", "num_bytes": 69589646, "num_examples": 24992}, {"name": "test", "num_bytes": 67958995, "num_examples": 24992}, {"name": "unsupervised", "num_bytes": 139649169, "num_examples": 49984}], "download_size": 108170940, "dataset_size": 277197810}, "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 macro", "args": {"average": "macro"}}, {"type": "f1", "name": "F1 micro", "args": {"average": "micro"}}, {"type": "f1", "name": "F1 weighted", "args": {"average": "weighted"}}, {"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"}}]}]}
TAGS
#task_categories-text-classification #task_ids-sentiment-classification #annotations_creators-expert-generated #language_creators-expert-generated #multilinguality-multilingual #size_categories-10K<n<100K #source_datasets-original #language-Dutch #language-English #license-other #region-us 

Dataset Card for "imdb\_dutch"
==============================


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: URL
* Repository:
* Paper:
* Point of Contact:


### Dataset Summary


Large Movie Review Dataset translated to Dutch.


This is a dataset for binary sentiment classification containing substantially more data than previous benchmark datasets.
We provide a set of 24,992 highly polar movie reviews for training, and 24,992 for testing. There is additional unlabeled data for use as well.


### Translation to Dutch


The dataset was translated with yhavinga/ul2-large-en-nl.
The translation code is available in the src directory.


### Supported Tasks and Leaderboards


### Languages


This dataset contains Dutch and English data.


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


### Data Instances


#### plain\_text


* Size of downloaded dataset files: 108 MiB
* Size of the generated dataset: 277 MiB


An example of 'train' looks as follows.


### Data Fields


The data fields are the same among all splits.


#### plain\_text


* 'text': a 'string' feature.
* 'text\_en': a 'string' feature.
* 'label': a classification label, with possible values including 'neg' (0), 'pos' (1).


### 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 @ghazi-f, @patrickvonplaten, @lhoestq, @thomwolf for adding
the English 'imdb' dataset.
This project would not have been possible without compute generously provided by Google through the
TPU Research Cloud.


Created by Yeb Havinga



### Dataset Summary


Large Movie Review Dataset translated to Dutch.


This is a dataset for binary sentiment classification containing substantially more data than previous benchmark datasets.
We provide a set of 24,992 highly polar movie reviews for training, and 24,992 for testing. There is additional unlabeled data for use as well. ### Translation to Dutch


The dataset was translated with yhavinga/ul2-large-en-nl.
The translation code is available in the src directory. ### Supported Tasks and Leaderboards ### Languages


This dataset contains Dutch and English data.


Dataset Structure
----------------- ### Data Instances #### plain\_text


* Size of downloaded dataset files: 108 MiB
* Size of the generated dataset: 277 MiB


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


The data fields are the same among all splits. #### plain\_text


* 'text': a 'string' feature.
* 'text\_en': a 'string' feature.
* 'label': a classification label, with possible values including 'neg' (0), 'pos' (1). ### 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 @ghazi-f, @patrickvonplaten, @lhoestq, @thomwolf for adding
the English 'imdb' dataset.
This project would not have been possible without compute generously provided by Google through the
TPU Research Cloud.


Created by Yeb Havinga
TAGS
#task_categories-text-classification #task_ids-sentiment-classification #annotations_creators-expert-generated #language_creators-expert-generated #multilinguality-multilingual #size_categories-10K<n<100K #source_datasets-original #language-Dutch #language-English #license-other #region-us 
 ### Dataset Summary


Large Movie Review Dataset translated to Dutch.


This is a dataset for binary sentiment classification containing substantially more data than previous benchmark datasets.
We provide a set of 24,992 highly polar movie reviews for training, and 24,992 for testing. There is additional unlabeled data for use as well. ### Translation to Dutch


The dataset was translated with yhavinga/ul2-large-en-nl.
The translation code is available in the src directory. ### Supported Tasks and Leaderboards ### Languages


This dataset contains Dutch and English data.


Dataset Structure
----------------- ### Data Instances #### plain\_text


* Size of downloaded dataset files: 108 MiB
* Size of the generated dataset: 277 MiB


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


The data fields are the same among all splits. #### plain\_text


* 'text': a 'string' feature.
* 'text\_en': a 'string' feature.
* 'label': a classification label, with possible values including 'neg' (0), 'pos' (1). ### 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 @ghazi-f, @patrickvonplaten, @lhoestq, @thomwolf for adding
the English 'imdb' dataset.
This project would not have been possible without compute generously provided by Google through the
TPU Research Cloud.


Created by Yeb Havinga
passage: TAGS
#task_categories-text-classification #task_ids-sentiment-classification #annotations_creators-expert-generated #language_creators-expert-generated #multilinguality-multilingual #size_categories-10K<n<100K #source_datasets-original #language-Dutch #language-English #license-other #region-us 
### Dataset Summary


Large Movie Review Dataset translated to Dutch.


This is a dataset for binary sentiment classification containing substantially more data than previous benchmark datasets.
We provide a set of 24,992 highly polar movie reviews for training, and 24,992 for testing. There is additional unlabeled data for use as well.### Translation to Dutch


The dataset was translated with yhavinga/ul2-large-en-nl.
The translation code is available in the src directory.### Supported Tasks and Leaderboards### Languages


This dataset contains Dutch and English data.


Dataset Structure
-----------------### Data Instances#### plain\_text


* Size of downloaded dataset files: 108 MiB
* Size of the generated dataset: 277 MiB


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


The data fields are the same among all splits.#### plain\_text


* 'text': a 'string' feature.
* 'text\_en': a 'string' feature.
* 'label': a classification label, with possible values including 'neg' (0), 'pos' (1).### 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