Datasets:

embedding-data
/

coco_captions_quintets

	---
	license: mit
	language:
	- en
	paperswithcode_id: embedding-data/coco_captions
	pretty_name: coco_captions
	task_categories:
	- sentence-similarity
	- paraphrase-mining
	task_ids:
	- semantic-similarity-classification

	---

	# Dataset Card for "coco_captions"

	## 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://cocodataset.org/#home](https://cocodataset.org/#home)
	- Repository: [https://github.com/cocodataset/cocodataset.github.io](https://github.com/cocodataset/cocodataset.github.io)
	- Paper: [More Information Needed](https://arxiv.org/abs/1405.0312)
	- Point of Contact: [info@cocodataset.org](info@cocodataset.org)
	- Size of downloaded dataset files:
	- Size of the generated dataset:
	- Total amount of disk used: 6.32 MB

	### Dataset Summary

	COCO is a large-scale object detection, segmentation, and captioning dataset. This repo contains five captions per image; useful for sentence similarity tasks.

	Disclaimer: The team releasing COCO did not upload the dataset to the Hub and did not write a dataset card.
	These steps were done by the Hugging Face team.

	### Supported Tasks

	- [Sentence Transformers](https://huggingface.co/sentence-transformers) training; useful for semantic search and sentence similarity.

	### Languages

	- English.

	## Dataset Structure

	Each example in the dataset contains quintets of similar sentences and is formatted as a dictionary with the key "set" and a list with the sentences as "value":

	```
	{"set": [sentence_1, sentence_2, sentence3, sentence4, sentence5]}
	{"set": [sentence_1, sentence_2, sentence3, sentence4, sentence5]}
	...
	{"set": [sentence_1, sentence_2, sentence3, sentence4, sentence5]}
	```

	This dataset is useful for training Sentence Transformers models. Refer to the following post on how to train models using similar pairs of sentences.

	### Usage Example

	Install the 🤗 Datasets library with `pip install datasets` and load the dataset from the Hub with:

	```python
	from datasets import load_dataset
	dataset = load_dataset("embedding-data/coco_captions")
	```
	The dataset is loaded as a `DatasetDict` and has the format:

	```python
	DatasetDict({
	train: Dataset({
	features: ['set'],
	num_rows: 82783
	})
	})
	```

	Review an example `i` with:

	```python
	dataset["train"][i]["set"]
	```


	### Data Instances

	[More Information Needed](https://cocodataset.org/#format-data)

	### Data Splits

	[More Information Needed](https://cocodataset.org/#format-data)

	## Dataset Creation

	### Curation Rationale

	[More Information Needed](https://cocodataset.org/#home)

	### Source Data

	#### Initial Data Collection and Normalization

	[More Information Needed](https://cocodataset.org/#home)

	#### Who are the source language producers?

	[More Information Needed](https://cocodataset.org/#home)

	### Annotations

	#### Annotation process

	[More Information Needed](https://cocodataset.org/#home)

	#### Who are the annotators?

	[More Information Needed](https://cocodataset.org/#home)

	### Personal and Sensitive Information

	[More Information Needed](https://cocodataset.org/#home)

	## Considerations for Using the Data

	### Social Impact of Dataset

	[More Information Needed](https://cocodataset.org/#home)

	### Discussion of Biases

	[More Information Needed](https://cocodataset.org/#home)

	### Other Known Limitations

	[More Information Needed](https://cocodataset.org/#home)

	## Additional Information

	### Dataset Curators

	[More Information Needed](https://cocodataset.org/#home)

	### Licensing Information

	The annotations in this dataset along with this website belong to the COCO Consortium
	and are licensed under a [Creative Commons Attribution 4.0 License](https://creativecommons.org/licenses/by/4.0/legalcode)

	### Citation Information

	[More Information Needed](https://cocodataset.org/#home)

	### Contributions

	Thanks to:

	- Tsung-Yi Lin - Google Brain
	- Genevieve Patterson - MSR, Trash TV
	- Matteo R. - Ronchi Caltech
	- Yin Cui - Google
	- Michael Maire - TTI-Chicago
	- Serge Belongie - Cornell Tech
	- Lubomir Bourdev - WaveOne, Inc.
	- Ross Girshick - FAIR
	- James Hays - Georgia Tech
	- Pietro Perona - Caltech
	- Deva Ramanan - CMU
	- Larry Zitnick - FAIR
	- Piotr Dollár - FAIR

	for adding this dataset.