---
title: coco-captions
canonical_url: "https://www.modelscope.cn/datasets/sentence-transformers/coco-captions"
md_url: "https://www.modelscope.cn/datasets/sentence-transformers/coco-captions.md"
repository: sentence-transformers/coco-captions
last_updated: 2025-01-06
license: "Apache License 2.0"
storage_size: "23 MB"
downloads: 1468
stars: 1
---

# coco-captions

> coco-captions - sentence-transformers 在 ModelScope 开源的数据集。Dataset Card for Coco Captions

sentence-transformers/coco-captions 是 ModelScope 魔搭社区上的数据集，存储大小 23 MB，采用 Apache License 2.0 许可。

- **Repository**: sentence-transformers/coco-captions
- **License**: Apache License 2.0
- **Storage size**: 23 MB
- **Downloads**: 1468
- **Stars**: 1
- **Last updated**: 2025-01-06

Source: https://www.modelscope.cn/datasets/sentence-transformers/coco-captions

---

# Dataset Card for Coco Captions

This dataset is a collection of caption pairs given to the same image, collected from the Coco dataset. See [Coco](https://cocodataset.org/) for additional information.
This dataset can be used directly with Sentence Transformers to train embedding models.

Note that two captions for the same image do not strictly have the same semantic meaning. 

## Dataset Subsets

### `pair` subset

* Columns: "caption1", "caption2"
* Column types: `str`, `str`
* Examples:
    ```python
    {
      'caption1': 'A clock that blends in with the wall hangs in a bathroom. ',
      'caption2': 'A very clean and well decorated empty bathroom',
    }
    ```
* Collection strategy: Reading the Coco Captions dataset from [embedding-training-data](https://huggingface.co/datasets/sentence-transformers/embedding-training-data), which has lists of duplicate captions. I've considered all adjacent captions as a positive pair, plus the last and first caption. So, e.g. 5 duplicate captions results in 5 duplicate pairs.
* Deduplified: No