| | --- |
| | language: |
| | - en |
| | multilinguality: |
| | - monolingual |
| | size_categories: |
| | - 100K<n<1M |
| | task_categories: |
| | - feature-extraction |
| | - sentence-similarity |
| | pretty_name: Flickr30k Captions |
| | tags: |
| | - sentence-transformers |
| | dataset_info: |
| | config_name: pair |
| | features: |
| | - name: caption1 |
| | dtype: string |
| | - name: caption2 |
| | dtype: string |
| | splits: |
| | - name: train |
| | num_bytes: 21319922 |
| | num_examples: 158881 |
| | download_size: 11450890 |
| | dataset_size: 21319922 |
| | configs: |
| | - config_name: pair |
| | data_files: |
| | - split: train |
| | path: pair/train-* |
| | --- |
| | |
| | # Dataset Card for Flickr30k Captions |
| |
|
| | This dataset is a collection of caption pairs given to the same image, collected from Flickr30k. See [Flickr30k](https://shannon.cs.illinois.edu/DenotationGraph/) 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 large structure has broken and is laying in a roadway.', |
| | 'caption2': 'A man stands on wooden supports and surveys damage.', |
| | } |
| | ``` |
| | * Collection strategy: Reading the Flickr30k 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 |
