Update README.md

README.md

@@ -1,4 +1,16 @@
 ---
+language:
+- en
+multilinguality:
+- monolingual
+size_categories:
+- 100K<n<1M
+task_categories:
+- feature-extraction
+- sentence-similarity
+pretty_name: Coco Captions
+tags:
+- sentence-transformers
 dataset_info:
   config_name: pair
   features:
@@ -18,3 +30,26 @@ configs:
   - split: train
     path: pair/train-*
 ---
+
+# 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