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: Specter
+tags:
+- sentence-transformers
 dataset_info:
 - config_name: pair
   features:
@@ -36,3 +48,39 @@ configs:
   - split: train
     path: triplet/train-*
 ---
+
+# Dataset Card for Specter
+
+This dataset is a collection of title-related-unrelated triplets from Scientific Publications on Specter. See [Specter](https://github.com/allenai/specter) for additional information.
+This dataset can be used directly with Sentence Transformers to train embedding models.
+
+## Dataset Subsets
+
+### `triplet` subset
+
+* Columns: "anchor", "positive", "negative"
+* Column types: `str`, `str`, `str`
+* Examples:
+    ```python
+    {
+      'anchor': "Integrating children's contributions in the interaction design process",
+      'positive': 'Designing for or designing with? Informant design for interactive learning environments',
+      'negative': 'Power Operation in ISD: Technological Frames Perspectives.',
+    }
+    ```
+* Collection strategy: Reading the Specter dataset from [embedding-training-data](https://huggingface.co/datasets/sentence-transformers/embedding-training-data), followed by deduplication.
+* Deduplified: Yes
+
+### `pair` subset
+
+* Columns: "anchor", "positive"
+* Column types: `str`, `str`
+* Examples:
+    ```python
+    {
+      'anchor': 'Time-dependent trajectory regression on road networks via multi-task learning',
+      'positive': 'Convex multi-task feature learning',
+    }
+    ```
+* Collection strategy: Reading the Specter dataset from [embedding-training-data](https://huggingface.co/datasets/sentence-transformers/embedding-training-data), only taking the title and related title, and then performing deduplication.
+* Deduplified: Yes