Create README.md

README.md

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+---
+license: mit
+task_categories:
+- feature-extraction
+- sentence-similarity
+language:
+- en
+size_categories:
+- 1K<n<10K
+annotations_creators:
+- expert-generated
+language_creators:
+- expert-generated
+source_datasets:
+- original
+task_ids:
+- semantic-similarity
+---
+
+# Dataset Card for FinSTS Golden Dataset
+
+## Table of Contents
+- [Dataset Summary](#dataset-summary)
+- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+- [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+- [Data Splits](#data-splits)
+- [Dataset Creation](#dataset-creation)
+- [Citing & Authors](#citing--authors)
+
+## Dataset Summary
+
+The FinSTS Golden Dataset is designed for financial semantic textual similarity tasks. It contains a development set of 2001 sentence pairs and a test set of 1999 sentence pairs, annotated to reflect the degree of semantic similarity between financial texts. This dataset is ideal for training and evaluating models in financial text analysis, clustering, and semantic search.
+
+## Supported Tasks and Leaderboards
+
+- **Text Similarity**: This dataset can be used to train models to measure the semantic similarity between pairs of financial sentences.
+- **Clustering**: The dataset can be utilized to cluster sentences based on their semantic content.
+- **Semantic Search**: It is useful for creating models that improve search results by understanding the semantic meaning of queries and documents.
+
+## Languages
+
+The dataset is in English.
+
+## Dataset Structure
+
+### Data Fields
+
+- `sentence1`: The first sentence in the pair.
+- `sentence2`: The second sentence in the pair.
+- `similarity_score`: A score between 0 and 5 indicating the degree of semantic similarity between the two sentences.
+
+### Example
+
+```json
+{
+  "sentence1": "The company's revenue grew significantly.",
+  "sentence2": "The firm experienced a substantial increase in sales.",
+  "similarity_score": 4.5
+}