Update README.md

README.md

@@ -24,15 +24,6 @@ tags:
 
 # 🌍 Dataset Card for Real-World Distribution Shifts (RWDS)
 
-## 📋 Table of Contents
-- [Dataset Description](#dataset-description)
-- [Dataset Summary](#dataset-summary)
-- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
-- [Languages](#languages)
-- [Dataset Structure](#dataset-structure)
-- [Dataset Creation](#dataset-creation)
-- [Considerations for Using the Data](#considerations-for-using-the-data)
-- [Additional Information](#additional-information)
 
 ## 📊 Dataset Description
 
@@ -46,7 +37,7 @@ tags:
 
 The Real-World Distribution Shifts (RWDS) dataset is a suite of three novel domain generalisation benchmarking datasets that focus on humanitarian and climate change applications. These datasets enable the investigation of spatial domain shifts in satellite imagery-based object detection under real-world scenarios.
 
-RWDS addresses the lack of standardized benchmark datasets for assessing object detection under realistic domain generalisation scenarios. The datasets evaluate model robustness when target distributions differ from source data, particularly focusing on spatial domain shifts caused by climate zones, geographic regions, and disaster events.
+RWDS addresses the lack of standardised benchmark datasets for assessing object detection under realistic domain generalisation scenarios. The datasets evaluate model robustness when target distributions differ from source data, particularly focusing on spatial domain shifts caused by climate zones, geographic regions, and disaster events.
 
 ### 🏆 Supported Tasks and Leaderboards
 
@@ -85,7 +76,7 @@ Each data instance contains and falls within a specific domain in RWDS-CZ, RWDS-
 #### RWDS-HE (Hurricane Events)
 - `image`: PIL Image object
 - `objects`: List of bounding boxes with binary damage classification  
-- `domain`: One of ["Florence", "Michael", "Harvey", "Matthew"]
+- Domain: One of ["Florence", "Michael", "Harvey", "Matthew"]
 - Task: Detecting damaged buildings across different hurricane events.
 
 ### 📊 Data Splits