Improve dataset card and add metadata

This PR improves the dataset card by:

- Adding essential metadata, including `task_categories`, `license`, and relevant `tags`.
- Providing a more concise and informative description of the dataset in the markdown section. The current description is too detailed and replicates the Github README.
- Removing unnecessary technical details from the card.

The current metadata is overly technical and doesn't provide the necessary information for users to understand the dataset at a glance. This PR addresses this.

README.md

@@ -1,35 +1,29 @@
 ---
-dataset_info:
-  features:
-  - name: width
-    dtype: int64
-  - name: height
-    dtype: int64
-  - name: total_regions
-    dtype: int64
-  - name: region_types
-    dtype: string
-  - name: text_types
-    dtype: string
-  - name: normalized_bounding_boxes
-    dtype: string
-  - name: category
-    dtype: string
-  - name: image
-    dtype: image
-  splits:
-  - name: train
-    num_bytes: 734884430.593
-    num_examples: 1701
-  download_size: 682479522
-  dataset_size: 734884430.593
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
+license: mit
+task_categories:
+- image-segmentation
+tags:
+  - arabic
+  - ocr
+  - document-understanding
+  - layout-analysis
+  - table-recognition
+  - chart-recognition
+  - vqa
+  - benchmark
 ---
 
-**Please see paper & code for more information:**
-- https://github.com/mbzuai-oryx/KITAB-Bench
-- https://arxiv.org/abs/2502.14949
+KITAB-Bench is a comprehensive benchmark for Arabic OCR and document understanding. It evaluates performance across multiple tasks, including OCR, layout detection, table recognition, chart extraction, and visual question answering (VQA). The benchmark includes diverse document types from 9 major domains and 36 sub-domains, offering a robust evaluation of Arabic document processing capabilities.
+
+**Key Features:**
+
+* **Diverse Datasets:**  Covers various document types (PDFs, handwritten text, tables, charts, etc.).
+* **Multiple Tasks:** Evaluates OCR, layout detection, table recognition, chart extraction, and VQA.
+* **Comprehensive Evaluation:** Uses established and novel metrics tailored to Arabic document processing.
+* **Strong Baselines:** Provides performance results for leading models, including GPT-4o and Gemini.
+
+**Paper:** [KITAB-Bench: A Comprehensive Multi-Domain Benchmark for Arabic OCR and Document Understanding](https://arxiv.org/abs/2502.14949)
+
+**Code:** [https://github.com/mbzuai-oryx/KITAB-Bench](https://github.com/mbzuai-oryx/KITAB-Bench)
+
+**Project Page:** [https://mbzuai-oryx.github.io/KITAB-Bench/](https://mbzuai-oryx.github.io/KITAB-Bench/)