Add dataset card

README.md

@@ -1,36 +1,60 @@
 ---
-dataset_info:
-  features:
-  - name: id
-    dtype: string
-  - name: query
-    dtype: string
-  - name: answer
-    dtype: string
-  - name: text
-    dtype: string
-  - name: choices
-    sequence: string
-  - name: gold
-    dtype: int64
-  - name: category
-    dtype: string
-  - name: original_sentiment
-    dtype: string
-  splits:
-  - name: validation
-    num_bytes: 127753
-    num_examples: 20
-  - name: test
-    num_bytes: 112975
-    num_examples: 20
-  download_size: 134577
-  dataset_size: 240728
-configs:
-- config_name: default
-  data_files:
-  - split: validation
-    path: data/validation-*
-  - split: test
-    path: data/test-*
+language:
+- ar
+license: apache-2.0
+task_categories:
+- multiple-choice
+- text-classification
+pretty_name: Sentiment Analysis MCQ Evaluation Dataset
+tags:
+- sentiment-analysis
+- mcq
+- financial
+- arabic
+- evaluation
+- benchmark
 ---
+
+# Sentiment Analysis MCQ Evaluation Dataset
+
+Validation and test splits for financial sentiment analysis in MCQ format.
+
+## Dataset Structure
+
+- **Format**: Multiple choice questions
+- **Language**: Arabic
+- **Domain**: Financial reports
+- **Task**: Sentiment classification
+- **Validation**: 20 examples
+- **Test**: 20 examples
+
+## Fields
+
+- `id`: Unique identifier
+- `query`: Full MCQ prompt
+- `answer`: Correct answer letter
+- `text`: Question text
+- `choices`: Answer options [a, b, c]
+- `gold`: Correct answer index
+- `category`: Report category
+- `original_sentiment`: Ground truth sentiment
+
+## Answer Mapping
+
+- a) positive - gold: 0
+- b) negative - gold: 1
+- c) neutral - gold: 2
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("SahmBenchmark/Sentiment_Analysis_MCQ_eval")
+test_data = dataset['test']
+
+for example in test_data:
+    print(f"Question: {example['text']}")
+    print(f"Choices: {example['choices']}")
+    print(f"Correct: {example['answer']} (index: {example['gold']})")
+```