Add dataset card

README.md

@@ -1,42 +1,52 @@
 ---
-dataset_info:
-  features:
-  - name: id
-    dtype: int64
-  - name: subfield
-    dtype: string
-  - name: context
-    dtype: 'null'
-  - name: question
-    dtype: string
-  - name: solution
-    sequence: string
-  - name: final_answer
-    sequence: string
-  - name: is_multiple_answer
-    dtype: bool
-  - name: unit
-    dtype: string
-  - name: answer_type
-    dtype: string
-  - name: error
-    dtype: string
-  - name: answer
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 1248385
-    num_examples: 575
-  - name: test
-    num_bytes: 117401
-    num_examples: 100
-  download_size: 643757
-  dataset_size: 1365786
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
-  - split: test
-    path: data/test-*
+license: mit
+task_categories:
+- question-answering
+language:
+- en
+tags:
+- olympiad
+- mathematics
+- competition
+size_categories:
+- 1K<n<10K
 ---
+
+# OlympiadBench (Split Version)
+
+This dataset is a split version of the original [knoveleng/OlympiadBench](https://huggingface.co/datasets/knoveleng/OlympiadBench) dataset.
+
+## Dataset Description
+
+This dataset contains mathematical olympiad problems with their solutions, split into training and test sets.
+
+## Dataset Structure
+
+- **Train split**: 575 examples
+- **Test split**: 100 examples (last 100 examples from original dataset)
+
+### Data Fields
+
+- `question`: The olympiad problem statement
+- `answer`: The solution to the problem
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+# Load the entire dataset
+dataset = load_dataset("weijiezz/OlympiadBench-split")
+
+# Load specific splits
+train_dataset = load_dataset("weijiezz/OlympiadBench-split", split="train")
+test_dataset = load_dataset("weijiezz/OlympiadBench-split", split="test")
+```
+
+## Source
+
+This dataset is derived from [knoveleng/OlympiadBench](https://huggingface.co/datasets/knoveleng/OlympiadBench).
+
+## License
+
+MIT License (following the original dataset)