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README.md

@@ -1,22 +1,40 @@
 ---
-dataset_info:
-  features:
-  - name: labels
-    dtype: int64
-  - name: time_series
-    list:
-      list: float64
-  - name: texts
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 14531856
-    num_examples: 13160
-  download_size: 5211512
-  dataset_size: 14531856
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
+license: mit
+task_categories:
+- time-series-forecasting
+- text-classification
+language:
+- ko
+size_categories:
+- 1K<n<10K
 ---
+
+# TIPS Raw Test Dataset
+
+## Dataset Description
+
+Raw OHLCV test data for multimodal stock anomaly prediction.
+No technical indicators, no normalization/scaling applied.
+
+### Key Configuration
+
+- **Sequence Length**: 10
+- **Features**: ['open', 'high', 'low', 'close', 'volume'] (raw values)
+- **Test Ratio**: 30% (most recent data)
+- **Undersampling**: Majority class reduced to 10%
+- **Label Distribution**: {0: 13116, 1: 44}
+- **Total Samples**: 13160
+
+### Data Fields
+
+- `labels`: int - Binary label (0: normal, 1: anomaly)
+- `time_series`: array [10, 5] - Raw OHLCV values
+- `texts`: string - Korean news text
+
+### Usage
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("k-datasoft/Multimodal-test-dataset")
+```