Update README.md

README.md

@@ -1,36 +1,25 @@
 ---
-library_name: autogluon
-license: mit
+license: other
 tags:
-- tabular-classification
-- automl
-- autogluon
-datasets:
-- Iris314/Youtube_music_comments
-metrics:
-- accuracy
-- f1
+- tabular
+- students
+- sleep
+- regression
+pretty_name: Students Sleep (Original & Augmented)
+task_categories:
+- tabular-regression
+task_ids:
+- regression
 ---
 
-# Tabular AutoML (AutoGluon)
+# Students Sleep (Original & Augmented)
 
-**Task:** Classification
-**Dataset:** `Iris314/Youtube_music_comments` (classmate HW1 dataset)
-**Target column:** `label`
+**Summary:** Tabular dataset about students with target column `sleep_hours`. Two splits are provided:
+`original` and `augmented`. Each split shares the same schema; the target is `sleep_hours` (numeric).
 
-## Best Model
-- **Name:** `WeightedEnsemble_L2`
-- **Hyperparameters:** See below (AutoGluon model_hyperparams for best model)
-
-## Results
-- **Hold-out (same distribution as training):**
-  - Accuracy = 0.9905
-  - Weighted F1 = 0.9905
-
-- **Additional check (original split):**
-  - Accuracy = 1.0000
-  - Weighted F1 = 1.0000
-
-## Notes
-- Trained with `presets="best_quality"`, `time_limit=300`.
-- AutoGluon ensembles classical ML models and tunes hyperparameters automatically.
+## Load
+```python
+from datasets import load_dataset
+ds = load_dataset("Iris314/Students_sleep_tabular")
+original  = ds["original"]
+augmented = ds["augmented"]