Update README.md

README.md

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 ---
+language: en
 license: mit
+tags:
+  - tic-tac-toe
+  - xo
+  - synthetic
+  - board-game
+  - classification
+task_categories:
+  - text-classification
+size_categories:
+  - 10K<n<100K
+pretty_name: "FemtoXO Dataset (Synthetic XO Games)"
+configs:
+  - config_name: default
+    data_files: data.jsonl
 ---
+
+# FemtoXO Dataset – Synthetic Tic‑Tac‑Toe Games
+
+**FemtoXO Dataset** is a large collection of board states and moves from randomly played Tic‑Tac‑Toe games.  
+It was created to train the [FemtoXO model](https://huggingface.co/your-username/FemtoXO), a tiny Transformer that plays as **X**.
+
+## Dataset Summary
+
+Each row represents one board position **where it is X’s turn to play**, along with the move X made in that turn.  
+The dataset is entirely synthetic and was generated programmatically by simulating 10,000 full random games and recording every X‑turn state.
+
+- **Total samples:** ≈ 90,000 (varies slightly due to different game lengths)
+- **Format:** JSON Lines (`.jsonl`)
+- **Language:** not applicable (board symbols)
+
+## Data Structure
+
+Each line is a JSON object with two fields:
+
+| Field   | Type    | Description |
+|---------|---------|-------------|
+| `board` | string (length 9) | Board state: `.` = empty, `X` = player X, `O` = player O |
+| `move`  | integer (0–8) | The index of the cell (0‑based, row‑major) chosen by X |
+
+**Example:**
+```json
+{"board": "X..O.....", "move": 4}
+```
+
+## Data Splits
+
+The data is provided as a single file (`data.jsonl`) containing all samples.  
+During training we typically split it into:
+- **Train:** 90%
+- **Validation:** 10%
+
+## Generation Process
+
+1. Start with an empty 3×3 board (all `.`).
+2. Players alternate turns (`X` first, then `O`), each choosing a random legal move.
+3. Before every X move, save the current board state and the chosen move.
+4. Game ends on a win or a draw (board full).
+
+The complete generator script is available in the [FemtoXO repository](https://huggingface.co/your-username/FemtoXO) under `src/train.py`.
+
+## Usage
+
+You can load the dataset directly with 🤗 Datasets:
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("your-username/femto-xo")
+print(dataset['train'][0])
+```
+
+## Known Limitations
+
+- **Random strategy:** Moves are chosen uniformly, so the dataset does **not** contain optimal/Minimax play. A model trained on this data will learn only to avoid immediate mistakes but not to force a win/draw optimally.
+- **No board rotation/augmentation:** All boards are in fixed orientation. You can apply data augmentation (rotations/reflections) during training to improve robustness.
+
+## Citation
+
+If you use this dataset, please cite:
+
+```
+@dataset{femto-xo,
+  author    = {Abdelkader Hazerchi},
+  title     = {FemtoXO Dataset: Synthetic Tic‑Tac‑Toe Games},
+  year      = {2025},
+  url       = {https://huggingface.co/datasets/abdelkader-dev/femto-xo-dataset-json}
+}
+```
+
+## License
+
+MIT – feel free to use, modify, and share.