license: cc-by-nc-4.0
task_categories:
- reinforcement-learning
- tabular-classification
language:
- en
tags:
- chess
- gambitflow
- big-data
- elite
- sqlite
size_categories:
- 1M<n<10M
pretty_name: GambitFlow Elite Training Data
📚 GambitFlow Elite Training Data
📖 Dataset Description
This dataset is the highly curated input required to train strong, club-level chess evaluation models like the Nexus-core CE. It is designed to maximize the signal-to-noise ratio in chess data by removing moves made by lower-rated players.
By exclusively training on Elite-level games, the resulting AI avoids learning common amateur mistakes and focuses on solid positional principles.
🛠️ Data Engineering & Filtering
The database was created through a multi-stage, streaming pipeline to handle the massive volume efficiently without memory overflow.
- Source: Lichess Public Database (January 2017).
- CRITICAL FILTER: Only games where White ELO > 2000 AND Black ELO > 2000 were accepted.
- Extraction: Positions (FENs) were extracted only up to the first 20 moves of each filtered game (the Opening/Early Middlegame phase).
- Optimization: The data was aggregated by unique FEN and stored in a compressed SQLite file.
- Final Volume: Over 5,000,000 Total Positions processed, resulting in 2,488,753 Unique Positions.
- File Size: 882 MB.
📂 File Structure & Schema
The main file is chess_stats_v2.db.
Table: positions
| Column | Type | Description |
|---|---|---|
fen |
TEXT (Primary Key) | The board position. Truncated to 4 parts (Position, Turn, Castling, En Passant) for maximum data aggregation across transpositions. |
stats |
TEXT (JSON) | JSON string containing aggregated move counts and game outcomes (W/D/L) for subsequent training. |
🚀 Usage (Model Training)
This database is meant to be read by the SQLiteIterableDataset class in PyTorch, ensuring only small batches of data are streamed at a time, preventing RAM crashes even with large datasets.
⚠️ License
This dataset is licensed under CC BY-NC 4.0. It is a derivative work of the Lichess Open Database (CC0). Commercial use is strictly prohibited.
Curated by GambitFlow