Datasets:
FEN
stringlengths 28
78
| Evaluation
stringlengths 1
6
|
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rnbqkbnr/pppp1ppp/4p3/8/4P3/8/PPPP1PPP/RNBQKBNR w KQkq - 0 2 | +56 |
rnbqkbnr/pppp1ppp/4p3/8/3PP3/8/PPP2PPP/RNBQKBNR b KQkq - 0 2 | -9 |
rnbqkbnr/ppp2ppp/4p3/3p4/3PP3/8/PPP2PPP/RNBQKBNR w KQkq - 0 3 | +52 |
rnbqkbnr/ppp2ppp/4p3/3p4/3PP3/8/PPPN1PPP/R1BQKBNR b KQkq - 1 3 | -26 |
rnbqkb1r/ppp2ppp/4pn2/3p4/3PP3/8/PPPN1PPP/R1BQKBNR w KQkq - 2 4 | +50 |
rnbqkb1r/ppp2ppp/4pn2/3pP3/3P4/8/PPPN1PPP/R1BQKBNR b KQkq - 0 4 | +10 |
rnbqkb1r/pppn1ppp/4p3/3pP3/3P4/8/PPPN1PPP/R1BQKBNR w KQkq - 1 5 | +75 |
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r1b4k/p5p1/4pq2/1p1p4/2n2P2/P2B4/1PQ4P/1K1R3R w - - 0 24 | +569 |
r1b4k/p5p1/4pq2/1p1p4/2n2P2/P2B4/1P2Q2P/1K1R3R b - - 1 24 | +353 |
r6k/p2b2p1/4pq2/1p1p4/2n2P2/P2B4/1P2Q2P/1K1R3R w - - 2 25 | +345 |
r6k/p2b2p1/4pq2/1p1p4/2n2P2/P2B4/1P2Q2P/1K1R2R1 b - - 3 25 | +331 |
r3b2k/p5p1/4pq2/1p1p4/2n2P2/P2B4/1P2Q2P/1K1R2R1 w - - 4 26 | +384 |
r3b2k/p5p1/4pq2/1p1p4/2n2P2/P2B4/1P2Q2P/1K2R1R1 b - - 5 26 | +300 |
r6k/p4bp1/4pq2/1p1p4/2n2P2/P2B4/1P2Q2P/1K2R1R1 w - - 6 27 | +357 |
r6k/p4bp1/4pq2/1p1p4/2n2P2/P2B2R1/1P2Q2P/1K2R3 b - - 7 27 | +327 |
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7k/p1r2b2/4pq2/1p1p1nR1/5P2/P2B4/1P2Q2P/1K4R1 w - - 3 31 | #+6 |
7k/p1r2b2/4pq2/1p1p1BR1/5P2/P7/1P2Q2P/1K4R1 b - - 0 31 | #+6 |
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rnb1kbnr/pp3ppp/3qp3/8/2Bp4/5N2/PPPN1PPP/R1BQ1RK1 b kq - 3 7 | +4 |
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r3k2r/1b3ppp/pq2p3/2b5/Pp4n1/3B1N2/1PP1QPPP/R1B2RK1 w kq - 0 17 | 0 |
r3k2r/1b3ppp/pq2p3/2b5/Pp4n1/3B1N1P/1PP1QPP1/R1B2RK1 b kq - 0 17 | -25 |
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r3k2r/1b3ppp/pq2pn2/2b3B1/Pp6/3B1N1P/1PP1QPP1/R4RK1 b kq - 2 18 | -56 |
r3k2r/1b3ppp/pq2p3/2b3Bn/Pp6/3B1N1P/1PP1QPP1/R4RK1 w kq - 3 19 | 0 |
r3k2r/1b3ppp/pq2p3/2b4n/Pp6/3BBN1P/1PP1QPP1/R4RK1 b kq - 4 19 | -23 |
r3k2r/1b3ppp/pq2p3/7n/Pp6/3BbN1P/1PP1QPP1/R4RK1 w kq - 0 20 | -6 |
r3k2r/1b3ppp/pq2p3/7n/Pp6/3BQN1P/1PP2PP1/R4RK1 b kq - 0 20 | -49 |
r3k2r/1b3ppp/p3p3/7n/Pp6/3BqN1P/1PP2PP1/R4RK1 w kq - 0 21 | 0 |
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r3k2r/1b3ppp/p3p3/8/Pp6/3BPNnP/1PP3P1/R4RK1 w kq - 1 22 | 0 |
End of preview. Expand
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Chess Evaluations Dataset
This dataset contains chess positions represented in FEN (Forsyth-Edwards Notation) along with their evaluations and next moves for tactical evals. The dataset is divided into three configurations:
- tactics: Includes chess positions, their evaluations, and the best move in the position.
- randoms: Contains random chess positions and their evaluations.
- chess_data: General chess positions with evaluations.
This is an in progress dataset which contains millions of positions with stockfish 11 (depth 22) evaluations. Please help contribute evaluations of the positions to the repo, the original owner of the dataset is r2dev2.
❗❗❗ Updates to the original dataset will be on the version hosted on kaggle.
Dataset Structure
Each configuration can be loaded separately:
- tactics: Columns -
FEN
,Evaluation
,Move
- randoms: Columns -
FEN
,Evaluation
- chess_data: Columns -
FEN
,Evaluation
Usage
You can load each configuration using the datasets
library:
from datasets import load_dataset
# Load the tactics dataset
tactics_dataset = load_dataset("someshsingh22/chess-evaluations", "tactics")
# Load the randoms dataset
randoms_dataset = load_dataset("someshsingh22/chess-evaluations", "randoms")
Contributing
To get started download a pre-built executable from the releases of chess contributor and run it.
The evaluation should go in eval folder under same name
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