Chess-Nut-Engine/chess-sft-corpus-4x-eval

Chess SFT Eval and Benchmark

Held-out evaluation splits and a frozen benchmark for Chess-Nut-Engine/chess-sft-corpus-4x. Every FEN in these files is excluded from generated training data (the blocklist is game-scoped: sibling positions of eval games are excluded too).

• Frozen from the 4x corpus generation run of 2026-07-06 (generator revision 3cd161b1078cdfa6598fba939f40250072adb524)
• Benchmark: 13,000 frozen examples across 9 splits; eval splits share the game-scoped blocklist (182,061 FENs) excluded from the training corpus

Eval examples	13,000
Benchmark examples	13,000
Format	JSONL

Loading

from datasets import load_dataset

eval_ds = load_dataset("Chess-Nut-Engine/chess-sft-corpus-4x-eval", "eval_splits")
bench_ds = load_dataset("Chess-Nut-Engine/chess-sft-corpus-4x-eval", "benchmark")

Eval Splits

Split	Description	Examples	Size
chess960	Fischer Random positions	500	0.1 MB
endgames	Tablebase-backed endgame play	1,500	0.2 MB
evaluation	Position assessment	1,500	0.3 MB
mate	MATE move-choice examples	1,000	0.1 MB
openings	Opening knowledge with ECO holdout	500	0.2 MB
perception	Board reading and representation	2,000	0.3 MB
planning	Best move, puzzle, and consequence tasks	2,000	1.0 MB
rules	Move legality and chess rules	2,000	0.3 MB
tactics	Tactical motifs and puzzle labels	2,000	1.0 MB

Frozen Benchmark

Split	Description	Examples	Size
chess960	Fischer Random positions	500	0.2 MB
endgames	Tablebase-backed endgame play	1,500	0.5 MB
evaluation	Position assessment	1,500	0.7 MB
mate	MATE move-choice examples	1,000	0.4 MB
openings	Opening knowledge with ECO holdout	500	0.3 MB
perception	Board reading and representation	2,000	1.5 MB
planning	Best move, puzzle, and consequence tasks	2,000	1.4 MB
rules	Move legality and chess rules	2,000	1.6 MB
tactics	Tactical motifs and puzzle labels	2,000	1.4 MB