!! latest version !!Windows x64 for Haswell CPUsWindows x64 for modern computers + AVX2Windows x64 for modern computersWindows x64 + SSSE3Windows x64Linux x64 for Haswell CPUsLinux x64 for modern computers + AVX2Linux x64 for modern computersLinux x64 + SSSE3Linux x64Author: Joost VandeVondele
Date: Fri Nov 26 18:16:04 2021 +0100
Timestamp: 1637946964
Update default net to nn-3678835b1d3d.nnue
New net trained with nnue-pytorch, started from the master net on a data set of Leela
(T60.binpack+T74.binpck) and Stockfish data (wrongIsRight_nodes5000pv2.binpack),
available as a single interleaved binpack:
https://drive.google.com/file/d/12uWZIA3F2cNbraAzQNb1jgf3tq_6HkTr/view?usp=sharing The nnue-pytorch branch used is
https://github.com/vondele/nnue-pytorch/tree/wdl, which
has the new feature to filter positions based on the likelihood of the current evaluation
leading to the game outcome. It should make it less likely to try to learn from
misevaluated positions. Standard options have been used, starting from the master net:
--gpus 1 --threads 4 --num-workers 4 --batch-size 16384 --progress_bar_refresh_rate 300
--smart-fen-skipping --random-fen-skipping 12 --features=HalfKAv2_hm^ --lambda=1.0
Testing with games shows neutral Elo at STC, and good performance at LTC:
STC:
https://tests.stockfishchess.org/tests/view/619eb597c0a4ea18ba95a4dc ELO: -0.44 +-1.8 (95%) LOS: 31.2%
Total: 40000 W: 10447 L: 10498 D: 19055
Elo -0.44Ptnml(0-2): 254, 4576, 10260, 4787, 123
LTC:
https://tests.stockfishchess.org/tests/view/619f6e87c0a4ea18ba95a53f ELO: 3.30 +-1.8 (95%) LOS: 100.0%
Total: 33062 W: 8560 L: 8246 D: 16256
Elo +3.30Ptnml(0-2): 54, 3358, 9352, 3754, 13
passed LTC SPRT:
https://tests.stockfishchess.org/tests/view/61a0864e8967bbf894416e65 LLR: 2.94 (-2.94,2.94) <0.50,3.00>
Total: 29376 W: 7663 L: 7396 D: 14317
Elo +3.16Ptnml(0-2): 67, 3017, 8205, 3380, 19
closes
https://github.com/official-stockfish/Stockfish/pull/3808 Bench: 7011501
see source 
