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596a528c6a
Created by retraining the master net with Leela T78 data from Aug+Sep 2022 added to the previous best dataset. Trained with end lambda 0.7 and started with max epoch 800. All positions with ply <= 28 were skipped: ``` python easy_train.py \ --experiment-name leela95-dfrc96-filt-only-T80octnov-T60novdecT78augsepT79aprmay-12tb7p-sk28-lambda7 \ --training-dataset /data/leela95-dfrc96-filt-only-T80octnov-T60novdecT78augsepT79aprmay-12tb7p.binpack \ --nnue-pytorch-branch linrock/nnue-pytorch/misc-fixes-skip-ply-lteq-28 \ --start-from-engine-test-net True \ --gpus "0," \ --start-lambda 1.0 \ --end-lambda 0.7 \ --gamma 0.995 \ --lr 4.375e-4 \ --tui False \ --seed $RANDOM \ --max_epoch 800 ``` Around epoch 750, training was manually paused and max epoch increased to 950 before resuming. The additional Leela training data from T78 was prepared in the same way as the previous best dataset. The exact training data used can be found at: https://robotmoon.com/nnue-training-data/ While the local elo ratings during this experiment were much lower than in recent master nets, several later epochs had a consistent elo above zero, and this was hypothesized to represent potential strength at slower time controls. Local elo at 25k nodes per move leela95-dfrc96-filt-only-T80octnov-T60novdecT78augsepT79aprmay-12tb7p-sk28-lambda7 nn-epoch819.nnue : 0.4 +/- 1.1 (nn-bc24c101ada0.nnue) nn-epoch799.nnue : 0.3 +/- 1.2 nn-epoch759.nnue : 0.3 +/- 1.1 nn-epoch839.nnue : 0.2 +/- 1.4 Passed STC https://tests.stockfishchess.org/tests/view/63cabf6f0eefe8694a0c6013 LLR: 2.94 (-2.94,2.94) <0.00,2.00> Total: 41608 W: 11161 L: 10848 D: 19599 Ptnml(0-2): 116, 4496, 11281, 4781, 130 Passed LTC https://tests.stockfishchess.org/tests/view/63cb1856344bb01c191af263 LLR: 2.95 (-2.94,2.94) <0.50,2.50> Total: 76760 W: 20517 L: 20137 D: 36106 Ptnml(0-2): 34, 7435, 23070, 7799, 42 closes https://github.com/official-stockfish/Stockfish/pull/4351 bench 3941848
63 lines
1.8 KiB
C++
63 lines
1.8 KiB
C++
/*
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Stockfish, a UCI chess playing engine derived from Glaurung 2.1
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Copyright (C) 2004-2023 The Stockfish developers (see AUTHORS file)
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Stockfish is free software: you can redistribute it and/or modify
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it under the terms of the GNU General Public License as published by
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the Free Software Foundation, either version 3 of the License, or
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(at your option) any later version.
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Stockfish is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU General Public License for more details.
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You should have received a copy of the GNU General Public License
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along with this program. If not, see <http://www.gnu.org/licenses/>.
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*/
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#ifndef EVALUATE_H_INCLUDED
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#define EVALUATE_H_INCLUDED
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#include <string>
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#include <optional>
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#include "types.h"
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namespace Stockfish {
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class Position;
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namespace Eval {
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std::string trace(Position& pos);
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Value evaluate(const Position& pos, int* complexity = nullptr);
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extern bool useNNUE;
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extern std::string currentEvalFileName;
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// The default net name MUST follow the format nn-[SHA256 first 12 digits].nnue
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// for the build process (profile-build and fishtest) to work. Do not change the
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// name of the macro, as it is used in the Makefile.
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#define EvalFileDefaultName "nn-bc24c101ada0.nnue"
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namespace NNUE {
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std::string trace(Position& pos);
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Value evaluate(const Position& pos, bool adjusted = false, int* complexity = nullptr);
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void init();
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void verify();
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bool load_eval(std::string name, std::istream& stream);
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bool save_eval(std::ostream& stream);
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bool save_eval(const std::optional<std::string>& filename);
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} // namespace NNUE
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} // namespace Eval
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} // namespace Stockfish
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#endif // #ifndef EVALUATE_H_INCLUDED
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