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Created by retraining the sparsified master net (nn-cd2ff4716c34.nnue) on a 100% minified dataset including Leela transformers data from T80 may2023. Weights permuted with the exact methods and code in: official-stockfish#4620 LEB128 compression done with the new serialize.py param in: official-stockfish/nnue-pytorch#251 Initially trained with max epoch 800. Around epoch 780, training was paused and max epoch raised to 960. python3 easy_train.py \ --experiment-name L1-1536-sparse-master-retrain \ --training-dataset /data/leela96-dfrc99-v2-T60novdecT77decT78jantosepT79aprmayT80juntonovjan-v6dd-T80febtomay2023.min.binpack \ --early-fen-skipping 27 \ --start-from-engine-test-net True \ --max_epoch 960 \ --lr 4.375e-4 \ --gamma 0.995 \ --start-lambda 1.0 \ --end-lambda 0.7 \ --tui False \ --seed $RANDOM \ --gpus 0 For preparing the training dataset (interleaved size 328G): python3 interleave_binpacks.py \ leela96-filt-v2.min.binpack \ dfrc99-16tb7p-eval-filt-v2.min.binpack \ filt-v6-dd-min/test60-novdec2021-12tb7p-filter-v6-dd.min.binpack \ filt-v6-dd-min/test77-dec2021-16tb7p-filter-v6-dd.min.binpack \ filt-v6-dd-min/test78-jantomay2022-16tb7p-filter-v6-dd.min.binpack \ filt-v6-dd-min/test78-juntosep2022-16tb7p-filter-v6-dd.min.binpack \ filt-v6-dd-min/test79-apr2022-16tb7p-filter-v6-dd.min.binpack \ filt-v6-dd-min/test79-may2022-16tb7p-filter-v6-dd.min.binpack \ filt-v6-dd-min/test80-jun2022-16tb7p-filter-v6-dd.min.binpack \ filt-v6-dd-min/test80-jul2022-16tb7p-filter-v6-dd.min.binpack \ filt-v6-dd-min/test80-aug2022-16tb7p-filter-v6-dd.min.binpack \ filt-v6-dd-min/test80-sep2022-16tb7p-filter-v6-dd.min.binpack \ filt-v6-dd-min/test80-oct2022-16tb7p-filter-v6-dd.min.binpack \ filt-v6-dd-min/test80-nov2022-16tb7p-filter-v6-dd.min.binpack \ filt-v6-dd-min/test80-jan2023-16tb7p-filter-v6-dd.min.binpack \ test80-2023/test80-feb2023-16tb7p-no-db.min.binpack \ test80-2023/test80-mar2023-2tb7p-no-db.min.binpack \ test80-2023/test80-apr2023-2tb7p-no-db.min.binpack \ test80-2023/test80-may2023-2tb7p-no-db.min.binpack \ /data/leela96-dfrc99-v2-T60novdecT77decT78jantosepT79aprmayT80juntonovjan-v6dd-T80febtomay2023.min.binpack Minified binpacks and Leela T80 training data from 2023 available at: https://robotmoon.com/nnue-training-data/ Local elo at 25k nodes per move: nn-epoch879.nnue : 3.9 +/- 5.7 Passed STC: https://tests.stockfishchess.org/tests/view/64928c1bdc7002ce609c7690 LLR: 2.94 (-2.94,2.94) <0.00,2.00> Total: 72000 W: 19242 L: 18889 D: 33869 Ptnml(0-2): 182, 7787, 19716, 8126, 189 Passed LTC: https://tests.stockfishchess.org/tests/view/64930a37dc7002ce609c82e3 LLR: 2.94 (-2.94,2.94) <0.50,2.50> Total: 54552 W: 14978 L: 14647 D: 24927 Ptnml(0-2): 23, 5123, 16650, 5460, 20 bench 2593605
Joachim26
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Jun 22, 2023
Created by retraining the sparsified master net (nn-cd2ff4716c34.nnue) on a 100% minified dataset including Leela transformers data from T80 may2023. Weights permuted with the exact methods and code in: official-stockfish#4620 LEB128 compression done with the new serialize.py param in: official-stockfish/nnue-pytorch#251 Initially trained with max epoch 800. Around epoch 780, training was paused and max epoch raised to 960. python3 easy_train.py \ --experiment-name L1-1536-sparse-master-retrain \ --training-dataset /data/leela96-dfrc99-v2-T60novdecT77decT78jantosepT79aprmayT80juntonovjan-v6dd-T80febtomay2023.min.binpack \ --early-fen-skipping 27 \ --start-from-engine-test-net True \ --max_epoch 960 \ --lr 4.375e-4 \ --gamma 0.995 \ --start-lambda 1.0 \ --end-lambda 0.7 \ --tui False \ --seed $RANDOM \ --gpus 0 For preparing the training dataset (interleaved size 328G): python3 interleave_binpacks.py \ leela96-filt-v2.min.binpack \ dfrc99-16tb7p-eval-filt-v2.min.binpack \ filt-v6-dd-min/test60-novdec2021-12tb7p-filter-v6-dd.min.binpack \ filt-v6-dd-min/test77-dec2021-16tb7p-filter-v6-dd.min.binpack \ filt-v6-dd-min/test78-jantomay2022-16tb7p-filter-v6-dd.min.binpack \ filt-v6-dd-min/test78-juntosep2022-16tb7p-filter-v6-dd.min.binpack \ filt-v6-dd-min/test79-apr2022-16tb7p-filter-v6-dd.min.binpack \ filt-v6-dd-min/test79-may2022-16tb7p-filter-v6-dd.min.binpack \ filt-v6-dd-min/test80-jun2022-16tb7p-filter-v6-dd.min.binpack \ filt-v6-dd-min/test80-jul2022-16tb7p-filter-v6-dd.min.binpack \ filt-v6-dd-min/test80-aug2022-16tb7p-filter-v6-dd.min.binpack \ filt-v6-dd-min/test80-sep2022-16tb7p-filter-v6-dd.min.binpack \ filt-v6-dd-min/test80-oct2022-16tb7p-filter-v6-dd.min.binpack \ filt-v6-dd-min/test80-nov2022-16tb7p-filter-v6-dd.min.binpack \ filt-v6-dd-min/test80-jan2023-16tb7p-filter-v6-dd.min.binpack \ test80-2023/test80-feb2023-16tb7p-no-db.min.binpack \ test80-2023/test80-mar2023-2tb7p-no-db.min.binpack \ test80-2023/test80-apr2023-2tb7p-no-db.min.binpack \ test80-2023/test80-may2023-2tb7p-no-db.min.binpack \ /data/leela96-dfrc99-v2-T60novdecT77decT78jantosepT79aprmayT80juntonovjan-v6dd-T80febtomay2023.min.binpack Minified binpacks and Leela T80 training data from 2023 available at: https://robotmoon.com/nnue-training-data/ Local elo at 25k nodes per move: nn-epoch879.nnue : 3.9 +/- 5.7 Passed STC: https://tests.stockfishchess.org/tests/view/64928c1bdc7002ce609c7690 LLR: 2.94 (-2.94,2.94) <0.00,2.00> Total: 72000 W: 19242 L: 18889 D: 33869 Ptnml(0-2): 182, 7787, 19716, 8126, 189 Passed LTC: https://tests.stockfishchess.org/tests/view/64930a37dc7002ce609c82e3 LLR: 2.94 (-2.94,2.94) <0.50,2.50> Total: 54552 W: 14978 L: 14647 D: 24927 Ptnml(0-2): 23, 5123, 16650, 5460, 20 closes official-stockfish#4635 bench 2593605
rn5f107s2
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Jun 22, 2023
Created by retraining the sparsified master net (nn-cd2ff4716c34.nnue) on a 100% minified dataset including Leela transformers data from T80 may2023. Weights permuted with the exact methods and code in: official-stockfish#4620 LEB128 compression done with the new serialize.py param in: official-stockfish/nnue-pytorch#251 Initially trained with max epoch 800. Around epoch 780, training was paused and max epoch raised to 960. python3 easy_train.py \ --experiment-name L1-1536-sparse-master-retrain \ --training-dataset /data/leela96-dfrc99-v2-T60novdecT77decT78jantosepT79aprmayT80juntonovjan-v6dd-T80febtomay2023.min.binpack \ --early-fen-skipping 27 \ --start-from-engine-test-net True \ --max_epoch 960 \ --lr 4.375e-4 \ --gamma 0.995 \ --start-lambda 1.0 \ --end-lambda 0.7 \ --tui False \ --seed $RANDOM \ --gpus 0 For preparing the training dataset (interleaved size 328G): python3 interleave_binpacks.py \ leela96-filt-v2.min.binpack \ dfrc99-16tb7p-eval-filt-v2.min.binpack \ filt-v6-dd-min/test60-novdec2021-12tb7p-filter-v6-dd.min.binpack \ filt-v6-dd-min/test77-dec2021-16tb7p-filter-v6-dd.min.binpack \ filt-v6-dd-min/test78-jantomay2022-16tb7p-filter-v6-dd.min.binpack \ filt-v6-dd-min/test78-juntosep2022-16tb7p-filter-v6-dd.min.binpack \ filt-v6-dd-min/test79-apr2022-16tb7p-filter-v6-dd.min.binpack \ filt-v6-dd-min/test79-may2022-16tb7p-filter-v6-dd.min.binpack \ filt-v6-dd-min/test80-jun2022-16tb7p-filter-v6-dd.min.binpack \ filt-v6-dd-min/test80-jul2022-16tb7p-filter-v6-dd.min.binpack \ filt-v6-dd-min/test80-aug2022-16tb7p-filter-v6-dd.min.binpack \ filt-v6-dd-min/test80-sep2022-16tb7p-filter-v6-dd.min.binpack \ filt-v6-dd-min/test80-oct2022-16tb7p-filter-v6-dd.min.binpack \ filt-v6-dd-min/test80-nov2022-16tb7p-filter-v6-dd.min.binpack \ filt-v6-dd-min/test80-jan2023-16tb7p-filter-v6-dd.min.binpack \ test80-2023/test80-feb2023-16tb7p-no-db.min.binpack \ test80-2023/test80-mar2023-2tb7p-no-db.min.binpack \ test80-2023/test80-apr2023-2tb7p-no-db.min.binpack \ test80-2023/test80-may2023-2tb7p-no-db.min.binpack \ /data/leela96-dfrc99-v2-T60novdecT77decT78jantosepT79aprmayT80juntonovjan-v6dd-T80febtomay2023.min.binpack Minified binpacks and Leela T80 training data from 2023 available at: https://robotmoon.com/nnue-training-data/ Local elo at 25k nodes per move: nn-epoch879.nnue : 3.9 +/- 5.7 Passed STC: https://tests.stockfishchess.org/tests/view/64928c1bdc7002ce609c7690 LLR: 2.94 (-2.94,2.94) <0.00,2.00> Total: 72000 W: 19242 L: 18889 D: 33869 Ptnml(0-2): 182, 7787, 19716, 8126, 189 Passed LTC: https://tests.stockfishchess.org/tests/view/64930a37dc7002ce609c82e3 LLR: 2.94 (-2.94,2.94) <0.50,2.50> Total: 54552 W: 14978 L: 14647 D: 24927 Ptnml(0-2): 23, 5123, 16650, 5460, 20 closes official-stockfish#4635 bench 2593605
linrock
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Sep 21, 2023
Creating this net involved: - a 6-stage training process from scratch - permuting L1 weights with official-stockfish/nnue-pytorch#254 A strong epoch after each training stage was chosen for the next. The 6 stages were: 1. 400 epochs, lambda 1.0, default LR and gamma UHOx2-wIsRight-multinet-dfrc-n5000 (135G) nodes5000pv2_UHO.binpack data_pv-2_diff-100_nodes-5000.binpack wrongIsRight_nodes5000pv2.binpack multinet_pv-2_diff-100_nodes-5000.binpack dfrc_n5000.binpack 2. 800 epochs, end-lambda 0.75, LR 4.375e-4, gamma 0.995, skip 12 LeelaFarseer-T78juntoaugT79marT80dec.binpack (141G) T60T70wIsRightFarseerT60T74T75T76.binpack test78-junjulaug2022-16tb7p.no-db.min.binpack test79-mar2022-16tb7p.no-db.min.binpack test80-dec2022-16tb7p.no-db.min.binpack 3. 800 epochs, end-lambda 0.7, LR 4.375e-4, gamma 0.995, skip 20 leela93-v1-dfrc99-v2-T78juntosepT80jan-v6dd-T78janfebT79aprT80aprmay.min.binpack leela93-filt-v1.min.binpack dfrc99-16tb7p-filt-v2.min.binpack test78-juntosep2022-16tb7p-filter-v6-dd.min-mar2023.min.binpack test80-jan2023-16tb7p.v6-sk20.min.binpack test78-janfeb2022-16tb7p.min.binpack test79-apr2022-16tb7p.min.binpack test80-apr2022-16tb7p.min.binpack test80-may2022-16tb7p.min.binpack 4. 800 epochs, end-lambda 0.7, LR 4.375e-4, gamma 0.995, skip 24 leela96-dfrc99-v2-T78juntosepT79mayT80junsepnovjan-v6dd-T80mar23-v6-T60novdecT77decT78aprmayT79aprT80may23.min.binpack leela96-filt-v2.min.binpack dfrc99-16tb7p-filt-v2.min.binpack test78-juntosep2022-16tb7p-filter-v6-dd.min.binpack test79-may2022-16tb7p.filter-v6-dd.min.binpack test80-jun2022-16tb7p.filter-v6-dd.min.binpack test80-sep2022-16tb7p.filter-v6-dd.min.binpack test80-nov2022-16tb7p.filter-v6-dd.min.binpack test80-jan2023-2tb7p.filter-v6-dd.min.binpack test80-mar2023-2tb7p.v6-sk16.min.binpack test60-novdec2021-16tb7p.min.binpack test77-dec2021-16tb7p.min.binpack test78-aprmay2022-16tb7p.min.binpack test79-apr2022-16tb7p.min.binpack test80-may2023-2tb7p.min.binpack 5. 960 epochs, end-lambda 0.7, LR 4.375e-4, gamma 0.995, skip 28 Increased max-epoch to 960 near the end of the first 800 epochs 5af11540bbfe dataset: official-stockfish#4635 6. 1000 epochs, end-lambda 0.7, LR 4.375e-4, gamma 0.995, skip 28 Increased max-epoch to 1000 near the end of the first 800 epochs 1ee1aba5ed dataset: official-stockfish#4782 L1 weights permuted with: ``` python3 serialize.py $nnue $nnue_permuted \ --features=HalfKAv2_hm \ --ft_optimize \ --ft_optimize_data=/data/fishpack32.binpack \ --ft_optimize_count=10000 ``` Speed measurements from 100 bench runs at depth 13 with profile-build x86-64-avx2: ``` sf_base = 1329051 +/- 2224 (95%) sf_test = 1163344 +/- 2992 (95%) diff = -165706 +/- 4913 (95%) speedup = -12.46807% +/- 0.370% (95%) ``` Training data can be found at: https://robotmoon.com/nnue-training-data/ Local elo at 25k nodes per move (vs. L1-2048 nn-1ee1aba5ed4c.nnue) ep959 : 16.2 +/- 2.3 Failed 10+0.1 STC: https://tests.stockfishchess.org/tests/view/6501beee2cd016da89abab21 LLR: -2.92 (-2.94,2.94) <0.00,2.00> Total: 13184 W: 3285 L: 3535 D: 6364 Ptnml(0-2): 85, 1662, 3334, 1440, 71 Failed 180+1.8 VLTC: https://tests.stockfishchess.org/tests/view/6505cf9a72620bc881ea908e LLR: -2.94 (-2.94,2.94) <0.00,2.00> Total: 64248 W: 16224 L: 16374 D: 31650 Ptnml(0-2): 26, 6788, 18640, 6650, 20 Passed 60+0.6 th 8 VLTC SMP (STC bounds): https://tests.stockfishchess.org/tests/view/65084a4618698b74c2e541dc LLR: 2.95 (-2.94,2.94) <0.00,2.00> Total: 90630 W: 23372 L: 23033 D: 44225 Ptnml(0-2): 13, 8490, 27968, 8833, 11 Passed 60+0.6 th 8 VLTC SMP: https://tests.stockfishchess.org/tests/view/6501d45d2cd016da89abacdb LLR: 2.95 (-2.94,2.94) <0.50,2.50> Total: 137804 W: 35764 L: 35276 D: 66764 Ptnml(0-2): 31, 13006, 42326, 13522, 17 bench 1246812
linrock
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Sep 21, 2023
Creating this net involved: - a 6-stage training process from scratch - permuting L1 weights with official-stockfish/nnue-pytorch#254 A strong epoch after each training stage was chosen for the next. The 6 stages were: 1. 400 epochs, lambda 1.0, default LR and gamma UHOx2-wIsRight-multinet-dfrc-n5000 (135G) nodes5000pv2_UHO.binpack data_pv-2_diff-100_nodes-5000.binpack wrongIsRight_nodes5000pv2.binpack multinet_pv-2_diff-100_nodes-5000.binpack dfrc_n5000.binpack 2. 800 epochs, end-lambda 0.75, LR 4.375e-4, gamma 0.995, skip 12 LeelaFarseer-T78juntoaugT79marT80dec.binpack (141G) T60T70wIsRightFarseerT60T74T75T76.binpack test78-junjulaug2022-16tb7p.no-db.min.binpack test79-mar2022-16tb7p.no-db.min.binpack test80-dec2022-16tb7p.no-db.min.binpack 3. 800 epochs, end-lambda 0.725, LR 4.375e-4, gamma 0.995, skip 20 leela93-v1-dfrc99-v2-T78juntosepT80jan-v6dd-T78janfebT79aprT80aprmay.min.binpack leela93-filt-v1.min.binpack dfrc99-16tb7p-filt-v2.min.binpack test78-juntosep2022-16tb7p-filter-v6-dd.min-mar2023.min.binpack test80-jan2023-3of3-16tb7p-filter-v6-dd.min-mar2023.binpack test78-janfeb2022-16tb7p.min.binpack test79-apr2022-16tb7p.min.binpack test80-apr2022-16tb7p.min.binpack test80-may2022-16tb7p.min.binpack 4. 800 epochs, end-lambda 0.7, LR 4.375e-4, gamma 0.995, skip 24 leela96-dfrc99-v2-T78juntosepT79mayT80junsepnovjan-v6dd-T80mar23-v6-T60novdecT77decT78aprmayT79aprT80may23.min.binpack leela96-filt-v2.min.binpack dfrc99-16tb7p-filt-v2.min.binpack test78-juntosep2022-16tb7p-filter-v6-dd.min.binpack test79-may2022-16tb7p.filter-v6-dd.min.binpack test80-jun2022-16tb7p.filter-v6-dd.min.binpack test80-sep2022-16tb7p.filter-v6-dd.min.binpack test80-nov2022-16tb7p.filter-v6-dd.min.binpack test80-jan2023-2tb7p.filter-v6-dd.min.binpack test80-mar2023-2tb7p.v6-sk16.min.binpack test60-novdec2021-16tb7p.min.binpack test77-dec2021-16tb7p.min.binpack test78-aprmay2022-16tb7p.min.binpack test79-apr2022-16tb7p.min.binpack test80-may2023-2tb7p.min.binpack 5. 960 epochs, end-lambda 0.7, LR 4.375e-4, gamma 0.995, skip 28 Increased max-epoch to 960 near the end of the first 800 epochs 5af11540bbfe dataset: official-stockfish#4635 6. 1000 epochs, end-lambda 0.7, LR 4.375e-4, gamma 0.995, skip 28 Increased max-epoch to 1000 near the end of the first 800 epochs 1ee1aba5ed dataset: official-stockfish#4782 L1 weights permuted with: ``` python3 serialize.py $nnue $nnue_permuted \ --features=HalfKAv2_hm \ --ft_optimize \ --ft_optimize_data=/data/fishpack32.binpack \ --ft_optimize_count=10000 ``` Speed measurements from 100 bench runs at depth 13 with profile-build x86-64-avx2: ``` sf_base = 1329051 +/- 2224 (95%) sf_test = 1163344 +/- 2992 (95%) diff = -165706 +/- 4913 (95%) speedup = -12.46807% +/- 0.370% (95%) ``` Training data can be found at: https://robotmoon.com/nnue-training-data/ Local elo at 25k nodes per move (vs. L1-2048 nn-1ee1aba5ed4c.nnue) ep959 : 16.2 +/- 2.3 Failed 10+0.1 STC: https://tests.stockfishchess.org/tests/view/6501beee2cd016da89abab21 LLR: -2.92 (-2.94,2.94) <0.00,2.00> Total: 13184 W: 3285 L: 3535 D: 6364 Ptnml(0-2): 85, 1662, 3334, 1440, 71 Failed 180+1.8 VLTC: https://tests.stockfishchess.org/tests/view/6505cf9a72620bc881ea908e LLR: -2.94 (-2.94,2.94) <0.00,2.00> Total: 64248 W: 16224 L: 16374 D: 31650 Ptnml(0-2): 26, 6788, 18640, 6650, 20 Passed 60+0.6 th 8 VLTC SMP (STC bounds): https://tests.stockfishchess.org/tests/view/65084a4618698b74c2e541dc LLR: 2.95 (-2.94,2.94) <0.00,2.00> Total: 90630 W: 23372 L: 23033 D: 44225 Ptnml(0-2): 13, 8490, 27968, 8833, 11 Passed 60+0.6 th 8 VLTC SMP: https://tests.stockfishchess.org/tests/view/6501d45d2cd016da89abacdb LLR: 2.95 (-2.94,2.94) <0.50,2.50> Total: 137804 W: 35764 L: 35276 D: 66764 Ptnml(0-2): 31, 13006, 42326, 13522, 17 bench 1246812
linrock
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this pull request
Sep 21, 2023
Creating this net involved: - a 6-stage training process from scratch - permuting L1 weights with official-stockfish/nnue-pytorch#254 A strong epoch after each training stage was chosen for the next. The 6 stages were: ``` 1. 400 epochs, lambda 1.0, default LR and gamma UHOx2-wIsRight-multinet-dfrc-n5000 (135G) nodes5000pv2_UHO.binpack data_pv-2_diff-100_nodes-5000.binpack wrongIsRight_nodes5000pv2.binpack multinet_pv-2_diff-100_nodes-5000.binpack dfrc_n5000.binpack 2. 800 epochs, end-lambda 0.75, LR 4.375e-4, gamma 0.995, skip 12 LeelaFarseer-T78juntoaugT79marT80dec.binpack (141G) T60T70wIsRightFarseerT60T74T75T76.binpack test78-junjulaug2022-16tb7p.no-db.min.binpack test79-mar2022-16tb7p.no-db.min.binpack test80-dec2022-16tb7p.no-db.min.binpack 3. 800 epochs, end-lambda 0.725, LR 4.375e-4, gamma 0.995, skip 20 leela93-v1-dfrc99-v2-T78juntosepT80jan-v6dd-T78janfebT79aprT80aprmay.min.binpack leela93-filt-v1.min.binpack dfrc99-16tb7p-filt-v2.min.binpack test78-juntosep2022-16tb7p-filter-v6-dd.min-mar2023.min.binpack test80-jan2023-3of3-16tb7p-filter-v6-dd.min-mar2023.binpack test78-janfeb2022-16tb7p.min.binpack test79-apr2022-16tb7p.min.binpack test80-apr2022-16tb7p.min.binpack test80-may2022-16tb7p.min.binpack 4. 800 epochs, end-lambda 0.7, LR 4.375e-4, gamma 0.995, skip 24 leela96-dfrc99-v2-T78juntosepT79mayT80junsepnovjan-v6dd-T80mar23-v6-T60novdecT77decT78aprmayT79aprT80may23.min.binpack leela96-filt-v2.min.binpack dfrc99-16tb7p-filt-v2.min.binpack test78-juntosep2022-16tb7p-filter-v6-dd.min.binpack test79-may2022-16tb7p.filter-v6-dd.min.binpack test80-jun2022-16tb7p.filter-v6-dd.min.binpack test80-sep2022-16tb7p.filter-v6-dd.min.binpack test80-nov2022-16tb7p.filter-v6-dd.min.binpack test80-jan2023-3of3-16tb7p-filter-v6-dd.min-mar2023.binpack test80-mar2023-2tb7p.v6-sk16.min.binpack test60-novdec2021-16tb7p.min.binpack test77-dec2021-16tb7p.min.binpack test78-aprmay2022-16tb7p.min.binpack test79-apr2022-16tb7p.min.binpack test80-may2023-2tb7p.min.binpack 5. 960 epochs, end-lambda 0.7, LR 4.375e-4, gamma 0.995, skip 28 Increased max-epoch to 960 near the end of the first 800 epochs 5af11540bbfe dataset: official-stockfish#4635 6. 1000 epochs, end-lambda 0.7, LR 4.375e-4, gamma 0.995, skip 28 Increased max-epoch to 1000 near the end of the first 800 epochs 1ee1aba5ed dataset: official-stockfish#4782 ``` L1 weights permuted with: ```bash python3 serialize.py $nnue $nnue_permuted \ --features=HalfKAv2_hm \ --ft_optimize \ --ft_optimize_data=/data/fishpack32.binpack \ --ft_optimize_count=10000 ``` Speed measurements from 100 bench runs at depth 13 with profile-build x86-64-avx2: ``` sf_base = 1329051 +/- 2224 (95%) sf_test = 1163344 +/- 2992 (95%) diff = -165706 +/- 4913 (95%) speedup = -12.46807% +/- 0.370% (95%) ``` Training data can be found at: https://robotmoon.com/nnue-training-data/ Local elo at 25k nodes per move (vs. L1-2048 nn-1ee1aba5ed4c.nnue) ep959 : 16.2 +/- 2.3 Failed 10+0.1 STC: https://tests.stockfishchess.org/tests/view/6501beee2cd016da89abab21 LLR: -2.92 (-2.94,2.94) <0.00,2.00> Total: 13184 W: 3285 L: 3535 D: 6364 Ptnml(0-2): 85, 1662, 3334, 1440, 71 Failed 180+1.8 VLTC: https://tests.stockfishchess.org/tests/view/6505cf9a72620bc881ea908e LLR: -2.94 (-2.94,2.94) <0.00,2.00> Total: 64248 W: 16224 L: 16374 D: 31650 Ptnml(0-2): 26, 6788, 18640, 6650, 20 Passed 60+0.6 th 8 VLTC SMP (STC bounds): https://tests.stockfishchess.org/tests/view/65084a4618698b74c2e541dc LLR: 2.95 (-2.94,2.94) <0.00,2.00> Total: 90630 W: 23372 L: 23033 D: 44225 Ptnml(0-2): 13, 8490, 27968, 8833, 11 Passed 60+0.6 th 8 VLTC SMP: https://tests.stockfishchess.org/tests/view/6501d45d2cd016da89abacdb LLR: 2.95 (-2.94,2.94) <0.50,2.50> Total: 137804 W: 35764 L: 35276 D: 66764 Ptnml(0-2): 31, 13006, 42326, 13522, 17 bench 1246812
linrock
added a commit
to linrock/Stockfish
that referenced
this pull request
Sep 21, 2023
Creating this net involved: - a 6-stage training process from scratch - permuting L1 weights with official-stockfish/nnue-pytorch#254 A strong epoch after each training stage was chosen for the next. The 6 stages were: ``` 1. 400 epochs, lambda 1.0, default LR and gamma UHOx2-wIsRight-multinet-dfrc-n5000 (135G) nodes5000pv2_UHO.binpack data_pv-2_diff-100_nodes-5000.binpack wrongIsRight_nodes5000pv2.binpack multinet_pv-2_diff-100_nodes-5000.binpack dfrc_n5000.binpack 2. 800 epochs, end-lambda 0.75, LR 4.375e-4, gamma 0.995, skip 12 LeelaFarseer-T78juntoaugT79marT80dec.binpack (141G) T60T70wIsRightFarseerT60T74T75T76.binpack test78-junjulaug2022-16tb7p.no-db.min.binpack test79-mar2022-16tb7p.no-db.min.binpack test80-dec2022-16tb7p.no-db.min.binpack 3. 800 epochs, end-lambda 0.725, LR 4.375e-4, gamma 0.995, skip 20 leela93-v1-dfrc99-v2-T78juntosepT80jan-v6dd-T78janfebT79aprT80aprmay.min.binpack leela93-filt-v1.min.binpack dfrc99-16tb7p-filt-v2.min.binpack test78-juntosep2022-16tb7p-filter-v6-dd.min-mar2023.binpack test80-jan2023-3of3-16tb7p-filter-v6-dd.min-mar2023.binpack test78-janfeb2022-16tb7p.min.binpack test79-apr2022-16tb7p.min.binpack test80-apr2022-16tb7p.min.binpack test80-may2022-16tb7p.min.binpack 4. 800 epochs, end-lambda 0.7, LR 4.375e-4, gamma 0.995, skip 24 leela96-dfrc99-v2-T78juntosepT79mayT80junsepnovjan-v6dd-T80mar23-v6-T60novdecT77decT78aprmayT79aprT80may23.min.binpack leela96-filt-v2.min.binpack dfrc99-16tb7p-filt-v2.min.binpack test78-juntosep2022-16tb7p-filter-v6-dd.min-mar2023.binpack test79-may2022-16tb7p.filter-v6-dd.min.binpack test80-jun2022-16tb7p.filter-v6-dd.min.binpack test80-sep2022-16tb7p.filter-v6-dd.min.binpack test80-nov2022-16tb7p.filter-v6-dd.min.binpack test80-jan2023-3of3-16tb7p-filter-v6-dd.min-mar2023.binpack test80-mar2023-2tb7p.v6-sk16.min.binpack test60-novdec2021-16tb7p.min.binpack test77-dec2021-16tb7p.min.binpack test78-aprmay2022-16tb7p.min.binpack test79-apr2022-16tb7p.min.binpack test80-may2023-2tb7p.min.binpack 5. 960 epochs, end-lambda 0.7, LR 4.375e-4, gamma 0.995, skip 28 Increased max-epoch to 960 near the end of the first 800 epochs 5af11540bbfe dataset: official-stockfish#4635 6. 1000 epochs, end-lambda 0.7, LR 4.375e-4, gamma 0.995, skip 28 Increased max-epoch to 1000 near the end of the first 800 epochs 1ee1aba5ed dataset: official-stockfish#4782 ``` L1 weights permuted with: ```bash python3 serialize.py $nnue $nnue_permuted \ --features=HalfKAv2_hm \ --ft_optimize \ --ft_optimize_data=/data/fishpack32.binpack \ --ft_optimize_count=10000 ``` Speed measurements from 100 bench runs at depth 13 with profile-build x86-64-avx2: ``` sf_base = 1329051 +/- 2224 (95%) sf_test = 1163344 +/- 2992 (95%) diff = -165706 +/- 4913 (95%) speedup = -12.46807% +/- 0.370% (95%) ``` Training data can be found at: https://robotmoon.com/nnue-training-data/ Local elo at 25k nodes per move (vs. L1-2048 nn-1ee1aba5ed4c.nnue) ep959 : 16.2 +/- 2.3 Failed 10+0.1 STC: https://tests.stockfishchess.org/tests/view/6501beee2cd016da89abab21 LLR: -2.92 (-2.94,2.94) <0.00,2.00> Total: 13184 W: 3285 L: 3535 D: 6364 Ptnml(0-2): 85, 1662, 3334, 1440, 71 Failed 180+1.8 VLTC: https://tests.stockfishchess.org/tests/view/6505cf9a72620bc881ea908e LLR: -2.94 (-2.94,2.94) <0.00,2.00> Total: 64248 W: 16224 L: 16374 D: 31650 Ptnml(0-2): 26, 6788, 18640, 6650, 20 Passed 60+0.6 th 8 VLTC SMP (STC bounds): https://tests.stockfishchess.org/tests/view/65084a4618698b74c2e541dc LLR: 2.95 (-2.94,2.94) <0.00,2.00> Total: 90630 W: 23372 L: 23033 D: 44225 Ptnml(0-2): 13, 8490, 27968, 8833, 11 Passed 60+0.6 th 8 VLTC SMP: https://tests.stockfishchess.org/tests/view/6501d45d2cd016da89abacdb LLR: 2.95 (-2.94,2.94) <0.50,2.50> Total: 137804 W: 35764 L: 35276 D: 66764 Ptnml(0-2): 31, 13006, 42326, 13522, 17 bench 1246812
linrock
added a commit
to linrock/Stockfish
that referenced
this pull request
Sep 21, 2023
Creating this net involved: - a 6-stage training process from scratch - permuting L1 weights with official-stockfish/nnue-pytorch#254 The datasets used in stages 1-5 were fully minimized. A strong epoch after each training stage was chosen for the next. The 6 stages were: ``` 1. 400 epochs, lambda 1.0, default LR and gamma UHOx2-wIsRight-multinet-dfrc-n5000 (135G) nodes5000pv2_UHO.binpack data_pv-2_diff-100_nodes-5000.binpack wrongIsRight_nodes5000pv2.binpack multinet_pv-2_diff-100_nodes-5000.binpack dfrc_n5000.binpack 2. 800 epochs, end-lambda 0.75, LR 4.375e-4, gamma 0.995, skip 12 LeelaFarseer-T78juntoaugT79marT80dec.binpack (141G) T60T70wIsRightFarseerT60T74T75T76.binpack test78-junjulaug2022-16tb7p.no-db.min.binpack test79-mar2022-16tb7p.no-db.min.binpack test80-dec2022-16tb7p.no-db.min.binpack 3. 800 epochs, end-lambda 0.725, LR 4.375e-4, gamma 0.995, skip 20 leela93-v1-dfrc99-v2-T78juntosepT80jan-v6dd-T78janfebT79aprT80aprmay.min.binpack leela93-filt-v1.min.binpack dfrc99-16tb7p-filt-v2.min.binpack test78-juntosep2022-16tb7p-filter-v6-dd.min-mar2023.binpack test80-jan2023-3of3-16tb7p-filter-v6-dd.min-mar2023.binpack test78-janfeb2022-16tb7p.min.binpack test79-apr2022-16tb7p.min.binpack test80-apr2022-16tb7p.min.binpack test80-may2022-16tb7p.min.binpack 4. 800 epochs, end-lambda 0.7, LR 4.375e-4, gamma 0.995, skip 24 leela96-dfrc99-v2-T78juntosepT79mayT80junsepnovjan-v6dd-T80mar23-v6-T60novdecT77decT78aprmayT79aprT80may23.min.binpack leela96-filt-v2.min.binpack dfrc99-16tb7p-filt-v2.min.binpack test78-juntosep2022-16tb7p-filter-v6-dd.min-mar2023.binpack test79-may2022-16tb7p.filter-v6-dd.min.binpack test80-jun2022-16tb7p.filter-v6-dd.min.binpack test80-sep2022-16tb7p.filter-v6-dd.min.binpack test80-nov2022-16tb7p.filter-v6-dd.min.binpack test80-jan2023-3of3-16tb7p-filter-v6-dd.min-mar2023.binpack test80-mar2023-2tb7p.v6-sk16.min.binpack test60-novdec2021-16tb7p.min.binpack test77-dec2021-16tb7p.min.binpack test78-aprmay2022-16tb7p.min.binpack test79-apr2022-16tb7p.min.binpack test80-may2023-2tb7p.min.binpack 5. 960 epochs, end-lambda 0.7, LR 4.375e-4, gamma 0.995, skip 28 Increased max-epoch to 960 near the end of the first 800 epochs 5af11540bbfe dataset: official-stockfish#4635 6. 1000 epochs, end-lambda 0.7, LR 4.375e-4, gamma 0.995, skip 28 Increased max-epoch to 1000 near the end of the first 800 epochs 1ee1aba5ed dataset: official-stockfish#4782 ``` L1 weights permuted with: ```bash python3 serialize.py $nnue $nnue_permuted \ --features=HalfKAv2_hm \ --ft_optimize \ --ft_optimize_data=/data/fishpack32.binpack \ --ft_optimize_count=10000 ``` Speed measurements from 100 bench runs at depth 13 with profile-build x86-64-avx2: ``` sf_base = 1329051 +/- 2224 (95%) sf_test = 1163344 +/- 2992 (95%) diff = -165706 +/- 4913 (95%) speedup = -12.46807% +/- 0.370% (95%) ``` Training data can be found at: https://robotmoon.com/nnue-training-data/ Local elo at 25k nodes per move (vs. L1-2048 nn-1ee1aba5ed4c.nnue) ep959 : 16.2 +/- 2.3 Failed 10+0.1 STC: https://tests.stockfishchess.org/tests/view/6501beee2cd016da89abab21 LLR: -2.92 (-2.94,2.94) <0.00,2.00> Total: 13184 W: 3285 L: 3535 D: 6364 Ptnml(0-2): 85, 1662, 3334, 1440, 71 Failed 180+1.8 VLTC: https://tests.stockfishchess.org/tests/view/6505cf9a72620bc881ea908e LLR: -2.94 (-2.94,2.94) <0.00,2.00> Total: 64248 W: 16224 L: 16374 D: 31650 Ptnml(0-2): 26, 6788, 18640, 6650, 20 Passed 60+0.6 th 8 VLTC SMP (STC bounds): https://tests.stockfishchess.org/tests/view/65084a4618698b74c2e541dc LLR: 2.95 (-2.94,2.94) <0.00,2.00> Total: 90630 W: 23372 L: 23033 D: 44225 Ptnml(0-2): 13, 8490, 27968, 8833, 11 Passed 60+0.6 th 8 VLTC SMP: https://tests.stockfishchess.org/tests/view/6501d45d2cd016da89abacdb LLR: 2.95 (-2.94,2.94) <0.50,2.50> Total: 137804 W: 35764 L: 35276 D: 66764 Ptnml(0-2): 31, 13006, 42326, 13522, 17 bench 1246812
linrock
added a commit
to linrock/Stockfish
that referenced
this pull request
Sep 21, 2023
Creating this net involved: - a 6-stage training process from scratch. The datasets used in stages 1-5 were fully minimized. - permuting L1 weights with official-stockfish/nnue-pytorch#254 A strong epoch after each training stage was chosen for the next. The 6 stages were: ``` 1. 400 epochs, lambda 1.0, default LR and gamma UHOx2-wIsRight-multinet-dfrc-n5000 (135G) nodes5000pv2_UHO.binpack data_pv-2_diff-100_nodes-5000.binpack wrongIsRight_nodes5000pv2.binpack multinet_pv-2_diff-100_nodes-5000.binpack dfrc_n5000.binpack 2. 800 epochs, end-lambda 0.75, LR 4.375e-4, gamma 0.995, skip 12 LeelaFarseer-T78juntoaugT79marT80dec.binpack (141G) T60T70wIsRightFarseerT60T74T75T76.binpack test78-junjulaug2022-16tb7p.no-db.min.binpack test79-mar2022-16tb7p.no-db.min.binpack test80-dec2022-16tb7p.no-db.min.binpack 3. 800 epochs, end-lambda 0.725, LR 4.375e-4, gamma 0.995, skip 20 leela93-v1-dfrc99-v2-T78juntosepT80jan-v6dd-T78janfebT79aprT80aprmay.min.binpack leela93-filt-v1.min.binpack dfrc99-16tb7p-filt-v2.min.binpack test78-juntosep2022-16tb7p-filter-v6-dd.min-mar2023.binpack test80-jan2023-3of3-16tb7p-filter-v6-dd.min-mar2023.binpack test78-janfeb2022-16tb7p.min.binpack test79-apr2022-16tb7p.min.binpack test80-apr2022-16tb7p.min.binpack test80-may2022-16tb7p.min.binpack 4. 800 epochs, end-lambda 0.7, LR 4.375e-4, gamma 0.995, skip 24 leela96-dfrc99-v2-T78juntosepT79mayT80junsepnovjan-v6dd-T80mar23-v6-T60novdecT77decT78aprmayT79aprT80may23.min.binpack leela96-filt-v2.min.binpack dfrc99-16tb7p-filt-v2.min.binpack test78-juntosep2022-16tb7p-filter-v6-dd.min-mar2023.binpack test79-may2022-16tb7p.filter-v6-dd.min.binpack test80-jun2022-16tb7p.filter-v6-dd.min.binpack test80-sep2022-16tb7p.filter-v6-dd.min.binpack test80-nov2022-16tb7p.filter-v6-dd.min.binpack test80-jan2023-3of3-16tb7p-filter-v6-dd.min-mar2023.binpack test80-mar2023-2tb7p.v6-sk16.min.binpack test60-novdec2021-16tb7p.min.binpack test77-dec2021-16tb7p.min.binpack test78-aprmay2022-16tb7p.min.binpack test79-apr2022-16tb7p.min.binpack test80-may2023-2tb7p.min.binpack 5. 960 epochs, end-lambda 0.7, LR 4.375e-4, gamma 0.995, skip 28 Increased max-epoch to 960 near the end of the first 800 epochs 5af11540bbfe dataset: official-stockfish#4635 6. 1000 epochs, end-lambda 0.7, LR 4.375e-4, gamma 0.995, skip 28 Increased max-epoch to 1000 near the end of the first 800 epochs 1ee1aba5ed dataset: official-stockfish#4782 ``` L1 weights permuted with: ```bash python3 serialize.py $nnue $nnue_permuted \ --features=HalfKAv2_hm \ --ft_optimize \ --ft_optimize_data=/data/fishpack32.binpack \ --ft_optimize_count=10000 ``` Speed measurements from 100 bench runs at depth 13 with profile-build x86-64-avx2: ``` sf_base = 1329051 +/- 2224 (95%) sf_test = 1163344 +/- 2992 (95%) diff = -165706 +/- 4913 (95%) speedup = -12.46807% +/- 0.370% (95%) ``` Training data can be found at: https://robotmoon.com/nnue-training-data/ Local elo at 25k nodes per move (vs. L1-2048 nn-1ee1aba5ed4c.nnue) ep959 : 16.2 +/- 2.3 Failed 10+0.1 STC: https://tests.stockfishchess.org/tests/view/6501beee2cd016da89abab21 LLR: -2.92 (-2.94,2.94) <0.00,2.00> Total: 13184 W: 3285 L: 3535 D: 6364 Ptnml(0-2): 85, 1662, 3334, 1440, 71 Failed 180+1.8 VLTC: https://tests.stockfishchess.org/tests/view/6505cf9a72620bc881ea908e LLR: -2.94 (-2.94,2.94) <0.00,2.00> Total: 64248 W: 16224 L: 16374 D: 31650 Ptnml(0-2): 26, 6788, 18640, 6650, 20 Passed 60+0.6 th 8 VLTC SMP (STC bounds): https://tests.stockfishchess.org/tests/view/65084a4618698b74c2e541dc LLR: 2.95 (-2.94,2.94) <0.00,2.00> Total: 90630 W: 23372 L: 23033 D: 44225 Ptnml(0-2): 13, 8490, 27968, 8833, 11 Passed 60+0.6 th 8 VLTC SMP: https://tests.stockfishchess.org/tests/view/6501d45d2cd016da89abacdb LLR: 2.95 (-2.94,2.94) <0.50,2.50> Total: 137804 W: 35764 L: 35276 D: 66764 Ptnml(0-2): 31, 13006, 42326, 13522, 17 bench 1246812
vondele
pushed a commit
to vondele/Stockfish
that referenced
this pull request
Sep 22, 2023
Creating this net involved: - a 6-stage training process from scratch. The datasets used in stages 1-5 were fully minimized. - permuting L1 weights with official-stockfish/nnue-pytorch#254 A strong epoch after each training stage was chosen for the next. The 6 stages were: ``` 1. 400 epochs, lambda 1.0, default LR and gamma UHOx2-wIsRight-multinet-dfrc-n5000 (135G) nodes5000pv2_UHO.binpack data_pv-2_diff-100_nodes-5000.binpack wrongIsRight_nodes5000pv2.binpack multinet_pv-2_diff-100_nodes-5000.binpack dfrc_n5000.binpack 2. 800 epochs, end-lambda 0.75, LR 4.375e-4, gamma 0.995, skip 12 LeelaFarseer-T78juntoaugT79marT80dec.binpack (141G) T60T70wIsRightFarseerT60T74T75T76.binpack test78-junjulaug2022-16tb7p.no-db.min.binpack test79-mar2022-16tb7p.no-db.min.binpack test80-dec2022-16tb7p.no-db.min.binpack 3. 800 epochs, end-lambda 0.725, LR 4.375e-4, gamma 0.995, skip 20 leela93-v1-dfrc99-v2-T78juntosepT80jan-v6dd-T78janfebT79aprT80aprmay.min.binpack leela93-filt-v1.min.binpack dfrc99-16tb7p-filt-v2.min.binpack test78-juntosep2022-16tb7p-filter-v6-dd.min-mar2023.binpack test80-jan2023-3of3-16tb7p-filter-v6-dd.min-mar2023.binpack test78-janfeb2022-16tb7p.min.binpack test79-apr2022-16tb7p.min.binpack test80-apr2022-16tb7p.min.binpack test80-may2022-16tb7p.min.binpack 4. 800 epochs, end-lambda 0.7, LR 4.375e-4, gamma 0.995, skip 24 leela96-dfrc99-v2-T78juntosepT79mayT80junsepnovjan-v6dd-T80mar23-v6-T60novdecT77decT78aprmayT79aprT80may23.min.binpack leela96-filt-v2.min.binpack dfrc99-16tb7p-filt-v2.min.binpack test78-juntosep2022-16tb7p-filter-v6-dd.min-mar2023.binpack test79-may2022-16tb7p.filter-v6-dd.min.binpack test80-jun2022-16tb7p.filter-v6-dd.min.binpack test80-sep2022-16tb7p.filter-v6-dd.min.binpack test80-nov2022-16tb7p.filter-v6-dd.min.binpack test80-jan2023-3of3-16tb7p-filter-v6-dd.min-mar2023.binpack test80-mar2023-2tb7p.v6-sk16.min.binpack test60-novdec2021-16tb7p.min.binpack test77-dec2021-16tb7p.min.binpack test78-aprmay2022-16tb7p.min.binpack test79-apr2022-16tb7p.min.binpack test80-may2023-2tb7p.min.binpack 5. 960 epochs, end-lambda 0.7, LR 4.375e-4, gamma 0.995, skip 28 Increased max-epoch to 960 near the end of the first 800 epochs 5af11540bbfe dataset: official-stockfish#4635 6. 1000 epochs, end-lambda 0.7, LR 4.375e-4, gamma 0.995, skip 28 Increased max-epoch to 1000 near the end of the first 800 epochs 1ee1aba5ed dataset: official-stockfish#4782 ``` L1 weights permuted with: ```bash python3 serialize.py $nnue $nnue_permuted \ --features=HalfKAv2_hm \ --ft_optimize \ --ft_optimize_data=/data/fishpack32.binpack \ --ft_optimize_count=10000 ``` Speed measurements from 100 bench runs at depth 13 with profile-build x86-64-avx2: ``` sf_base = 1329051 +/- 2224 (95%) sf_test = 1163344 +/- 2992 (95%) diff = -165706 +/- 4913 (95%) speedup = -12.46807% +/- 0.370% (95%) ``` Training data can be found at: https://robotmoon.com/nnue-training-data/ Local elo at 25k nodes per move (vs. L1-2048 nn-1ee1aba5ed4c.nnue) ep959 : 16.2 +/- 2.3 Failed 10+0.1 STC: https://tests.stockfishchess.org/tests/view/6501beee2cd016da89abab21 LLR: -2.92 (-2.94,2.94) <0.00,2.00> Total: 13184 W: 3285 L: 3535 D: 6364 Ptnml(0-2): 85, 1662, 3334, 1440, 71 Failed 180+1.8 VLTC: https://tests.stockfishchess.org/tests/view/6505cf9a72620bc881ea908e LLR: -2.94 (-2.94,2.94) <0.00,2.00> Total: 64248 W: 16224 L: 16374 D: 31650 Ptnml(0-2): 26, 6788, 18640, 6650, 20 Passed 60+0.6 th 8 VLTC SMP (STC bounds): https://tests.stockfishchess.org/tests/view/65084a4618698b74c2e541dc LLR: 2.95 (-2.94,2.94) <0.00,2.00> Total: 90630 W: 23372 L: 23033 D: 44225 Ptnml(0-2): 13, 8490, 27968, 8833, 11 Passed 60+0.6 th 8 VLTC SMP: https://tests.stockfishchess.org/tests/view/6501d45d2cd016da89abacdb LLR: 2.95 (-2.94,2.94) <0.50,2.50> Total: 137804 W: 35764 L: 35276 D: 66764 Ptnml(0-2): 31, 13006, 42326, 13522, 17 closes official-stockfish#4795 bench 1246812
linrock
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Mar 5, 2024
Created by retraining the previous main net `nn-b1a57edbea57.nnue` with: - some of the same options as before: - ranger21, more WDL skipping, 15% more loss when Q is too high - removal of the huge 514G pre-interleaved binpack - removal of SF-generated dfrc data (dfrc99-16tb7p-filt-v2.min.binpack) - interleaving many binpacks at training time - training with some bestmove capture positions where SEE < 0 - increased usage of torch.compile to speed up training by up to 40% ```yaml experiment-name: 2560--S10-dfrc0-to-dec2023-skip-more-wdl-15p-more-loss-high-q-see-ge0-sk28 nnue-pytorch-branch: linrock/nnue-pytorch/r21-more-wdl-skip-15p-more-loss-high-q-skip-see-ge0-torch-compile-more start-from-engine-test-net: True early-fen-skipping: 28 training-dataset: # similar, not the exact same as: # official-stockfish#4635 - /data/S5-5af/leela96.v2.min.binpack - /data/S5-5af/test60-2021-11-12-novdec-12tb7p.v6-dd.min.binpack - /data/S5-5af/test77-2021-12-dec-16tb7p.v6-dd.min.binpack - /data/S5-5af/test78-2022-01-to-05-jantomay-16tb7p.v6-dd.min.binpack - /data/S5-5af/test78-2022-06-to-09-juntosep-16tb7p.v6-dd.min.binpack - /data/S5-5af/test79-2022-04-apr-16tb7p.v6-dd.min.binpack - /data/S5-5af/test79-2022-05-may-16tb7p.v6-dd.min.binpack - /data/S5-5af/test80-2022-06-jun-16tb7p.v6-dd.min.unmin.binpack - /data/S5-5af/test80-2022-07-jul-16tb7p.v6-dd.min.binpack - /data/S5-5af/test80-2022-08-aug-16tb7p.v6-dd.min.binpack - /data/S5-5af/test80-2022-09-sep-16tb7p.v6-dd.min.unmin.binpack - /data/S5-5af/test80-2022-10-oct-16tb7p.v6-dd.min.binpack - /data/S5-5af/test80-2022-11-nov-16tb7p.v6-dd.min.binpack - /data/S5-5af/test80-2023-01-jan-16tb7p.v6-sk20.min.binpack - /data/S5-5af/test80-2023-02-feb-16tb7p.v6-dd.min.binpack - /data/S5-5af/test80-2023-03-mar-2tb7p.min.unmin.binpack - /data/S5-5af/test80-2023-04-apr-2tb7p.binpack - /data/S5-5af/test80-2023-05-may-2tb7p.min.dd.binpack # official-stockfish#4782 - /data/S6-1ee1aba5ed/test80-2023-06-jun-2tb7p.binpack - /data/S6-1ee1aba5ed/test80-2023-07-jul-2tb7p.min.binpack # official-stockfish#4972 - /data/S8-baff1edbea57/test80-2023-08-aug-2tb7p.v6.min.binpack - /data/S8-baff1edbea57/test80-2023-09-sep-2tb7p.binpack - /data/S8-baff1edbea57/test80-2023-10-oct-2tb7p.binpack # official-stockfish#5056 - /data/S9-b1a57edbea57/test80-2023-11-nov-2tb7p.binpack - /data/S9-b1a57edbea57/test80-2023-12-dec-2tb7p.binpack num-epochs: 800 lr: 4.375e-4 gamma: 0.995 start-lambda: 1.0 end-lambda: 0.7 ``` This particular net was reached at epoch 759. Use of more torch.compile decorators in nnue-pytorch model.py than in the previous main net training run sped up training by up to 40% on Tesla gpus when using recent pytorch compiled with cuda 12: https://github.com/linrock/nnue-tools/blob/7fb9831/Dockerfile Skipping positions with bestmove captures where static exchange evaluation is >= 0 is based on the implementation from Sopel's NNUE training & experimentation log: https://docs.google.com/document/d/1gTlrr02qSNKiXNZ_SuO4-RjK4MXBiFlLE6jvNqqMkAY Experiment 293 - only skip captures with see>=0 Positions with bestmove captures where score == 0 are always skipped for compatibility with minimized binpacks, since the original minimizer sets scores to 0 for slight improvements in compression. The trainer branch used was: https://github.com/linrock/nnue-pytorch/tree/r21-more-wdl-skip-15p-more-loss-high-q-skip-see-ge0-torch-compile-more Binpacks were renamed to be sorted chronologically by default when sorted by name. The binpack data are otherwise the same as binpacks with similar names in the prior naming convention. Training data can be found at: https://robotmoon.com/nnue-training-data/ Passed STC: https://tests.stockfishchess.org/tests/view/65e3ddd1f2ef6c733362ae5c LLR: 2.92 (-2.94,2.94) <0.00,2.00> Total: 149792 W: 39153 L: 38661 D: 71978 Ptnml(0-2): 675, 17586, 37905, 18032, 698 Passed LTC: https://tests.stockfishchess.org/tests/view/65e4d91c416ecd92c162a69b LLR: 2.94 (-2.94,2.94) <0.50,2.50> Total: 64416 W: 16517 L: 16135 D: 31764 Ptnml(0-2): 38, 7218, 17313, 7602, 37 Bench: 1536373
linrock
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Mar 5, 2024
Created by retraining the previous main net `nn-b1a57edbea57.nnue` with: - some of the same options as before: - ranger21, more WDL skipping, 15% more loss when Q is too high - removal of the huge 514G pre-interleaved binpack - removal of SF-generated dfrc data (dfrc99-16tb7p-filt-v2.min.binpack) - interleaving many binpacks at training time - training with some bestmove capture positions where SEE < 0 - increased usage of torch.compile to speed up training by up to 40% ```yaml experiment-name: 2560--S10-dfrc0-to-dec2023-skip-more-wdl-15p-more-loss-high-q-see-ge0-sk28 nnue-pytorch-branch: linrock/nnue-pytorch/r21-more-wdl-skip-15p-more-loss-high-q-skip-see-ge0-torch-compile-more start-from-engine-test-net: True early-fen-skipping: 28 training-dataset: # similar, not the exact same as: # official-stockfish#4635 - /data/S5-5af/leela96.v2.min.binpack - /data/S5-5af/test60-2021-11-12-novdec-12tb7p.v6-dd.min.binpack - /data/S5-5af/test77-2021-12-dec-16tb7p.v6-dd.min.binpack - /data/S5-5af/test78-2022-01-to-05-jantomay-16tb7p.v6-dd.min.binpack - /data/S5-5af/test78-2022-06-to-09-juntosep-16tb7p.v6-dd.min.binpack - /data/S5-5af/test79-2022-04-apr-16tb7p.v6-dd.min.binpack - /data/S5-5af/test79-2022-05-may-16tb7p.v6-dd.min.binpack - /data/S5-5af/test80-2022-06-jun-16tb7p.v6-dd.min.unmin.binpack - /data/S5-5af/test80-2022-07-jul-16tb7p.v6-dd.min.binpack - /data/S5-5af/test80-2022-08-aug-16tb7p.v6-dd.min.binpack - /data/S5-5af/test80-2022-09-sep-16tb7p.v6-dd.min.unmin.binpack - /data/S5-5af/test80-2022-10-oct-16tb7p.v6-dd.min.binpack - /data/S5-5af/test80-2022-11-nov-16tb7p.v6-dd.min.binpack - /data/S5-5af/test80-2023-01-jan-16tb7p.v6-sk20.min.binpack - /data/S5-5af/test80-2023-02-feb-16tb7p.v6-dd.min.binpack - /data/S5-5af/test80-2023-03-mar-2tb7p.min.unmin.binpack - /data/S5-5af/test80-2023-04-apr-2tb7p.binpack - /data/S5-5af/test80-2023-05-may-2tb7p.min.dd.binpack # official-stockfish#4782 - /data/S6-1ee1aba5ed/test80-2023-06-jun-2tb7p.binpack - /data/S6-1ee1aba5ed/test80-2023-07-jul-2tb7p.min.binpack # official-stockfish#4972 - /data/S8-baff1edbea57/test80-2023-08-aug-2tb7p.v6.min.binpack - /data/S8-baff1edbea57/test80-2023-09-sep-2tb7p.binpack - /data/S8-baff1edbea57/test80-2023-10-oct-2tb7p.binpack # official-stockfish#5056 - /data/S9-b1a57edbea57/test80-2023-11-nov-2tb7p.binpack - /data/S9-b1a57edbea57/test80-2023-12-dec-2tb7p.binpack num-epochs: 800 lr: 4.375e-4 gamma: 0.995 start-lambda: 1.0 end-lambda: 0.7 ``` This particular net was reached at epoch 759. Use of more torch.compile decorators in nnue-pytorch model.py than in the previous main net training run sped up training by up to 40% on Tesla gpus when using recent pytorch compiled with cuda 12: https://github.com/linrock/nnue-tools/blob/7fb9831/Dockerfile Skipping positions with bestmove captures where static exchange evaluation is >= 0 is based on the implementation from Sopel's NNUE training & experimentation log: https://docs.google.com/document/d/1gTlrr02qSNKiXNZ_SuO4-RjK4MXBiFlLE6jvNqqMkAY Experiment 293 - only skip captures with see>=0 Positions with bestmove captures where score == 0 are always skipped for compatibility with minimized binpacks, since the original minimizer sets scores to 0 for slight improvements in compression. The trainer branch used was: https://github.com/linrock/nnue-pytorch/tree/r21-more-wdl-skip-15p-more-loss-high-q-skip-see-ge0-torch-compile-more Binpacks were renamed to be sorted chronologically by default when sorted by name. The binpack data are otherwise the same as binpacks with similar names in the prior naming convention. Training data can be found at: https://robotmoon.com/nnue-training-data/ Passed STC: https://tests.stockfishchess.org/tests/view/65e3ddd1f2ef6c733362ae5c LLR: 2.92 (-2.94,2.94) <0.00,2.00> Total: 149792 W: 39153 L: 38661 D: 71978 Ptnml(0-2): 675, 17586, 37905, 18032, 698 Passed LTC: https://tests.stockfishchess.org/tests/view/65e4d91c416ecd92c162a69b LLR: 2.94 (-2.94,2.94) <0.50,2.50> Total: 64416 W: 16517 L: 16135 D: 31764 Ptnml(0-2): 38, 7218, 17313, 7602, 37 Bench: 1373183
Disservin
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Mar 7, 2024
Created by retraining the previous main net `nn-b1a57edbea57.nnue` with: - some of the same options as before: - ranger21, more WDL skipping, 15% more loss when Q is too high - removal of the huge 514G pre-interleaved binpack - removal of SF-generated dfrc data (dfrc99-16tb7p-filt-v2.min.binpack) - interleaving many binpacks at training time - training with some bestmove capture positions where SEE < 0 - increased usage of torch.compile to speed up training by up to 40% ```yaml experiment-name: 2560--S10-dfrc0-to-dec2023-skip-more-wdl-15p-more-loss-high-q-see-ge0-sk28 nnue-pytorch-branch: linrock/nnue-pytorch/r21-more-wdl-skip-15p-more-loss-high-q-skip-see-ge0-torch-compile-more start-from-engine-test-net: True early-fen-skipping: 28 training-dataset: # similar, not the exact same as: # #4635 - /data/S5-5af/leela96.v2.min.binpack - /data/S5-5af/test60-2021-11-12-novdec-12tb7p.v6-dd.min.binpack - /data/S5-5af/test77-2021-12-dec-16tb7p.v6-dd.min.binpack - /data/S5-5af/test78-2022-01-to-05-jantomay-16tb7p.v6-dd.min.binpack - /data/S5-5af/test78-2022-06-to-09-juntosep-16tb7p.v6-dd.min.binpack - /data/S5-5af/test79-2022-04-apr-16tb7p.v6-dd.min.binpack - /data/S5-5af/test79-2022-05-may-16tb7p.v6-dd.min.binpack - /data/S5-5af/test80-2022-06-jun-16tb7p.v6-dd.min.unmin.binpack - /data/S5-5af/test80-2022-07-jul-16tb7p.v6-dd.min.binpack - /data/S5-5af/test80-2022-08-aug-16tb7p.v6-dd.min.binpack - /data/S5-5af/test80-2022-09-sep-16tb7p.v6-dd.min.unmin.binpack - /data/S5-5af/test80-2022-10-oct-16tb7p.v6-dd.min.binpack - /data/S5-5af/test80-2022-11-nov-16tb7p.v6-dd.min.binpack - /data/S5-5af/test80-2023-01-jan-16tb7p.v6-sk20.min.binpack - /data/S5-5af/test80-2023-02-feb-16tb7p.v6-dd.min.binpack - /data/S5-5af/test80-2023-03-mar-2tb7p.min.unmin.binpack - /data/S5-5af/test80-2023-04-apr-2tb7p.binpack - /data/S5-5af/test80-2023-05-may-2tb7p.min.dd.binpack # #4782 - /data/S6-1ee1aba5ed/test80-2023-06-jun-2tb7p.binpack - /data/S6-1ee1aba5ed/test80-2023-07-jul-2tb7p.min.binpack # #4972 - /data/S8-baff1edbea57/test80-2023-08-aug-2tb7p.v6.min.binpack - /data/S8-baff1edbea57/test80-2023-09-sep-2tb7p.binpack - /data/S8-baff1edbea57/test80-2023-10-oct-2tb7p.binpack # #5056 - /data/S9-b1a57edbea57/test80-2023-11-nov-2tb7p.binpack - /data/S9-b1a57edbea57/test80-2023-12-dec-2tb7p.binpack num-epochs: 800 lr: 4.375e-4 gamma: 0.995 start-lambda: 1.0 end-lambda: 0.7 ``` This particular net was reached at epoch 759. Use of more torch.compile decorators in nnue-pytorch model.py than in the previous main net training run sped up training by up to 40% on Tesla gpus when using recent pytorch compiled with cuda 12: https://github.com/linrock/nnue-tools/blob/7fb9831/Dockerfile Skipping positions with bestmove captures where static exchange evaluation is >= 0 is based on the implementation from Sopel's NNUE training & experimentation log: https://docs.google.com/document/d/1gTlrr02qSNKiXNZ_SuO4-RjK4MXBiFlLE6jvNqqMkAY Experiment 293 - only skip captures with see>=0 Positions with bestmove captures where score == 0 are always skipped for compatibility with minimized binpacks, since the original minimizer sets scores to 0 for slight improvements in compression. The trainer branch used was: https://github.com/linrock/nnue-pytorch/tree/r21-more-wdl-skip-15p-more-loss-high-q-skip-see-ge0-torch-compile-more Binpacks were renamed to be sorted chronologically by default when sorted by name. The binpack data are otherwise the same as binpacks with similar names in the prior naming convention. Training data can be found at: https://robotmoon.com/nnue-training-data/ Passed STC: https://tests.stockfishchess.org/tests/view/65e3ddd1f2ef6c733362ae5c LLR: 2.92 (-2.94,2.94) <0.00,2.00> Total: 149792 W: 39153 L: 38661 D: 71978 Ptnml(0-2): 675, 17586, 37905, 18032, 698 Passed LTC: https://tests.stockfishchess.org/tests/view/65e4d91c416ecd92c162a69b LLR: 2.94 (-2.94,2.94) <0.50,2.50> Total: 64416 W: 16517 L: 16135 D: 31764 Ptnml(0-2): 38, 7218, 17313, 7602, 37 closes #5090 Bench: 1373183
bftjoe
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Mar 8, 2024
commit 632f1c21cd271e7c4c242fdafa328a55ec63b9cb
Author: Robert Nurnberg @ elitebook <robert.nurnberg@gmx.de>
Date: Thu Mar 7 22:01:40 2024 +0100
Fix wrong constant usage in go mate
Fixes an oversight in official-stockfish/Stockfish#5094
In theory, master could stop search when run with `go mate 247` and return a TB loss (not a mate score). Also fixes the spelling of opponenWorsening.
closes official-stockfish/Stockfish#5096
No functional change
commit 0f01a516d2ddd475bbe3bccab176dbbccb879053
Author: Muzhen Gaming <61100393+XInTheDark@users.noreply.github.com>
Date: Mon Mar 4 18:48:02 2024 +0800
VLTC time management tune
Result of 35k games of SPSA tuning at 180+1.8. Tuning attempt can be
found here:
https://tests.stockfishchess.org/tests/view/65e40599f2ef6c733362b03b
Passed VLTC 180+1.8:
https://tests.stockfishchess.org/tests/view/65e5a6f5416ecd92c162b5d4
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 31950 W: 8225 L: 7949 D: 15776
Ptnml(0-2): 3, 3195, 9309, 3459, 9
Passed VLTC 240+2.4:
https://tests.stockfishchess.org/tests/view/65e714de0ec64f0526c3d1f1
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 65108 W: 16558 L: 16202 D: 32348
Ptnml(0-2): 7, 6366, 19449, 6728, 4
closes official-stockfish/Stockfish#5095
Bench: 1714391
commit 748791f80dbc29793e473e3e9eda83ffa0afcfaa
Author: Shahin M. Shahin <41402573+peregrineshahin@users.noreply.github.com>
Date: Wed Mar 6 20:56:55 2024 +0300
Fix `go mate x` in multithreading
Fixes two issues with master for go mate x:
- when running go mate x in losing positions, master always goes to the
maximal depth, arguably against what the UCI protocol demands
- when running go mate x in winning positions with multiple
threads, master may return non-mate scores from the search (this issue
is present in stockfish since at least sf16) The issues are fixed by
(a) also checking if score is mate -x and by (b) only letting
mainthread stop the search for go mate x commands, and by not looking
for a best thread but using mainthread as per the default. Related:
niklasf/python-chess#1070
More diagnostics can be found here peregrineshahin#6 (comment)
closes official-stockfish/Stockfish#5094
No functional change
Co-Authored-By: Robert Nürnberg <28635489+robertnurnberg@users.noreply.github.com>
commit 6136d094c5f46456964889754ae2d6098834b14f
Author: Michael Chaly <Vizvezdenec@gmail.com>
Date: Thu Mar 7 11:57:18 2024 +0300
Introduce double extensions for PV nodes
Our double/triple extensions were allowed only for non-pv nodes. This
patch allows them to be done for PV nodes, with some stricter
conditions.
Passed STC:
https://tests.stockfishchess.org/tests/view/65d657ec1d8e83c78bfddab8
LLR: 2.95 (-2.94,2.94) <0.00,2.00>
Total: 339424 W: 88097 L: 87318 D: 164009
Ptnml(0-2): 1573, 39935, 85729, 41090, 1385
Passed LTC:
https://tests.stockfishchess.org/tests/view/65dd63824b19edc854ebc433
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 459564 W: 115812 L: 114614 D: 229138
Ptnml(0-2): 248, 51441, 125173, 52705, 215
closes official-stockfish/Stockfish#5093
Bench: 1714391
commit 1db969e6200afe4f023469a56aa5edf755d92bbb
Author: rn5f107s2 <clemens.lerchl@gmail.com>
Date: Thu Feb 15 23:01:02 2024 +0100
Reduce futility_margin if opponents last move was bad
This reduces the futiltiy_margin if our opponents last move was bad by
around ~1/3 when not improving and ~1/2.7 when improving, the idea being
to retroactively futility prune moves that were played, but turned out
to be bad. A bad move is being defined as their staticEval before their
move being lower as our staticEval now is. If the depth is 2 and we are
improving the opponent worsening flag is not set, in order to not risk
having a too low futility_margin, due to the fact that when these
conditions are met the futility_margin already drops quite low.
Passed STC:
https://tests.stockfishchess.org/tests/live_elo/65e3977bf2ef6c733362aae3
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 122432 W: 31884 L: 31436 D: 59112
Ptnml(0-2): 467, 14404, 31035, 14834, 476
Passed LTC:
https://tests.stockfishchess.org/tests/live_elo/65e47f40f2ef6c733362b6d2
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 421692 W: 106572 L: 105452 D: 209668
Ptnml(0-2): 216, 47217, 114865, 48327, 221
closes official-stockfish/Stockfish#5092
Bench: 1565939
commit bd579ab5d1a931a09a62f2ed33b5149ada7bc65f
Author: Linmiao Xu <linmiao.xu@gmail.com>
Date: Fri Mar 1 10:34:03 2024 -0800
Update default main net to nn-1ceb1ade0001.nnue
Created by retraining the previous main net `nn-b1a57edbea57.nnue` with:
- some of the same options as before:
- ranger21, more WDL skipping, 15% more loss when Q is too high
- removal of the huge 514G pre-interleaved binpack
- removal of SF-generated dfrc data (dfrc99-16tb7p-filt-v2.min.binpack)
- interleaving many binpacks at training time
- training with some bestmove capture positions where SEE < 0
- increased usage of torch.compile to speed up training by up to 40%
```yaml
experiment-name: 2560--S10-dfrc0-to-dec2023-skip-more-wdl-15p-more-loss-high-q-see-ge0-sk28
nnue-pytorch-branch: linrock/nnue-pytorch/r21-more-wdl-skip-15p-more-loss-high-q-skip-see-ge0-torch-compile-more
start-from-engine-test-net: True
early-fen-skipping: 28
training-dataset:
# similar, not the exact same as:
# official-stockfish/Stockfish#4635
- /data/S5-5af/leela96.v2.min.binpack
- /data/S5-5af/test60-2021-11-12-novdec-12tb7p.v6-dd.min.binpack
- /data/S5-5af/test77-2021-12-dec-16tb7p.v6-dd.min.binpack
- /data/S5-5af/test78-2022-01-to-05-jantomay-16tb7p.v6-dd.min.binpack
- /data/S5-5af/test78-2022-06-to-09-juntosep-16tb7p.v6-dd.min.binpack
- /data/S5-5af/test79-2022-04-apr-16tb7p.v6-dd.min.binpack
- /data/S5-5af/test79-2022-05-may-16tb7p.v6-dd.min.binpack
- /data/S5-5af/test80-2022-06-jun-16tb7p.v6-dd.min.unmin.binpack
- /data/S5-5af/test80-2022-07-jul-16tb7p.v6-dd.min.binpack
- /data/S5-5af/test80-2022-08-aug-16tb7p.v6-dd.min.binpack
- /data/S5-5af/test80-2022-09-sep-16tb7p.v6-dd.min.unmin.binpack
- /data/S5-5af/test80-2022-10-oct-16tb7p.v6-dd.min.binpack
- /data/S5-5af/test80-2022-11-nov-16tb7p.v6-dd.min.binpack
- /data/S5-5af/test80-2023-01-jan-16tb7p.v6-sk20.min.binpack
- /data/S5-5af/test80-2023-02-feb-16tb7p.v6-dd.min.binpack
- /data/S5-5af/test80-2023-03-mar-2tb7p.min.unmin.binpack
- /data/S5-5af/test80-2023-04-apr-2tb7p.binpack
- /data/S5-5af/test80-2023-05-may-2tb7p.min.dd.binpack
# official-stockfish/Stockfish#4782
- /data/S6-1ee1aba5ed/test80-2023-06-jun-2tb7p.binpack
- /data/S6-1ee1aba5ed/test80-2023-07-jul-2tb7p.min.binpack
# official-stockfish/Stockfish#4972
- /data/S8-baff1edbea57/test80-2023-08-aug-2tb7p.v6.min.binpack
- /data/S8-baff1edbea57/test80-2023-09-sep-2tb7p.binpack
- /data/S8-baff1edbea57/test80-2023-10-oct-2tb7p.binpack
# official-stockfish/Stockfish#5056
- /data/S9-b1a57edbea57/test80-2023-11-nov-2tb7p.binpack
- /data/S9-b1a57edbea57/test80-2023-12-dec-2tb7p.binpack
num-epochs: 800
lr: 4.375e-4
gamma: 0.995
start-lambda: 1.0
end-lambda: 0.7
```
This particular net was reached at epoch 759. Use of more torch.compile decorators
in nnue-pytorch model.py than in the previous main net training run sped up training
by up to 40% on Tesla gpus when using recent pytorch compiled with cuda 12:
https://github.com/linrock/nnue-tools/blob/7fb9831/Dockerfile
Skipping positions with bestmove captures where static exchange evaluation is >= 0
is based on the implementation from Sopel's NNUE training & experimentation log:
https://docs.google.com/document/d/1gTlrr02qSNKiXNZ_SuO4-RjK4MXBiFlLE6jvNqqMkAY
Experiment 293 - only skip captures with see>=0
Positions with bestmove captures where score == 0 are always skipped for
compatibility with minimized binpacks, since the original minimizer sets
scores to 0 for slight improvements in compression.
The trainer branch used was:
https://github.com/linrock/nnue-pytorch/tree/r21-more-wdl-skip-15p-more-loss-high-q-skip-see-ge0-torch-compile-more
Binpacks were renamed to be sorted chronologically by default when sorted by name.
The binpack data are otherwise the same as binpacks with similar names in the prior
naming convention.
Training data can be found at:
https://robotmoon.com/nnue-training-data/
Passed STC:
https://tests.stockfishchess.org/tests/view/65e3ddd1f2ef6c733362ae5c
LLR: 2.92 (-2.94,2.94) <0.00,2.00>
Total: 149792 W: 39153 L: 38661 D: 71978
Ptnml(0-2): 675, 17586, 37905, 18032, 698
Passed LTC:
https://tests.stockfishchess.org/tests/view/65e4d91c416ecd92c162a69b
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 64416 W: 16517 L: 16135 D: 31764
Ptnml(0-2): 38, 7218, 17313, 7602, 37
closes official-stockfish/Stockfish#5090
Bench: 1373183
commit a96b0d46093c67707e4e75e7aa5aa057b7c131a2
Author: FauziAkram <fauzi.dabat@hotmail.com>
Date: Mon Mar 4 16:13:36 2024 +0300
Update elo estimates
Tests used to change the elo worth of some functions:
https://tests.stockfishchess.org/tests/view/65c3f69dc865510db0283eef
https://tests.stockfishchess.org/tests/view/65c3f935c865510db0283f2a
https://tests.stockfishchess.org/tests/view/65d1489f1d8e83c78bfd7dbf
https://tests.stockfishchess.org/tests/view/65ce9d361d8e83c78bfd4951
https://tests.stockfishchess.org/tests/view/65cfcd901d8e83c78bfd6184
closes official-stockfish/Stockfish#5089
No functional change
commit a615efb19f5dfb4b205ed3a9dd8525e54e8777cc
Author: FauziAkram <fauzi.dabat@hotmail.com>
Date: Mon Feb 26 18:08:22 2024 +0300
Simplify Time Management
Instead of having a formula for using extra time with larger increments.
Simply set it to 1 when the increment is lower than 0.5s and to 1.1 when
the increment is higher.
The values can later on be further improved.
Passed STC:
https://tests.stockfishchess.org/tests/view/65d25d3c1d8e83c78bfd9293
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 27488 W: 7077 L: 6848 D: 13563
Ptnml(0-2): 96, 3041, 7267, 3218, 122
Passed LTC:
https://tests.stockfishchess.org/tests/view/65d2a72c1d8e83c78bfd97fa
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 137568 W: 34612 L: 34512 D: 68444
Ptnml(0-2): 60, 14672, 39221, 14770, 61
Passed VLTC:
https://tests.stockfishchess.org/tests/view/65d7d7d39b2da0226a5a205b
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 139650 W: 35229 L: 35134 D: 69287
Ptnml(0-2): 33, 14227, 41218, 14306, 41
Passed also the TCEC TC style suggested by vondele:
https://tests.stockfishchess.org/tests/view/65e4ca73416ecd92c162a57d
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 134150 W: 34278 L: 34163 D: 65709
Ptnml(0-2): 561, 15727, 34444, 15722, 621
closes official-stockfish/Stockfish#5076
Bench: 1553115
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Created by retraining the sparsified master net (nn-cd2ff4716c34.nnue) on a 100% minified dataset including Leela transformers data from T80 may2023.
Weights permuted with the exact methods and code in: #4620
LEB128 compression done with the new serialize.py param in: official-stockfish/nnue-pytorch#251
Initially trained with max epoch 800. Around epoch 780, training was paused and max epoch raised to 960.
python3 easy_train.py \ --experiment-name L1-1536-sparse-master-retrain \ --training-dataset /data/leela96-dfrc99-v2-T60novdecT77decT78jantosepT79aprmayT80juntonovjan-v6dd-T80febtomay2023.min.binpack \ --early-fen-skipping 27 \ --start-from-engine-test-net True \ --max_epoch 960 \ --lr 4.375e-4 \ --gamma 0.995 \ --start-lambda 1.0 \ --end-lambda 0.7 \ --tui False \ --seed $RANDOM \ --gpus 0For preparing the training dataset (interleaved size 328G):
Minified binpacks and Leela T80 training data from 2023 available at:
https://robotmoon.com/nnue-training-data/
Local elo at 25k nodes per move:
nn-epoch879.nnue : 3.9 +/- 5.7
Passed STC:
https://tests.stockfishchess.org/tests/view/64928c1bdc7002ce609c7690
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 72000 W: 19242 L: 18889 D: 33869
Ptnml(0-2): 182, 7787, 19716, 8126, 189
Passed LTC:
https://tests.stockfishchess.org/tests/view/64930a37dc7002ce609c82e3
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 54552 W: 14978 L: 14647 D: 24927
Ptnml(0-2): 23, 5123, 16650, 5460, 20
bench 2593605