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Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
 Linmiao XuandJoost VandeVondele
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a49b3ba7ed |
Update default net to nn-5af11540bbfe.nnue
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: https://github.com/official-stockfish/Stockfish/pull/4620 LEB128 compression done with the new serialize.py param in: https://github.com/glinscott/nnue-pytorch/pull/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 https://github.com/official-stockfish/Stockfish/pull/4635 bench 2593605 |
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Linmiao XuandStéphane Nicolet
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932f5a2d65 |
Update default net to nn-ea57bea57e32.nnue
Created by retraining an earlier epoch (ep659) of the experiment that led to the first SFNNv6 net: - First retrained on the nn-0dd1cebea573 dataset - Then retrained with skip 20 on a smaller dataset containing unfiltered Leela data - And then retrained again with skip 27 on the nn-0dd1cebea573 dataset The equivalent 7-step training sequence from scratch that led here was: 1. max-epoch 400, lambda 1.0, constant LR 9.75e-4, T79T77-filter-v6-dd.min.binpack ep379 chosen for retraining in step2 2. max-epoch 800, end-lambda 0.75, T60T70wIsRightFarseerT60T74T75T76.binpack ep679 chosen for retraining in step3 3. max-epoch 800, end-lambda 0.75, skip 28, nn-e1fb1ade4432 dataset ep799 chosen for retraining in step4 4. max-epoch 800, end-lambda 0.7, skip 28, nn-e1fb1ade4432 dataset ep759 became nn-8d69132723e2.nnue (first SFNNv6 net) ep659 chosen for retraining in step5 5. max-epoch 800, end-lambda 0.7, skip 28, nn-0dd1cebea573 dataset ep759 chosen for retraining in step6 6. max-epoch 800, end-lambda 0.7, skip 20, leela-dfrc-v2-T77decT78janfebT79aprT80apr.binpack ep639 chosen for retraining in step7 7. max-epoch 800, end-lambda 0.7, skip 27, nn-0dd1cebea573 dataset ep619 became nn-ea57bea57e32.nnue For the last retraining (step7): python3 easy_train.py --experiment-name L1-1536-Re6-masterShuffled-ep639-sk27-Re5-leela-dfrc-v2-T77toT80small-Re4-masterShuffled-ep659-Re3-sameAs-Re2-leela96-dfrc99-16t-v2-T60novdecT80juntonovjanfebT79aprmayT78jantosepT77dec-v6dd-Re1-LeelaFarseer-new-T77T79 \ --training-dataset /data/leela96-dfrc99-T60novdec-v2-T80juntonovjanfebT79aprmayT78jantosepT77dec-v6dd-T80apr.binpack \ --nnue-pytorch-branch linrock/nnue-pytorch/misc-fixes-L1-1536 \ --early-fen-skipping 27 \ --start-lambda 1.0 \ --end-lambda 0.7 \ --max_epoch 800 \ --start-from-engine-test-net False \ --start-from-model /data/L1-1536-Re5-leela-dfrc-v2-T77toT80small-epoch639.nnue \ --lr 4.375e-4 \ --gamma 0.995 \ --tui False \ --seed $RANDOM \ --gpus "0," For preparing the step6 leela-dfrc-v2-T77decT78janfebT79aprT80apr.binpack dataset: python3 interleave_binpacks.py \ leela96-filt-v2.binpack \ dfrc99-16tb7p-eval-filt-v2.binpack \ test77-dec2021-16tb7p.no-db.min-mar2023.binpack \ test78-janfeb2022-16tb7p.no-db.min-mar2023.binpack \ test79-apr2022-16tb7p-filter-v6-dd.binpack \ test80-apr2022-16tb7p.no-db.min-mar2023.binpack \ /data/leela-dfrc-v2-T77decT78janfebT79aprT80apr.binpack The unfiltered Leela data used for the step6 dataset can be found at: https://robotmoon.com/nnue-training-data Local elo at 25k nodes per move: nn-epoch619.nnue : 2.3 +/- 1.9 Passed STC: https://tests.stockfishchess.org/tests/view/6480d43c6e6ce8d9fc6d7cc8 LLR: 2.94 (-2.94,2.94) <0.00,2.00> Total: 40992 W: 11017 L: 10706 D: 19269 Ptnml(0-2): 113, 4400, 11170, 4689, 124 Passed LTC: https://tests.stockfishchess.org/tests/view/648119ac6e6ce8d9fc6d8208 LLR: 2.94 (-2.94,2.94) <0.50,2.50> Total: 129174 W: 35059 L: 34579 D: 59536 Ptnml(0-2): 66, 12548, 38868, 13050, 55 closes https://github.com/official-stockfish/Stockfish/pull/4611 bench: 2370027 |
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Linmiao XuandJoost VandeVondele
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54ad986768 |
Remove optimism multiplier in nnue eval calculation
The same formula had passed SPRT against an earlier version of master. Passed non-regression STC vs. |
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Linmiao XuandJoost VandeVondele
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373359b44d |
Update default net to nn-0dd1cebea573.nnue
Created by retraining an earlier epoch of the experiment leading to the first SFNNv6 net on a more-randomized version of the nn-e1fb1ade4432.nnue dataset mixed with unfiltered T80 apr2023 data. Trained using early-fen-skipping 28 and max-epoch 960. The trainer settings and epochs used in the 5-step training sequence leading here were: 1. train from scratch for 400 epochs, lambda 1.0, constant LR 9.75e-4, T79T77-filter-v6-dd.min.binpack 2. retrain ep379, max-epoch 800, end-lambda 0.75, T60T70wIsRightFarseerT60T74T75T76.binpack 3. retrain ep679, max-epoch 800, end-lambda 0.75, skip 28, nn-e1fb1ade4432 dataset 4. retrain ep799, max-epoch 800, end-lambda 0.7, skip 28, nn-e1fb1ade4432 dataset 5. retrain ep439, max-epoch 960, end-lambda 0.7, skip 28, shuffled nn-e1fb1ade4432 + T80 apr2023 This net was epoch 559 of the final (step 5) retraining: ```bash python3 easy_train.py \ --experiment-name L1-1536-Re4-leela96-dfrc99-T60novdec-v2-T80juntonovjanfebT79aprmayT78jantosepT77dec-v6dd-T80apr-shuffled-sk28 \ --training-dataset /data/leela96-dfrc99-T60novdec-v2-T80juntonovjanfebT79aprmayT78jantosepT77dec-v6dd-T80apr.binpack \ --nnue-pytorch-branch linrock/nnue-pytorch/misc-fixes-L1-1536 \ --early-fen-skipping 28 \ --start-lambda 1.0 \ --end-lambda 0.7 \ --max_epoch 960 \ --start-from-engine-test-net False \ --start-from-model /data/L1-1536-Re3-nn-epoch439.nnue \ --engine-test-branch linrock/Stockfish/L1-1536 \ --lr 4.375e-4 \ --gamma 0.995 \ --tui False \ --seed $RANDOM \ --gpus "0," ``` During data preparation, most binpacks were unminimized by removing positions with score 32002 (`VALUE_NONE`). This makes the tradeoff of increasing dataset filesize on disk to increase the randomness of positions in interleaved datasets. The code used for unminimizing is at: https://github.com/linrock/Stockfish/tree/tools-unminify For preparing the dataset used in this experiment: ```bash python3 interleave_binpacks.py \ leela96-filt-v2.binpack \ dfrc99-16tb7p-eval-filt-v2.binpack \ filt-v6-dd-min/test60-novdec2021-12tb7p-filter-v6-dd.min-mar2023.unmin.binpack \ filt-v6-dd-min/test80-aug2022-16tb7p-filter-v6-dd.min-mar2023.unmin.binpack \ filt-v6-dd-min/test80-sep2022-16tb7p-filter-v6-dd.min-mar2023.unmin.binpack \ filt-v6-dd-min/test80-jun2022-16tb7p-filter-v6-dd.min-mar2023.unmin.binpack \ filt-v6-dd/test80-jul2022-16tb7p-filter-v6-dd.binpack \ filt-v6-dd/test80-oct2022-16tb7p-filter-v6-dd.binpack \ filt-v6-dd/test80-nov2022-16tb7p-filter-v6-dd.binpack \ filt-v6-dd-min/test80-jan2023-3of3-16tb7p-filter-v6-dd.min-mar2023.unmin.binpack \ filt-v6-dd-min/test80-feb2023-16tb7p-filter-v6-dd.min-mar2023.unmin.binpack \ filt-v6-dd/test79-apr2022-16tb7p-filter-v6-dd.binpack \ filt-v6-dd/test79-may2022-16tb7p-filter-v6-dd.binpack \ filt-v6-dd-min/test78-jantomay2022-16tb7p-filter-v6-dd.min-mar2023.unmin.binpack \ filt-v6-dd/test78-juntosep2022-16tb7p-filter-v6-dd.binpack \ filt-v6-dd/test77-dec2021-16tb7p-filter-v6-dd.binpack \ test80-apr2023-2tb7p.binpack \ /data/leela96-dfrc99-T60novdec-v2-T80juntonovjanfebT79aprmayT78jantosepT77dec-v6dd-T80apr.binpack ``` T80 apr2023 data was converted using lc0-rescorer with ~2tb of tablebases and can be found at: https://robotmoon.com/nnue-training-data/ Local elo at 25k nodes per move vs. nn-e1fb1ade4432.nnue (L1 size 1024): nn-epoch559.nnue : 25.7 +/- 1.6 Passed STC: https://tests.stockfishchess.org/tests/view/647cd3b87cf638f0f53f9cbb LLR: 2.95 (-2.94,2.94) <0.00,2.00> Total: 59200 W: 16000 L: 15660 D: 27540 Ptnml(0-2): 159, 6488, 15996, 6768, 189 Passed LTC: https://tests.stockfishchess.org/tests/view/647d58de726f6b400e4085d8 LLR: 2.95 (-2.94,2.94) <0.50,2.50> Total: 58800 W: 16002 L: 15657 D: 27141 Ptnml(0-2): 44, 5607, 17748, 5962, 39 closes https://github.com/official-stockfish/Stockfish/pull/4606 bench 2141197 |
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Linmiao XuandJoost VandeVondele
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ced0311890 |
Remove static eval threshold for extensions when giving check
Passed non-regression STC: https://tests.stockfishchess.org/tests/view/647685d54a36543c4c9f4f2a LLR: 2.93 (-2.94,2.94) <-1.75,0.25> Total: 114688 W: 30701 L: 30571 D: 53416 Ptnml(0-2): 336, 12708, 31136, 12818, 346 Passed non-regression LTC: https://tests.stockfishchess.org/tests/view/64774b02b81f005b572de770 LLR: 2.94 (-2.94,2.94) <-1.75,0.25> Total: 107310 W: 28920 L: 28796 D: 49594 Ptnml(0-2): 33, 10427, 32621, 10531, 43 closes https://github.com/official-stockfish/Stockfish/pull/4599 bench 2597974 |
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Linmiao XuandJoost VandeVondele
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6cf8d938c5 |
Simplify blending nnue complexity with optimism
Passed non-regression STC: https://tests.stockfishchess.org/tests/view/6478a26d54dd118e1d98f21c LLR: 2.94 (-2.94,2.94) <-1.75,0.25> Total: 241248 W: 64058 L: 64063 D: 113127 Ptnml(0-2): 644, 26679, 65960, 26720, 621 Passed non-regression LTC: https://tests.stockfishchess.org/tests/view/647b464854dd118e1d9928b2 LLR: 2.96 (-2.94,2.94) <-1.75,0.25> Total: 24336 W: 6658 L: 6451 D: 11227 Ptnml(0-2): 8, 2316, 7312, 2525, 7 closes https://github.com/official-stockfish/Stockfish/pull/4602 bench 2425813 |
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Linmiao XuandJoost VandeVondele
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07bd8adcbc |
Simplify nnue eval complexity calculation
Remove a multiplier when blending nnue complexity with semi-classical complexity. Passed non-regression STC: https://tests.stockfishchess.org/tests/view/6473a71dd29264e4cfa75839 LLR: 2.95 (-2.94,2.94) <-1.75,0.25> Total: 124768 W: 33180 L: 33060 D: 58528 Ptnml(0-2): 314, 13797, 34030, 13941, 302 Passed non-regression LTC: https://tests.stockfishchess.org/tests/view/6474af3dd29264e4cfa768f4 LLR: 2.96 (-2.94,2.94) <-1.75,0.25> Total: 108180 W: 29008 L: 28884 D: 50288 Ptnml(0-2): 29, 10420, 33075, 10530, 36 closes https://github.com/official-stockfish/Stockfish/pull/4592 bench 2316827 |
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Linmiao XuandJoost VandeVondele
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c1fff71650 |
Update NNUE architecture to SFNNv6 with larger L1 size of 1536
Created by training a new net from scratch with L1 size increased from 1024 to 1536. Thanks to Vizvezdenec for the idea of exploring larger net sizes after recent training data improvements. A new net was first trained with lambda 1.0 and constant LR 8.75e-4. Then a strong net from a later epoch in the training run was chosen for retraining with start-lambda 1.0 and initial LR 4.375e-4 decaying with gamma 0.995. Retraining was performed a total of 3 times, for this 4-step process: 1. 400 epochs, lambda 1.0 on filtered T77+T79 v6 deduplicated data 2. 800 epochs, end-lambda 0.75 on T60T70wIsRightFarseerT60T74T75T76.binpack 3. 800 epochs, end-lambda 0.75 and early-fen-skipping 28 on the master dataset 4. 800 epochs, end-lambda 0.7 and early-fen-skipping 28 on the master dataset In the training sequence that reached the new nn-8d69132723e2.nnue net, the epochs used for the 3x retraining runs were: 1. epoch 379 trained on T77T79-filter-v6-dd.min.binpack 2. epoch 679 trained on T60T70wIsRightFarseerT60T74T75T76.binpack 3. epoch 799 trained on the master dataset For training from scratch: python3 easy_train.py \ --experiment-name new-L1-1536-T77T79-filter-v6dd \ --training-dataset /data/T77T79-filter-v6-dd.min.binpack \ --max_epoch 400 \ --lambda 1.0 \ --start-from-engine-test-net False \ --engine-test-branch linrock/Stockfish/L1-1536 \ --nnue-pytorch-branch linrock/Stockfish/misc-fixes-L1-1536 \ --tui False \ --gpus "0," \ --seed $RANDOM Retraining commands were similar to each other. For the 3rd retraining run: python3 easy_train.py \ --experiment-name L1-1536-T77T79-v6dd-Re1-LeelaFarseer-Re2-masterDataset-Re3-sameData \ --training-dataset /data/leela96-dfrc99-v2-T60novdecT80juntonovjanfebT79aprmayT78jantosepT77dec-v6dd.binpack \ --early-fen-skipping 28 \ --max_epoch 800 \ --start-lambda 1.0 \ --end-lambda 0.7 \ --lr 4.375e-4 \ --gamma 0.995 \ --start-from-engine-test-net False \ --start-from-model /data/L1-1536-T77T79-v6dd-Re1-LeelaFarseer-Re2-masterDataset-nn-epoch799.nnue \ --engine-test-branch linrock/Stockfish/L1-1536 \ --nnue-pytorch-branch linrock/nnue-pytorch/misc-fixes-L1-1536 \ --tui False \ --gpus "0," \ --seed $RANDOM The T77+T79 data used is a subset of the master dataset available at: https://robotmoon.com/nnue-training-data/ T60T70wIsRightFarseerT60T74T75T76.binpack is available at: https://drive.google.com/drive/folders/1S9-ZiQa_3ApmjBtl2e8SyHxj4zG4V8gG Local elo at 25k nodes per move vs. nn-e1fb1ade4432.nnue (L1 size 1024): nn-epoch759.nnue : 26.9 +/- 1.6 Failed STC https://tests.stockfishchess.org/tests/view/64742485d29264e4cfa75f97 LLR: -2.94 (-2.94,2.94) <0.00,2.00> Total: 13728 W: 3588 L: 3829 D: 6311 Ptnml(0-2): 71, 1661, 3610, 1482, 40 Failing LTC https://tests.stockfishchess.org/tests/view/64752d7c4a36543c4c9f3618 LLR: -1.91 (-2.94,2.94) <0.50,2.50> Total: 35424 W: 9522 L: 9603 D: 16299 Ptnml(0-2): 24, 3579, 10585, 3502, 22 Passed VLTC 180+1.8 https://tests.stockfishchess.org/tests/view/64752df04a36543c4c9f3638 LLR: 2.95 (-2.94,2.94) <0.50,2.50> Total: 47616 W: 13174 L: 12863 D: 21579 Ptnml(0-2): 13, 4261, 14952, 4566, 16 Passed VLTC SMP 60+0.6 th 8 https://tests.stockfishchess.org/tests/view/647446ced29264e4cfa761e5 LLR: 2.94 (-2.94,2.94) <0.50,2.50> Total: 19942 W: 5694 L: 5451 D: 8797 Ptnml(0-2): 6, 1504, 6707, 1749, 5 closes https://github.com/official-stockfish/Stockfish/pull/4593 bench 2222567 |
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Linmiao XuandJoost VandeVondele
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21d6b69f7c |
Update 7 eval and optimism params
Params found using spsa at 30+0.3 with this tuning config: ``` // evaluate.cpp int nnueOptScaleBase = 1001; int nnueComplexityMult = 406; int nnueComplexityOptOffset = 424; int evalOptComplexityOffset = 272; int evalOptScaleOffset = 748; TUNE(SetRange(801, 1201), nnueOptScaleBase); TUNE(SetRange(306, 506), nnueComplexityMult); TUNE(SetRange(324, 524), nnueComplexityOptOffset); TUNE(SetRange(172, 372), evalOptComplexityOffset); TUNE(SetRange(648, 848), evalOptScaleOffset); // search.cpp int searchOptBase = 120; int searchOptDenom = 161; TUNE(SetRange(20, 220), searchOptBase); TUNE(SetRange(111, 211), searchOptDenom); ``` Passed STC: https://tests.stockfishchess.org/tests/view/644dda8accf5e93df5e50cbe LLR: 2.93 (-2.94,2.94) <0.00,2.00> Total: 136800 W: 36682 L: 36237 D: 63881 Ptnml(0-2): 353, 14910, 37492, 15229, 416 Passed LTC: https://tests.stockfishchess.org/tests/view/644eaedb3f31c3bbe4a3d345 LLR: 2.94 (-2.94,2.94) <0.50,2.50> Total: 64548 W: 17624 L: 17272 D: 29652 Ptnml(0-2): 33, 6112, 19631, 6466, 32 closes https://github.com/official-stockfish/Stockfish/pull/4550 bench 3670343 |
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Linmiao XuandJoost VandeVondele
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41f50b2c83 |
Update default net to nn-e1fb1ade4432.nnue
Created by retraining nn-dabb1ed23026.nnue with a dataset composed of: * The previous best dataset (nn-1ceb1a57d117.nnue dataset) * Adding de-duplicated T80 data from feb2023 and the last 10 days of jan2023, filtered with v6-dd Initially trained with the same options as the recent master net (nn-1ceb1a57d117.nnue). Around epoch 890, training was manually stopped and max epoch increased to 1000. ``` python3 easy_train.py \ --experiment-name leela96-dfrc99-T60novdec-v2-T80augsep-v6-T80junjuloctnovjanfebT79aprmayT78jantosepT77dec-v6dd \ --training-dataset /data/leela96-dfrc99-T60novdec-v2-T80augsep-v6-T80junjuloctnovjanfebT79aprmayT78jantosepT77dec-v6dd.binpack \ --nnue-pytorch-branch linrock/nnue-pytorch/misc-fixes \ --start-from-engine-test-net True \ --early-fen-skipping 30 \ --start-lambda 1.0 \ --end-lambda 0.7 \ --max_epoch 900 \ --lr 4.375e-4 \ --gamma 0.995 \ --tui False \ --gpus "0," \ --seed $RANDOM ``` The same v6-dd filtering and binpack minimizer was used for preparing the recent nn-1ceb1a57d117.nnue dataset. ``` python3 interleave_binpacks.py \ leela96-filt-v2.binpack \ dfrc99-filt-v2.binpack \ T60-nov2021-12tb7p-eval-filt-v2.binpack \ T60-dec2021-12tb7p-eval-filt-v2.binpack \ filt-v6/test80-aug2022-16tb7p-filter-v6.min-mar2023.binpack \ filt-v6/test80-sep2022-16tb7p-filter-v6.min-mar2023.binpack \ filt-v6-dd/test80-jun2022-16tb7p-filter-v6-dd.min-mar2023.binpack \ filt-v6-dd/test80-jul2022-16tb7p-filter-v6-dd.binpack \ filt-v6-dd/test80-oct2022-16tb7p-filter-v6-dd.binpack \ filt-v6-dd/test80-nov2022-16tb7p-filter-v6-dd.binpack \ filt-v6-dd/test80-jan2022-3of3-16tb7p-filter-v6-dd.min-mar2023.binpack \ filt-v6-dd/test80-feb2023-16tb7p-filter-v6-dd.min-mar2023.binpack \ filt-v6-dd/test79-apr2022-16tb7p-filter-v6-dd.binpack \ filt-v6-dd/test79-may2022-16tb7p-filter-v6-dd.binpack \ filt-v6-dd/test78-jantomay2022-16tb7p-filter-v6-dd.min-mar2023.binpack \ filt-v6-dd/test78-juntosep2022-16tb7p-filter-v6-dd.binpack \ filt-v6-dd/test77-dec2021-16tb7p-filter-v6-dd.binpack \ /data/leela96-dfrc99-T60novdec-v2-T80augsep-v6-T80junjuloctnovjanfebT79aprmayT78jantosepT77dec-v6dd.binpack ``` Links for downloading the training data components can be found at: https://robotmoon.com/nnue-training-data/ Local elo at 25k nodes per move: nn-epoch919.nnue : 2.6 +/- 2.8 Passed STC vs. nn-dabb1ed23026.nnue https://tests.stockfishchess.org/tests/view/644420df94ff3db5625f2af5 LLR: 2.94 (-2.94,2.94) <0.00,2.00> Total: 125960 W: 33898 L: 33464 D: 58598 Ptnml(0-2): 351, 13920, 34021, 14320, 368 Passed LTC vs. nn-1ceb1a57d117.nnue https://tests.stockfishchess.org/tests/view/64469f128d30316529b3dc46 LLR: 2.95 (-2.94,2.94) <0.50,2.50> Total: 24544 W: 6817 L: 6542 D: 11185 Ptnml(0-2): 8, 2252, 7488, 2505, 19 closes https://github.com/official-stockfish/Stockfish/pull/4546 bench 3714847 |
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Linmiao XuandJoost VandeVondele
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c3ce220408 |
Created by retraining the master net with these changes to the dataset:
* Extending v6 filtering to data from T77 dec2021, T79 may2022, and T80 nov2022 * Reducing the number of duplicate positions, prioritizing position scores seen later in time * Using a binpack minimizer to reduce the overall data size Trained the same way as the previous master net, aside from the dataset changes: ``` python3 easy_train.py \ --experiment-name leela96-dfrc99-T60novdec-v2-T80augsep-v6-T80junjuloctnovT79aprmayT78jantosepT77dec-v6dd \ --training-dataset /data/leela96-dfrc99-T60novdec-v2-T80augsep-v6-T80junjuloctnovT79aprmayT78jantosepT77dec-v6dd.binpack \ --nnue-pytorch-branch linrock/nnue-pytorch/misc-fixes \ --start-from-engine-test-net True \ --early-fen-skipping 30 \ --start-lambda 1.0 \ --end-lambda 0.7 \ --max_epoch 900 \ --lr 4.375e-4 \ --gamma 0.995 \ --tui False \ --gpus "0," \ --seed $RANDOM ``` The new v6-dd filtering reduces duplicate positions by iterating over hourly data files within leela test runs, starting with the most recent, then keeping positions the first time they're seen and ignoring positions that are seen again. This ordering was done with the assumption that position scores seen later in time are generally more accurate than scores seen earlier in the test run. Positions are de-duplicated based on piece orientations, the first token in fen strings. The binpack minimizer was run with default settings after first merging monthly data into single binpacks. ``` python3 interleave_binpacks.py \ leela96-filt-v2.binpack \ dfrc99-filt-v2.binpack \ T60-nov2021-12tb7p-eval-filt-v2.binpack \ T60-dec2021-12tb7p-eval-filt-v2.binpack \ filt-v6/test80-aug2022-16tb7p-filter-v6.min-mar2023.binpack \ filt-v6/test80-sep2022-16tb7p-filter-v6.min-mar2023.binpack \ filt-v6-dd/test80-jun2022-16tb7p-filter-v6-dd.min-mar2023.binpack \ filt-v6-dd/test80-jul2022-16tb7p-filter-v6-dd.binpack \ filt-v6-dd/test80-oct2022-16tb7p-filter-v6-dd.binpack \ filt-v6-dd/test80-nov2022-16tb7p-filter-v6-dd.binpack \ filt-v6-dd/test79-apr2022-16tb7p-filter-v6-dd.binpack \ filt-v6-dd/test79-may2022-16tb7p-filter-v6-dd.binpack \ filt-v6-dd/test78-jantomay2022-16tb7p-filter-v6-dd.min-mar2023.binpack \ filt-v6-dd/test78-juntosep2022-16tb7p-filter-v6-dd.binpack \ filt-v6-dd/test77-dec2021-16tb7p-filter-v6-dd.binpack \ /data/leela96-dfrc99-T60novdec-v2-T80augsep-v6-T80junjuloctnovT79aprmayT78jantosepT77dec-v6dd.binpack ``` The code for v6-dd filtering is available along with training data preparation scripts at: https://github.com/linrock/nnue-data Links for downloading the training data components: https://robotmoon.com/nnue-training-data/ The binpack minimizer is from: #4447 Local elo at 25k nodes per move: nn-epoch859.nnue : 1.2 +/- 2.6 Passed STC: https://tests.stockfishchess.org/tests/view/643aad7db08900ff1bc5a832 LLR: 2.93 (-2.94,2.94) <0.00,2.00> Total: 565040 W: 150225 L: 149162 D: 265653 Ptnml(0-2): 1875, 62137, 153229, 63608, 1671 Passed LTC: https://tests.stockfishchess.org/tests/view/643ecf2fa43cf30e719d2042 LLR: 2.94 (-2.94,2.94) <0.50,2.50> Total: 1014840 W: 274645 L: 272456 D: 467739 Ptnml(0-2): 515, 98565, 306970, 100956, 414 closes https://github.com/official-stockfish/Stockfish/pull/4545 bench 3476305 |
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Linmiao XuandJoost VandeVondele
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7bd23d4d04 |
Simplify away nnue scale pawn count multiplier
Removes 2x multipliers in nnue scale calculation along with the pawn count term that was recently reintroduced. Passed non-regression STC: https://tests.stockfishchess.org/tests/view/64305bc720eb941419bdf72e LLR: 2.95 (-2.94,2.94) <-1.75,0.25> Total: 38008 W: 10234 L: 10021 D: 17753 Ptnml(0-2): 96, 4151, 10323, 4312, 122 Passed non-regression LTC: https://tests.stockfishchess.org/tests/view/6430b76a028b029b01ac9bfd LLR: 2.94 (-2.94,2.94) <-1.75,0.25> Total: 91232 W: 24686 L: 24547 D: 41999 Ptnml(0-2): 30, 8721, 27986, 8838, 41 closes https://github.com/official-stockfish/Stockfish/pull/4510 bench 4017320 |
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Linmiao XuandJoost VandeVondele
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37160c4b16 |
Update default net to nn-dabb1ed23026.nnue
Created by retraining the master net with these modifications: * New filtering methods for existing data from T80 sep+oct2022, T79 apr2022, T78 jun+jul+aug+sep2022, T77 dec2021 * Adding new filtered data from T80 aug2022 and T78 apr+may2022 * Increasing early-fen-skipping from 28 to 30 ``` python3 easy_train.py \ --experiment-name leela96-dfrc99-T80novT79mayT60novdec-v2-T80augsepoctT79aprT78aprtosep-v6-T77dec-v3-sk30 \ --training-dataset /data/leela96-dfrc99-T80novT79mayT60novdec-v2-T80augsepoctT79aprT78aprtosep-v6-T77dec-v3.binpack \ --nnue-pytorch-branch linrock/nnue-pytorch/misc-fixes \ --start-from-engine-test-net True \ --early-fen-skipping 30 \ --max_epoch 900 \ --start-lambda 1.0 \ --end-lambda 0.7 \ --lr 4.375e-4 \ --gamma 0.995 \ --tui False \ --gpus "0," \ --seed $RANDOM ``` The v3 filtering used for data from T77dec 2021 differs from v2 filtering in that: * To improve binpack compression, positions after ply 28 were skipped during training by setting position scores to VALUE_NONE (32002) instead of removing them entirely * All early-game positions with ply <= 28 were removed to maximize binpack compression * Only bestmove captures at d6pv2 search were skipped, not 2nd bestmove captures * Binpack compression was repaired for the remaining positions by effectively replacing bestmoves with "played moves" to maintain contiguous sequences of positions in the training game data After improving binpack compression, The T77 dec2021 data size was reduced from 95G to 19G. The v6 filtering used for data from T80augsepoctT79aprT78aprtosep 2022 differs from v2 in that: * All positions with only one legal move were removed * Tighter score differences at d6pv2 search were used to remove more positions with only one good move than before * d6pv2 search was not used to remove positions where the best 2 moves were captures ``` python3 interleave_binpacks.py \ nn-547-dataset/leela96-eval-filt-v2.binpack \ nn-547-dataset/dfrc99-eval-filt-v2.binpack \ nn-547-dataset/test80-nov2022-12tb7p-eval-filt-v2-d6.binpack \ nn-547-dataset/T79-may2022-12tb7p-eval-filt-v2.binpack \ nn-547-dataset/T60-nov2021-12tb7p-eval-filt-v2.binpack \ nn-547-dataset/T60-dec2021-12tb7p-eval-filt-v2.binpack \ filt-v6/test80-aug2022-16tb7p-filter-v6.binpack \ filt-v6/test80-sep2022-16tb7p-filter-v6.binpack \ filt-v6/test80-oct2022-16tb7p-filter-v6.binpack \ filt-v6/test79-apr2022-16tb7p-filter-v6.binpack \ filt-v6/test78-aprmay2022-16tb7p-filter-v6.binpack \ filt-v6/test78-junjulaug2022-16tb7p-filter-v6.binpack \ filt-v6/test78-sep2022-16tb7p-filter-v6.binpack \ filt-v3/test77-dec2021-16tb7p-filt-v3.binpack \ /data/leela96-dfrc99-T80novT79mayT60novdec-v2-T80augsepoctT79aprT78aprtosep-v6-T77dec-v3.binpack ``` The code for the new data filtering methods is available at: https://github.com/linrock/Stockfish/tree/nnue-data-v3/nnue-data The code for giving hexword names to .nnue files is at: https://github.com/linrock/nnue-namer Links for downloading the training data components can be found at: https://robotmoon.com/nnue-training-data/ Local elo at 25k nodes per move: nn-epoch779.nnue : 0.6 +/- 3.1 Passed STC: https://tests.stockfishchess.org/tests/view/64212412db43ab2ba6f8efb0 LLR: 2.94 (-2.94,2.94) <0.00,2.00> Total: 82256 W: 22185 L: 21809 D: 38262 Ptnml(0-2): 286, 9065, 22067, 9407, 303 Passed LTC: https://tests.stockfishchess.org/tests/view/64223726db43ab2ba6f91d6c LLR: 2.94 (-2.94,2.94) <0.50,2.50> Total: 30840 W: 8437 L: 8149 D: 14254 Ptnml(0-2): 14, 2891, 9323, 3177, 15 closes https://github.com/official-stockfish/Stockfish/pull/4465 bench 5101970 |
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Linmiao XuandJoost VandeVondele
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876906965b |
Update default net to nn-52471d67216a.nnue
Created by retraining the master net with modifications to the previous best dataset: * Improving T80 oct+nov 2022 endgame lambda accuracy by rescoring with 12-16tb of syzygy 7p tablebases * Filtering T78 jun+jul+aug 2022 with d6pv2 search to remove positions with bestmove captures or one good move * Adding T80 sep 2022 data, rescored with 16tb of 7p tablebases, unfiltered Trained with max-epoch 900, end-lambda 0.7, and early-fen-skipping 28. ``` python3 easy_train.py \ --experiment-name leela96-dfrc99-T80octnovT79aprmayT78junjulaugT60novdec-filt-v2-T78sep12tb7p-T77decT80sep16tb7p-lambda7-sk28 \ --training-dataset /data/leela96-dfrc99-T80octnovT79aprmayT78junjulaugT60novdec-filt-v2-T78sep12tb7p-T77decT80sep16tb7p.binpack \ --nnue-pytorch-branch linrock/nnue-pytorch/easy-train-early-fen-skipping \ --early-fen-skipping 28 \ --start-from-engine-test-net True \ --gpus "0," \ --max_epoch 900 \ --start-lambda 1.0 \ --end-lambda 0.7 \ --gamma 0.995 \ --lr 4.375e-4 \ --tui False \ --seed $RANDOM ``` Training data was rescored and d6pv2 filtered in the same way as recent best datasets. For preparing the merged training dataset: ``` python3 interleave_binpacks.py \ leela96-eval-filt-v2.binpack \ dfrc99-eval-filt-v2.binpack \ test80-oct2022-16tb7p-eval-filt-v2-d6.binpack \ test80-nov2022-12tb7p-eval-filt-v2-d6.binpack \ T79-apr2022-12tb7p-eval-filt-v2.binpack \ T79-may2022-12tb7p-eval-filt-v2.binpack \ test78-junjulaug2022-16tb7p-eval-filt-v2-d6.binpack \ T60-nov2021-12tb7p-eval-filt-v2.binpack \ T60-dec2021-12tb7p-eval-filt-v2.binpack \ T78-sep2022-12tb7p.binpack \ test77-dec2021-16gb7p.binpack \ test80-sep2022-16tb7p.binpack \ /data/leela96-dfrc99-T80octnovT79aprmayT78junjulaugT60novdec-filt-v2-T78sep12tb7p-T77decT80sep16tb7p.binpack ``` Links for downloading the training data components can be found at: https://robotmoon.com/nnue-training-data/ Local elo at 25k nodes per move: nn-epoch839.nnue : 0.6 +/- 1.4 Passed STC: https://tests.stockfishchess.org/tests/view/63f9ab4be74a12625bcdf02e LLR: 2.95 (-2.94,2.94) <0.00,2.00> Total: 84656 W: 22681 L: 22302 D: 39673 Ptnml(0-2): 271, 9343, 22734, 9696, 284 Passed LTC: https://tests.stockfishchess.org/tests/view/63fa3833e74a12625bce0c0e LLR: 2.94 (-2.94,2.94) <0.50,2.50> Total: 184664 W: 49933 L: 49344 D: 85387 Ptnml(0-2): 111, 17977, 55561, 18578, 105 closes https://github.com/official-stockfish/Stockfish/pull/4416 bench: 4814343 |
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Linmiao XuandJoost VandeVondele
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69639d764b |
Reintroduce nnue pawn scaling with lower lazy thresholds
Params found with the nevergrad TBPSA optimizer via nevergrad4sf modified to: * use SPRT LLR with fishtest STC elo gainer bounds [0, 2] as the objective function * increase the game batch size after each new optimal point is found The params were the optimal point after TBPSA iteration 7 and 160 nevergrad evaluations with: * initial batch size of 96 games per evaluation * batch size increase of 64 games after each iteration * a budget of 512 evaluations * TC: fixed 1.5 million nodes per move, no time limit nevergrad4sf enables optimizing stockfish params with TBPSA: https://github.com/vondele/nevergrad4sf Using pentanomial game results with smaller game batch sizes was inspired by: Use of SPRT LLR calculated from pentanomial game results as the objective function was an experiment at maximizing the information from game batches to reduce the computational cost for TBPSA to converge on good parameters. For the exact code used to find the params: https://github.com/linrock/tuning-fork Passed STC: https://tests.stockfishchess.org/tests/view/63f4ef5ee74a12625bcd114a LLR: 2.94 (-2.94,2.94) <0.00,2.00> Total: 66552 W: 17736 L: 17390 D: 31426 Ptnml(0-2): 164, 7229, 18166, 7531, 186 Passed LTC: https://tests.stockfishchess.org/tests/view/63f56028e74a12625bcd2550 LLR: 2.94 (-2.94,2.94) <0.50,2.50> Total: 71264 W: 19150 L: 18787 D: 33327 Ptnml(0-2): 23, 6728, 21771, 7083, 27 closes https://github.com/official-stockfish/Stockfish/pull/4401 bench 3687580 |
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Linmiao XuandJoost VandeVondele
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05dea2ca46 |
Update default net to nn-1337b1adec5b.nnue
Created by retraining the master net on a dataset composed of: * Most of the previous best dataset filtered to remove positions likely having only one good move * Adding training data from Leela T77 dec2021 rescored with 16tb of 7-piece tablebases Trained with end lambda 0.7 and max epoch 900. Positions with ply <= 28 were removed from most of the previous best dataset before training began. A new nnue-pytorch trainer param for skipping early plies was used to skip plies <= 24 in the unfiltered and additional Leela T77 parts of the dataset. ``` python easy_train.py \ --experiment-name leela96-dfrc99-T80octnovT79aprmayT60novdec-eval-filt-v2-T78augsep-12tb-T77dec-16tb-lambda7-sk24 \ --training-dataset /data/leela96-dfrc99-T80octnovT79aprmayT60novdec-eval-filt-v2-T78augsep-12tb-T77dec-16tb.binpack \ --nnue-pytorch-branch linrock/nnue-pytorch/easy-train-early-fen-skipping \ --early-fen-skipping 24 \ --gpus "0," \ --start-from-engine-test-net True \ --start-lambda 1.0 \ --end-lambda 0.7 \ --gamma 0.995 \ --lr 4.375e-4 \ --tui False \ --seed $RANDOM \ --max_epoch 900 ``` The depth6 multipv2 search filtering method is the same as the one used for filtering recent best datasets, with a lower eval difference threshold to remove slightly more positions than before. These parts of the dataset were filtered: * 96% of T60T70wIsRightFarseerT60T74T75T76.binpack * 99% of dfrc_n5000.binpack * T80 oct + nov 2022 data, no positions with castling flags, rescored with ~600gb 7p tablebases * T79 apr + may 2022 data, rescored with 12tb 7p tablebases * T60 nov + dec 2021 data, rescored with 12tb 7p tablebases These parts of the dataset were not filtered. Positions with ply <= 24 were skipped during training: * T78 aug + sep 2022 data, rescored with 12tb 7p tablebases * 84% of T77 dec 2021 data, rescored with 16tb 7p tablebases The code and exact evaluation thresholds used for data filtering can be found at: https://github.com/linrock/Stockfish/tree/tools-filter-multipv2-eval-diff-t2/src/filter The exact training data used can be found at: https://robotmoon.com/nnue-training-data/ Local elo at 25k nodes per move: nn-epoch859.nnue : 3.5 +/ 1.2 Passed STC: LLR: 2.95 (-2.94,2.94) <0.00,2.00> https://tests.stockfishchess.org/tests/view/63dfeefc73223e7f52ad769f Total: 219744 W: 58572 L: 58002 D: 103170 Ptnml(0-2): 609, 24446, 59284, 24832, 701 Passed LTC: https://tests.stockfishchess.org/tests/view/63e268fc73223e7f52ade7b6 LLR: 2.94 (-2.94,2.94) <0.50,2.50> Total: 91256 W: 24528 L: 24121 D: 42607 Ptnml(0-2): 48, 8863, 27390, 9288, 39 closes https://github.com/official-stockfish/Stockfish/pull/4387 bench 3841998 |
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Linmiao XuandJoost VandeVondele
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596a528c6a |
Update default net to nn-bc24c101ada0.nnue
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 |
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Linmiao XuandJoost VandeVondele
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3d2381d76d |
Update default net to nn-1e7ca356472e.nnue
Created by retraining the master net on a dataset composed of: * The Leela-dfrc_n5000.binpack dataset filtered with depth6 multipv2 search to remove positions with only one good move, in addition to removing positions where either of the two best moves are captures * The same Leela T80 oct+nov 2022 training data used in recent best datasets * Additional Leela training data from T60 nov+dec 2021 and T79 apr+may 2022 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-mpv-eval-fonly-T80octnov-T79aprmayT60novdec-12tb7p-sk28-lambda7 \ --training-dataset /data/leela95-dfrc96-mpv-eval-fonly-T80octnov-T79aprmayT60novdec-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 780, training was manually paused and max epoch increased to 920 before resuming. During depth6 multipv2 data filtering, positions were considered to have only one good move if the score of the best move was significantly better than the 2nd best move in a way that changes the outcome of the game: * the best move leads to a significant advantage while the 2nd best move equalizes or loses * the best move is about equal while the 2nd best move loses The modified stockfish branch and exact score thresholds used for filtering are at: https://github.com/linrock/Stockfish/tree/tools-filter-multipv2-eval-diff/src/filter About 95% of the Leela portion and 96% of the DFRC portion of the Leela-dfrc_n5000.binpack dataset was filtered. Unfiltered parts of the dataset were left out. The additional Leela training data from T60 nov+dec 2021 and T79 apr+may 2022 was WDL-rescored with about 12TB of syzygy 7-piece tablebases where the material difference is less than around 6 pawns. Best moves were exported to .plain data files during data conversion with the lc0 rescorer. The exact training data can be found at: https://robotmoon.com/nnue-training-data/ Local elo at 25k nodes per move experiment_leela95-dfrc96-mpv-eval-fonly-T80octnov-T79aprmayT60novdec-12tb7p-sk28-lambda7 run_0/nn-epoch899.nnue : 3.8 +/- 1.6 Passed STC https://tests.stockfishchess.org/tests/view/63bed1f540aa064159b9c89b LLR: 2.94 (-2.94,2.94) <0.00,2.00> Total: 103344 W: 27392 L: 26991 D: 48961 Ptnml(0-2): 333, 11223, 28099, 11744, 273 Passed LTC https://tests.stockfishchess.org/tests/view/63c010415705810de2deb3ec LLR: 2.94 (-2.94,2.94) <0.50,2.50> Total: 21712 W: 5891 L: 5619 D: 10202 Ptnml(0-2): 12, 2022, 6511, 2304, 7 closes https://github.com/official-stockfish/Stockfish/pull/4338 bench 4106793 |
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Linmiao XuandJoost VandeVondele
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a6fa683418 |
Update default net to nn-a3dc078bafc7.nnue
This is a later epoch (epoch 859) from the same experiment run that trained yesterday's master net nn-60fa44e376d9.nnue (epoch 779). The experiment was manually paused around epoch 790 and unpaused with max epoch increased to 900 mainly to get more local elo data without letting the GPU idle. nn-60fa44e376d9.nnue is from #4314 nn-335a9b2d8a80.nnue is from #4295 Local elo vs. nn-335a9b2d8a80.nnue at 25k nodes per move: experiment_leela93-dfrc99-filt-only-T80-oct-nov-skip28 run_0/nn-epoch779.nnue (nn-60fa44e376d9.nnue) : 5.0 +/- 1.2 run_0/nn-epoch859.nnue (nn-a3dc078bafc7.nnue) : 5.6 +/- 1.6 Passed STC vs. nn-335a9b2d8a80.nnue https://tests.stockfishchess.org/tests/view/63ae10495bd1e5f27f13d94f LLR: 2.95 (-2.94,2.94) <0.00,2.00> Total: 37536 W: 10088 L: 9781 D: 17667 Ptnml(0-2): 110, 4006, 10223, 4325, 104 An LTC test vs. nn-335a9b2d8a80.nnue was paused due to nn-60fa44e376d9.nnue passing LTC first: https://tests.stockfishchess.org/tests/view/63ae5d34331d5fca5113703b Passed LTC vs. nn-60fa44e376d9.nnue https://tests.stockfishchess.org/tests/view/63af1e41465d2b022dbce4e7 LLR: 2.94 (-2.94,2.94) <0.50,2.50> Total: 148704 W: 39672 L: 39155 D: 69877 Ptnml(0-2): 59, 14443, 44843, 14936, 71 closes https://github.com/official-stockfish/Stockfish/pull/4319 bench 3984365 |
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Linmiao XuandJoost VandeVondele
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be9bc420af |
Update default net to nn-60fa44e376d9.nnue
Created by retraining the master net on the previous best dataset with additional filtering. No new data was added. More of the Leela-dfrc_n5000.binpack part of the dataset was pre-filtered with depth6 multipv2 search to remove bestmove captures. About 93% of the previous Leela/SF data and 99% of the SF dfrc data was filtered. Unfiltered parts of the dataset were left out. The new Leela T80 oct+nov data is the same as before. All early game positions with ply count <= 28 were skipped during training by modifying the training data loader in nnue-pytorch. Trained in a similar way as recent master nets, with a different nnue-pytorch branch for early ply skipping: python3 easy_train.py \ --experiment-name=leela93-dfrc99-filt-only-T80-oct-nov-skip28 \ --training-dataset=/data/leela93-dfrc99-filt-only-T80-oct-nov.binpack \ --start-from-engine-test-net True \ --nnue-pytorch-branch=linrock/nnue-pytorch/misc-fixes-skip-ply-lteq-28 \ --gpus="0," \ --start-lambda=1.0 \ --end-lambda=0.75 \ --gamma=0.995 \ --lr=4.375e-4 \ --tui=False \ --seed=$RANDOM \ --max_epoch=800 \ --network-testing-threads 20 \ --num-workers 6 For the exact training data used: https://robotmoon.com/nnue-training-data/ Details about the previous best dataset: #4295 Local testing at a fixed 25k nodes: experiment_leela93-dfrc99-filt-only-T80-oct-nov-skip28 Local Elo: run_0/nn-epoch779.nnue : 5.1 +/- 1.5 Passed STC https://tests.stockfishchess.org/tests/view/63adb3acae97a464904fd4e8 LLR: 2.94 (-2.94,2.94) <0.00,2.00> Total: 36504 W: 9847 L: 9538 D: 17119 Ptnml(0-2): 108, 3981, 9784, 4252, 127 Passed LTC https://tests.stockfishchess.org/tests/view/63ae0ae25bd1e5f27f13d884 LLR: 2.94 (-2.94,2.94) <0.50,2.50> Total: 36592 W: 10017 L: 9717 D: 16858 Ptnml(0-2): 17, 3461, 11037, 3767, 14 closes https://github.com/official-stockfish/Stockfish/pull/4314 bench 4015511 |
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Linmiao XuandJoost VandeVondele
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c620886181 |
Update default net to nn-335a9b2d8a80.nnue
Created by retraining the master net with a combination of:
the previous best dataset (Leela-dfrc_n5000.binpack), with about half the dataset filtered using depth6 multipv2 search to throw away positions where either of the 2 best moves are captures
Leela T80 Oct and Nov training data rescored with best moves, adding ~9.5 billion positions
Trained effectively the same way as the previous master net:
python3 easy_train.py \
--experiment-name=leela-dfrc-filtered-T80-oct-nov \
--training-dataset=/data/leela-dfrc-filtered-T80-oct-nov.binpack \
--start-from-engine-test-net True \
--gpus="0," \
--start-lambda=1.0 \
--end-lambda=0.75 \
--gamma=0.995 \
--lr=4.375e-4 \
--tui=False \
--seed=$RANDOM \
--max_epoch=800 \
--auto-exit-timeout-on-training-finished=900 \
--network-testing-threads 20 \
--num-workers 6
Local testing at a fixed 25k nodes:
experiments/experiment_leela-dfrc-filtered-T80-oct-nov/training/run_0/nn-epoch779.nnue
localElo: run_0/nn-epoch779.nnue : 4.7 +/- 3.1
The new Leela T80 part of the dataset was prepared by downloading test80 training data from all of Oct 2022 and Nov 2022, rescoring with syzygy 6-piece tablebases and ~600 GB of 7-piece tablebases, saving best moves to exported .plain files, removing all positions with castling flags, then converting to binpacks and using interleave_binpacks.py to merge them together. Scripts used in this data conversion process are available at:
https://github.com/linrock/lc0-data-converter
Filtering binpack data using depth6 multipv2 search was done by modifying transform.cpp in the tools branch:
https://github.com/linrock/Stockfish/tree/tools-filter-multipv2-no-rescore
Links for downloading the training data (total size: 338 GB) are available at:
https://robotmoon.com/nnue-training-data/
Passed STC:
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 30544 W: 8244 L: 7947 D: 14353
Ptnml(0-2): 93, 3243, 8302, 3542, 92
https://tests.stockfishchess.org/tests/view/63a0d377264a0cf18f86f82b
Passed LTC:
LLR: 2.95 (-2.94,2.94) <0.50,2.50>
Total: 32464 W: 8866 L: 8573 D: 15025
Ptnml(0-2): 19, 3054, 9794, 3345, 20
https://tests.stockfishchess.org/tests/view/63a10bc9fb452d3c44b1e016
closes https://github.com/official-stockfish/Stockfish/pull/4295
Bench 3554904
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Linmiao XuandJoost VandeVondele
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7f8166db89 |
Tuned safe checks and minor piece king protectors
A combination of terms related to king safety one tuned safe check weights,
the other tuned knight and bishop king protector weights separately with
some compensation in the high outpost bonuses given to the minor pieces.
passed STC
LLR: 2.95 (-2.94,2.94) {-0.50,1.50}
Total: 39892 W: 7594 L: 7350 D: 24948
Ptnml(0-2): 643, 4559, 9314, 4771, 659
https://tests.stockfishchess.org/tests/view/5ea49635b908f6dd28f34b82
passed LTC
LLR: 2.94 (-2.94,2.94) {0.25,1.75}
Total: 104934 W: 13300 L: 12834 D: 78800
Ptnml(0-2): 697, 9571, 31514, 9939, 746
https://tests.stockfishchess.org/tests/view/5ea4abf6b908f6dd28f34bcb
closes https://github.com/official-stockfish/Stockfish/pull/2649
Bench 4800754
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