Update default net to nn-0dd1cebea573.nnue #4606
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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 bench 2141197
linrock
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Jun 29, 2023
Creating this net involved: - a 5-step training process from scratch - greedy permuting L1 weights with official-stockfish#4620 - leb128 compression with official-stockfish/nnue-pytorch#251 - greedy 2- and 3- cycle permuting with official-stockfish#4640 The 5 training steps were: 1. 400 epochs, lambda 1.0, lr 9.75e-4 UHOx2-wIsRight-multinet-dfrc-n5000-largeGensfen-d9.binpack (178G) 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 large_gensfen_multipvdiff_100_d9.binpack ep399 chosen as start model for step2 2. 800 epochs, end-lambda 0.75, skip 16 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 ep559 chosen as start model for step3 3. 800 epochs, end-lambda 0.725, skip 20 leela96-dfrc99-v2-T80dectofeb-sk20-mar-v6-T77decT78janfebT79apr.binpack (223G) leela96-filt-v2.min.binpack dfrc99-16tb7p-eval-filt-v2.min.binpack test80-dec2022-16tb7p-filter-v6-sk20.min-mar2023.binpack test80-jan2023-16tb7p-filter-v6-sk20.min-mar2023.binpack test80-feb2023-16tb7p-filter-v6-sk20.min-mar2023.binpack test80-mar2023-2tb7p-filter-v6.min.binpack test77-dec2021-16tb7p.no-db.min.binpack test78-janfeb2022-16tb7p.no-db.min.binpack test79-apr2022-16tb7p.no-db.min.binpack ep499 chosen as start model for step4 4. 800 epochs, end-lambda 0.7, skip 24 0dd1cebea57 dataset official-stockfish#4606 ep599 chosen as start model for step5 5. 800 epochs, end-lambda 0.7, skip 28 same dataset as step4 ep619 became nn-1b951f8b449d.nnue For the final step5 training: python3 easy_train.py \ --experiment-name L1-2048-S5-sameData-sk28-S4-0dd1cebea57-shuffled-S3-leela96-dfrc99-v2-T80dectofeb-sk20-mar-v6-T77decT78janfebT79apr-sk20-S2-LeelaFarseerT78T79T80-ep399-S1-UHOx2-wIsRight-multinet-dfrc-n5000-largeGensfen-d9 \ --training-dataset /data/leela96-dfrc99-T60novdec-v2-T80juntonovjanfebT79aprmayT78jantosepT77dec-v6dd-T80apr.binpack \ --early-fen-skipping 28 \ --nnue-pytorch-branch linrock/nnue-pytorch/misc-fixes-L1-2048 \ --engine-test-branch linrock/Stockfish/L1-2048 \ --start-from-engine-test-net False \ --start-from-model /data/experiments/experiment_L1-2048-S4-0dd1cebea57-shuffled-S3-leela96-dfrc99-v2-T80dectofeb-sk20-mar-v6-T77decT78janfebT79apr-sk20-S2-LeelaFarseerT78T79T80-ep399-S1-UHOx2-wIsRight-multinet-dfrc-n5000-largeGensfen-d9/training/run_0/nn-epoch599.nnue --max_epoch 800 \ --lr 4.375e-4 \ --gamma 0.995 \ --start-lambda 1.0 \ --end-lambda 0.7 \ --tui False \ --seed $RANDOM \ --gpus 0 SF training data components for the step1 dataset: https://drive.google.com/drive/folders/1yLCEmioC3Xx9KQr4T7uB6GnLm5icAYGU Leela training data for steps 2-5 can be found at: https://robotmoon.com/nnue-training-data/ Due to larger L1 size and slower inference, the speed penalty loses elo at STC. Measurements from 100 bench runs at depth 13 with x86-64-modern on Intel Core i5-1038NG7 2.00GHz: sf_base = 1240730 +/- 3443 (95%) sf_test = 1153341 +/- 2832 (95%) diff = -87388 +/- 1616 (95%) speedup = -7.04330% +/- 0.130% (95%) Local elo at 25k nodes per move (vs. L1-1536 nn-fdc1d0fe6455.nnue): nn-epoch619.nnue : 21.1 +/- 3.2 Failed STC: https://tests.stockfishchess.org/tests/view/6498ee93dc7002ce609cf979 LLR: -2.95 (-2.94,2.94) <0.00,2.00> Total: 11680 W: 3058 L: 3299 D: 5323 Ptnml(0-2): 44, 1422, 3149, 1181, 44 LTC: https://tests.stockfishchess.org/tests/view/649b32f5dc7002ce609d20cf Elo: 0.68 ± 1.5 (95%) LOS: 80.5% Total: 40000 W: 10887 L: 10809 D: 18304 Ptnml(0-2): 36, 3938, 11958, 4048, 20 nElo: 1.50 ± 3.4 (95%) PairsRatio: 1.02 Passed VLTC 180+1.8: https://tests.stockfishchess.org/tests/view/64992b43dc7002ce609cfd20 LLR: 3.06 (-2.94,2.94) <0.00,2.00> Total: 38086 W: 10612 L: 10338 D: 17136 Ptnml(0-2): 9, 3316, 12115, 3598, 5 Passed VLTC SMP 60+0.6 th 8: https://tests.stockfishchess.org/tests/view/649a21fedc7002ce609d0c7d LLR: 2.95 (-2.94,2.94) <0.50,2.50> Total: 38936 W: 11091 L: 10820 D: 17025 Ptnml(0-2): 1, 2948, 13305, 3207, 7 bench 2858591
linrock
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Jun 29, 2023
Creating this net involved: - a 5-step training process from scratch - greedy permuting L1 weights with official-stockfish#4620 - leb128 compression with official-stockfish/nnue-pytorch#251 - greedy 2- and 3- cycle permuting with official-stockfish#4640 The 5 training steps were: 1. 400 epochs, lambda 1.0, lr 9.75e-4 UHOx2-wIsRight-multinet-dfrc-n5000-largeGensfen-d9.binpack (178G) 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 large_gensfen_multipvdiff_100_d9.binpack ep399 chosen as start model for step2 2. 800 epochs, end-lambda 0.75, skip 16 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 ep559 chosen as start model for step3 3. 800 epochs, end-lambda 0.725, skip 20 leela96-dfrc99-v2-T80dectofeb-sk20-mar-v6-T77decT78janfebT79apr.binpack (223G) leela96-filt-v2.min.binpack dfrc99-16tb7p-eval-filt-v2.min.binpack test80-dec2022-16tb7p-filter-v6-sk20.min-mar2023.binpack test80-jan2023-16tb7p-filter-v6-sk20.min-mar2023.binpack test80-feb2023-16tb7p-filter-v6-sk20.min-mar2023.binpack test80-mar2023-2tb7p-filter-v6.min.binpack test77-dec2021-16tb7p.no-db.min.binpack test78-janfeb2022-16tb7p.no-db.min.binpack test79-apr2022-16tb7p.no-db.min.binpack ep499 chosen as start model for step4 4. 800 epochs, end-lambda 0.7, skip 24 0dd1cebea57 dataset official-stockfish#4606 ep599 chosen as start model for step5 5. 800 epochs, end-lambda 0.7, skip 28 same dataset as step4 ep619 became nn-1b951f8b449d.nnue For the final step5 training: python3 easy_train.py \ --experiment-name L1-2048-S5-sameData-sk28-S4-0dd1cebea57-shuffled-S3-leela96-dfrc99-v2-T80dectofeb-sk20-mar-v6-T77decT78janfebT79apr-sk20-S2-LeelaFarseerT78T79T80-ep399-S1-UHOx2-wIsRight-multinet-dfrc-n5000-largeGensfen-d9 \ --training-dataset /data/leela96-dfrc99-T60novdec-v2-T80juntonovjanfebT79aprmayT78jantosepT77dec-v6dd-T80apr.binpack \ --early-fen-skipping 28 \ --nnue-pytorch-branch linrock/nnue-pytorch/misc-fixes-L1-2048 \ --engine-test-branch linrock/Stockfish/L1-2048 \ --start-from-engine-test-net False \ --start-from-model /data/experiments/experiment_L1-2048-S4-0dd1cebea57-shuffled-S3-leela96-dfrc99-v2-T80dectofeb-sk20-mar-v6-T77decT78janfebT79apr-sk20-S2-LeelaFarseerT78T79T80-ep399-S1-UHOx2-wIsRight-multinet-dfrc-n5000-largeGensfen-d9/training/run_0/nn-epoch599.nnue --max_epoch 800 \ --lr 4.375e-4 \ --gamma 0.995 \ --start-lambda 1.0 \ --end-lambda 0.7 \ --tui False \ --seed $RANDOM \ --gpus 0 SF training data components for the step1 dataset: https://drive.google.com/drive/folders/1yLCEmioC3Xx9KQr4T7uB6GnLm5icAYGU Leela training data for steps 2-5 can be found at: https://robotmoon.com/nnue-training-data/ Due to larger L1 size and slower inference, the speed penalty loses elo at STC. Measurements from 100 bench runs at depth 13 with x86-64-modern on Intel Core i5-1038NG7 2.00GHz: sf_base = 1240730 +/- 3443 (95%) sf_test = 1153341 +/- 2832 (95%) diff = -87388 +/- 1616 (95%) speedup = -7.04330% +/- 0.130% (95%) Local elo at 25k nodes per move (vs. L1-1536 nn-fdc1d0fe6455.nnue): nn-epoch619.nnue : 21.1 +/- 3.2 Failed STC: https://tests.stockfishchess.org/tests/view/6498ee93dc7002ce609cf979 LLR: -2.95 (-2.94,2.94) <0.00,2.00> Total: 11680 W: 3058 L: 3299 D: 5323 Ptnml(0-2): 44, 1422, 3149, 1181, 44 LTC: https://tests.stockfishchess.org/tests/view/649b32f5dc7002ce609d20cf Elo: 0.68 ± 1.5 (95%) LOS: 80.5% Total: 40000 W: 10887 L: 10809 D: 18304 Ptnml(0-2): 36, 3938, 11958, 4048, 20 nElo: 1.50 ± 3.4 (95%) PairsRatio: 1.02 Passed VLTC 180+1.8: https://tests.stockfishchess.org/tests/view/64992b43dc7002ce609cfd20 LLR: 3.06 (-2.94,2.94) <0.00,2.00> Total: 38086 W: 10612 L: 10338 D: 17136 Ptnml(0-2): 9, 3316, 12115, 3598, 5 Passed VLTC SMP 60+0.6 th 8: https://tests.stockfishchess.org/tests/view/649a21fedc7002ce609d0c7d LLR: 2.95 (-2.94,2.94) <0.50,2.50> Total: 38936 W: 11091 L: 10820 D: 17025 Ptnml(0-2): 1, 2948, 13305, 3207, 7 bench 2858591
vondele
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Jul 1, 2023
Creating this net involved: - a 5-step training process from scratch - greedy permuting L1 weights with official-stockfish#4620 - leb128 compression with official-stockfish/nnue-pytorch#251 - greedy 2- and 3- cycle permuting with official-stockfish#4640 The 5 training steps were: 1. 400 epochs, lambda 1.0, lr 9.75e-4 UHOx2-wIsRight-multinet-dfrc-n5000-largeGensfen-d9.binpack (178G) 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 large_gensfen_multipvdiff_100_d9.binpack ep399 chosen as start model for step2 2. 800 epochs, end-lambda 0.75, skip 16 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 ep559 chosen as start model for step3 3. 800 epochs, end-lambda 0.725, skip 20 leela96-dfrc99-v2-T80dectofeb-sk20-mar-v6-T77decT78janfebT79apr.binpack (223G) leela96-filt-v2.min.binpack dfrc99-16tb7p-eval-filt-v2.min.binpack test80-dec2022-16tb7p-filter-v6-sk20.min-mar2023.binpack test80-jan2023-16tb7p-filter-v6-sk20.min-mar2023.binpack test80-feb2023-16tb7p-filter-v6-sk20.min-mar2023.binpack test80-mar2023-2tb7p-filter-v6.min.binpack test77-dec2021-16tb7p.no-db.min.binpack test78-janfeb2022-16tb7p.no-db.min.binpack test79-apr2022-16tb7p.no-db.min.binpack ep499 chosen as start model for step4 4. 800 epochs, end-lambda 0.7, skip 24 0dd1cebea57 dataset official-stockfish#4606 ep599 chosen as start model for step5 5. 800 epochs, end-lambda 0.7, skip 28 same dataset as step4 ep619 became nn-1b951f8b449d.nnue For the final step5 training: python3 easy_train.py \ --experiment-name L1-2048-S5-sameData-sk28-S4-0dd1cebea57-shuffled-S3-leela96-dfrc99-v2-T80dectofeb-sk20-mar-v6-T77decT78janfebT79apr-sk20-S2-LeelaFarseerT78T79T80-ep399-S1-UHOx2-wIsRight-multinet-dfrc-n5000-largeGensfen-d9 \ --training-dataset /data/leela96-dfrc99-T60novdec-v2-T80juntonovjanfebT79aprmayT78jantosepT77dec-v6dd-T80apr.binpack \ --early-fen-skipping 28 \ --nnue-pytorch-branch linrock/nnue-pytorch/misc-fixes-L1-2048 \ --engine-test-branch linrock/Stockfish/L1-2048 \ --start-from-engine-test-net False \ --start-from-model /data/experiments/experiment_L1-2048-S4-0dd1cebea57-shuffled-S3-leela96-dfrc99-v2-T80dectofeb-sk20-mar-v6-T77decT78janfebT79apr-sk20-S2-LeelaFarseerT78T79T80-ep399-S1-UHOx2-wIsRight-multinet-dfrc-n5000-largeGensfen-d9/training/run_0/nn-epoch599.nnue --max_epoch 800 \ --lr 4.375e-4 \ --gamma 0.995 \ --start-lambda 1.0 \ --end-lambda 0.7 \ --tui False \ --seed $RANDOM \ --gpus 0 SF training data components for the step1 dataset: https://drive.google.com/drive/folders/1yLCEmioC3Xx9KQr4T7uB6GnLm5icAYGU Leela training data for steps 2-5 can be found at: https://robotmoon.com/nnue-training-data/ Due to larger L1 size and slower inference, the speed penalty loses elo at STC. Measurements from 100 bench runs at depth 13 with x86-64-modern on Intel Core i5-1038NG7 2.00GHz: sf_base = 1240730 +/- 3443 (95%) sf_test = 1153341 +/- 2832 (95%) diff = -87388 +/- 1616 (95%) speedup = -7.04330% +/- 0.130% (95%) Local elo at 25k nodes per move (vs. L1-1536 nn-fdc1d0fe6455.nnue): nn-epoch619.nnue : 21.1 +/- 3.2 Failed STC: https://tests.stockfishchess.org/tests/view/6498ee93dc7002ce609cf979 LLR: -2.95 (-2.94,2.94) <0.00,2.00> Total: 11680 W: 3058 L: 3299 D: 5323 Ptnml(0-2): 44, 1422, 3149, 1181, 44 LTC: https://tests.stockfishchess.org/tests/view/649b32f5dc7002ce609d20cf Elo: 0.68 ± 1.5 (95%) LOS: 80.5% Total: 40000 W: 10887 L: 10809 D: 18304 Ptnml(0-2): 36, 3938, 11958, 4048, 20 nElo: 1.50 ± 3.4 (95%) PairsRatio: 1.02 Passed VLTC 180+1.8: https://tests.stockfishchess.org/tests/view/64992b43dc7002ce609cfd20 LLR: 3.06 (-2.94,2.94) <0.00,2.00> Total: 38086 W: 10612 L: 10338 D: 17136 Ptnml(0-2): 9, 3316, 12115, 3598, 5 Passed VLTC SMP 60+0.6 th 8: https://tests.stockfishchess.org/tests/view/649a21fedc7002ce609d0c7d LLR: 2.95 (-2.94,2.94) <0.50,2.50> Total: 38936 W: 11091 L: 10820 D: 17025 Ptnml(0-2): 1, 2948, 13305, 3207, 7 closes official-stockfish#4646 Bench: 2505168
linrock
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Sep 11, 2023
Created by retraining the master net on a dataset composed by: - adding Leela data from T60 jul-dec 2020, T77 nov 2021, T80 jun-jul 2023 - deduplicating and unminimizing parts of the dataset before interleaving Trained initially with max epoch 800, then increased near the end of training twice. First to 960, then 1200. After training, post-processing involved: - greedy permuting L1 weights with official-stockfish#4620 - greedy 2- and 3- cycle permuting with official-stockfish#4640 python3 easy_train.py \ --experiment-name 2048-retrain-S6-sk28 \ --training-dataset /data/S6.binpack \ --early-fen-skipping 28 \ --start-from-engine-test-net True \ --max_epoch 1200 \ --lr 4.375e-4 \ --gamma 0.995 \ --start-lambda 1.0 \ --end-lambda 0.7 \ --tui False \ --seed $RANDOM \ --gpus 0 In the list of datasets below, periods in the filename represent the sequence of steps applied to arrive at the particular binpack. For example: test77-dec2021-16tb7p.filter-v6-dd.min-mar2023.unminimized.binpack 1. test77 dec2021 data rescored with 16 TB of syzygy tablebases during data conversion 2. filtered with csv_filter_v6_dd.py - v6 filtering and deduplication in one step 3. minimized with the original mar2023 implementation of `minimize_binpack` in the tools branch 4. unminimized by removing all positions with score == 32002 (`VALUE_NONE`) Binpacks were: - filtered with: https://github.com/linrock/nnue-data - unminimized with: https://github.com/linrock/Stockfish/tree/tools-unminify - deduplicated with: https://github.com/linrock/Stockfish/tree/tools-dd DATASETS=( leela96-filt-v2.min.unminimized.binpack dfrc99-16tb7p-eval-filt-v2.min.unminimized.binpack # most of the 0dd1cebea57 v6-dd dataset (without test80-jul2022) # official-stockfish#4606 test60-novdec2021-12tb7p.filter-v6-dd.min-mar2023.unminimized.binpack test77-dec2021-16tb7p.filter-v6-dd.min-mar2023.unminimized.binpack test78-jantomay2022-16tb7p.filter-v6-dd.min-mar2023.unminimized.binpack test78-juntosep2022-16tb7p.filter-v6-dd.min-mar2023.unminimized.binpack test79-apr2022-16tb7p.filter-v6-dd.min-mar2023.unminimized.binpack test79-may2022-16tb7p.filter-v6-dd.min-mar2023.unminimized.binpack test80-jun2022-16tb7p.filter-v6-dd.min-mar2023.unminimized.binpack test80-aug2022-16tb7p.filter-v6-dd.min-mar2023.unminimized.binpack test80-sep2022-16tb7p.filter-v6-dd.min-mar2023.unminimized.binpack test80-oct2022-16tb7p.filter-v6-dd.min.binpack test80-nov2022-16tb7p.filter-v6-dd.min.binpack test80-jan2023-3of3-16tb7p.filter-v6-dd.min-mar2023.unminimized.binpack test80-feb2023-16tb7p.filter-v6-dd.min-mar2023.unminimized.binpack # older Leela data, recently converted test60-octnovdec2020-2tb7p.min.unminimized.binpack test60-julaugsep2020-2tb7p.min.binpack test77-nov2021-2tb7p.min.dd.binpack # newer Leela data test80-mar2023-2tb7p.min.unminimized.binpack test80-apr2023-2tb7p.filter-v6-sk16.min.unminimized.binpack test80-may2023-2tb7p.min.dd.binpack test80-jun2023-2tb7p.min.binpack test80-jul2023-2tb7p.binpack ) python3 interleave_binpacks.py ${DATASETS[@]} S6.binpack Training data can be found at: https://robotmoon.com/nnue-training-data/ Local elo at 25k nodes per move: nn-epoch1059 : 2.7 +/- 1.6 Passed STC: https://tests.stockfishchess.org/tests/view/64fc8d705dab775b5359db42 LLR: 2.93 (-2.94,2.94) <0.00,2.00> Total: 168352 W: 43216 L: 42704 D: 82432 Ptnml(0-2): 599, 19672, 43134, 20160, 611 Passed LTC: https://tests.stockfishchess.org/tests/view/64fd44a75dab775b5359f065 LLR: 2.94 (-2.94,2.94) <0.50,2.50> Total: 154194 W: 39436 L: 38881 D: 75877 Ptnml(0-2): 78, 16577, 43238, 17120, 84 bench 1672490
linrock
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Sep 11, 2023
Created by retraining the master net on a dataset composed by: - adding Leela data from T60 jul-dec 2020, T77 nov 2021, T80 jun-jul 2023 - deduplicating and unminimizing parts of the dataset before interleaving Trained initially with max epoch 800, then increased near the end of training twice. First to 960, then 1200. After training, post-processing involved: - greedy permuting L1 weights with official-stockfish#4620 - greedy 2- and 3- cycle permuting with official-stockfish#4640 python3 easy_train.py \ --experiment-name 2048-retrain-S6-sk28 \ --training-dataset /data/S6.binpack \ --early-fen-skipping 28 \ --start-from-engine-test-net True \ --max_epoch 1200 \ --lr 4.375e-4 \ --gamma 0.995 \ --start-lambda 1.0 \ --end-lambda 0.7 \ --tui False \ --seed $RANDOM \ --gpus 0 In the list of datasets below, periods in the filename represent the sequence of steps applied to arrive at the particular binpack. For example: test77-dec2021-16tb7p.filter-v6-dd.min-mar2023.unminimized.binpack 1. test77 dec2021 data rescored with 16 TB of syzygy tablebases during data conversion 2. filtered with csv_filter_v6_dd.py - v6 filtering and deduplication in one step 3. minimized with the original mar2023 implementation of `minimize_binpack` in the tools branch 4. unminimized by removing all positions with score == 32002 (`VALUE_NONE`) Binpacks were: - filtered with: https://github.com/linrock/nnue-data - unminimized with: https://github.com/linrock/Stockfish/tree/tools-unminify - deduplicated with: https://github.com/linrock/Stockfish/tree/tools-dd DATASETS=( leela96-filt-v2.min.unminimized.binpack dfrc99-16tb7p-eval-filt-v2.min.unminimized.binpack # most of the 0dd1cebea57 v6-dd dataset (without test80-jul2022) # official-stockfish#4606 test60-novdec2021-12tb7p.filter-v6-dd.min-mar2023.unminimized.binpack test77-dec2021-16tb7p.filter-v6-dd.min-mar2023.unminimized.binpack test78-jantomay2022-16tb7p.filter-v6-dd.min-mar2023.unminimized.binpack test78-juntosep2022-16tb7p.filter-v6-dd.min-mar2023.unminimized.binpack test79-apr2022-16tb7p.filter-v6-dd.min-mar2023.unminimized.binpack test79-may2022-16tb7p.filter-v6-dd.min-mar2023.unminimized.binpack test80-jun2022-16tb7p.filter-v6-dd.min-mar2023.unminimized.binpack test80-aug2022-16tb7p.filter-v6-dd.min-mar2023.unminimized.binpack test80-sep2022-16tb7p.filter-v6-dd.min-mar2023.unminimized.binpack test80-oct2022-16tb7p.filter-v6-dd.min.binpack test80-nov2022-16tb7p.filter-v6-dd.min.binpack test80-jan2023-3of3-16tb7p.filter-v6-dd.min-mar2023.unminimized.binpack test80-feb2023-16tb7p.filter-v6-dd.min-mar2023.unminimized.binpack # older Leela data, recently converted test60-octnovdec2020-2tb7p.min.unminimized.binpack test60-julaugsep2020-2tb7p.min.binpack test77-nov2021-2tb7p.min.dd.binpack # newer Leela data test80-mar2023-2tb7p.min.unminimized.binpack test80-apr2023-2tb7p.filter-v6-sk16.min.unminimized.binpack test80-may2023-2tb7p.min.dd.binpack test80-jun2023-2tb7p.min.binpack test80-jul2023-2tb7p.binpack ) python3 interleave_binpacks.py ${DATASETS[@]} /data/S6.binpack Training data can be found at: https://robotmoon.com/nnue-training-data/ Local elo at 25k nodes per move: nn-epoch1059 : 2.7 +/- 1.6 Passed STC: https://tests.stockfishchess.org/tests/view/64fc8d705dab775b5359db42 LLR: 2.93 (-2.94,2.94) <0.00,2.00> Total: 168352 W: 43216 L: 42704 D: 82432 Ptnml(0-2): 599, 19672, 43134, 20160, 611 Passed LTC: https://tests.stockfishchess.org/tests/view/64fd44a75dab775b5359f065 LLR: 2.94 (-2.94,2.94) <0.50,2.50> Total: 154194 W: 39436 L: 38881 D: 75877 Ptnml(0-2): 78, 16577, 43238, 17120, 84 bench 1672490
Disservin
pushed a commit
that referenced
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Sep 11, 2023
Created by retraining the master net on a dataset composed by: - adding Leela data from T60 jul-dec 2020, T77 nov 2021, T80 jun-jul 2023 - deduplicating and unminimizing parts of the dataset before interleaving Trained initially with max epoch 800, then increased near the end of training twice. First to 960, then 1200. After training, post-processing involved: - greedy permuting L1 weights with #4620 - greedy 2- and 3- cycle permuting with #4640 python3 easy_train.py \ --experiment-name 2048-retrain-S6-sk28 \ --training-dataset /data/S6.binpack \ --early-fen-skipping 28 \ --start-from-engine-test-net True \ --max_epoch 1200 \ --lr 4.375e-4 \ --gamma 0.995 \ --start-lambda 1.0 \ --end-lambda 0.7 \ --tui False \ --seed $RANDOM \ --gpus 0 In the list of datasets below, periods in the filename represent the sequence of steps applied to arrive at the particular binpack. For example: test77-dec2021-16tb7p.filter-v6-dd.min-mar2023.unminimized.binpack 1. test77 dec2021 data rescored with 16 TB of syzygy tablebases during data conversion 2. filtered with csv_filter_v6_dd.py - v6 filtering and deduplication in one step 3. minimized with the original mar2023 implementation of `minimize_binpack` in the tools branch 4. unminimized by removing all positions with score == 32002 (`VALUE_NONE`) Binpacks were: - filtered with: https://github.com/linrock/nnue-data - unminimized with: https://github.com/linrock/Stockfish/tree/tools-unminify - deduplicated with: https://github.com/linrock/Stockfish/tree/tools-dd DATASETS=( leela96-filt-v2.min.unminimized.binpack dfrc99-16tb7p-eval-filt-v2.min.unminimized.binpack # most of the 0dd1cebea57 v6-dd dataset (without test80-jul2022) # #4606 test60-novdec2021-12tb7p.filter-v6-dd.min-mar2023.unminimized.binpack test77-dec2021-16tb7p.filter-v6-dd.min-mar2023.unminimized.binpack test78-jantomay2022-16tb7p.filter-v6-dd.min-mar2023.unminimized.binpack test78-juntosep2022-16tb7p.filter-v6-dd.min-mar2023.unminimized.binpack test79-apr2022-16tb7p.filter-v6-dd.min-mar2023.unminimized.binpack test79-may2022-16tb7p.filter-v6-dd.min-mar2023.unminimized.binpack test80-jun2022-16tb7p.filter-v6-dd.min-mar2023.unminimized.binpack test80-aug2022-16tb7p.filter-v6-dd.min-mar2023.unminimized.binpack test80-sep2022-16tb7p.filter-v6-dd.min-mar2023.unminimized.binpack test80-oct2022-16tb7p.filter-v6-dd.min.binpack test80-nov2022-16tb7p.filter-v6-dd.min.binpack test80-jan2023-3of3-16tb7p.filter-v6-dd.min-mar2023.unminimized.binpack test80-feb2023-16tb7p.filter-v6-dd.min-mar2023.unminimized.binpack # older Leela data, recently converted test60-octnovdec2020-2tb7p.min.unminimized.binpack test60-julaugsep2020-2tb7p.min.binpack test77-nov2021-2tb7p.min.dd.binpack # newer Leela data test80-mar2023-2tb7p.min.unminimized.binpack test80-apr2023-2tb7p.filter-v6-sk16.min.unminimized.binpack test80-may2023-2tb7p.min.dd.binpack test80-jun2023-2tb7p.min.binpack test80-jul2023-2tb7p.binpack ) python3 interleave_binpacks.py ${DATASETS[@]} /data/S6.binpack Training data can be found at: https://robotmoon.com/nnue-training-data/ Local elo at 25k nodes per move: nn-epoch1059 : 2.7 +/- 1.6 Passed STC: https://tests.stockfishchess.org/tests/view/64fc8d705dab775b5359db42 LLR: 2.93 (-2.94,2.94) <0.00,2.00> Total: 168352 W: 43216 L: 42704 D: 82432 Ptnml(0-2): 599, 19672, 43134, 20160, 611 Passed LTC: https://tests.stockfishchess.org/tests/view/64fd44a75dab775b5359f065 LLR: 2.94 (-2.94,2.94) <0.50,2.50> Total: 154194 W: 39436 L: 38881 D: 75877 Ptnml(0-2): 78, 16577, 43238, 17120, 84 closes #4782 Bench: 1603079
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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:
This net was epoch 559 of the final (step 5) retraining:
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:
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
bench 2141197