Dev Builds » 20231230-1008

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NCM plays each Stockfish dev build 20,000 times against Stockfish 15. This yields an approximate Elo difference and establishes confidence in the strength of the dev builds.

Summary

Host Duration Avg Base NPS Games WLD Standard Elo Ptnml(0-2) Gamepair Elo

Test Detail

ID Host Base NPS Games WLD Standard Elo Ptnml(0-2) Gamepair Elo CLI PGN

Commit

Commit ID f12035c88c58a5fd568d26cde9868f73a8d7b839
Author Linmiao Xu
Date 2023-12-30 10:08:03 UTC
Update default net to nn-b1e55edbea57.nnue Created by retraining the master big net `nn-0000000000a0.nnue` on the same dataset with the ranger21 optimizer and more WDL skipping at training time. More WDL skipping is meant to increase lambda accuracy and train on fewer misevaluated positions where position scores are unlikely to correlate with game outcomes. Inspired by: - repeated reports in discord #events-discuss about SF misplaying due to wrong endgame evals, possibly due to Leela's endgame weaknesses reflected in training data - an attempt to reduce the skewed dataset piece count distribution where there are much more positions with less than 16 pieces, since the target piece count distribution in the trainer is symmetric around 16 The faster convergence seen with ranger21 is meant to: - prune experiment ideas more quickly since fewer epochs are needed to reach elo maxima - research faster potential trainings by shortening each run ```yaml experiment-name: 2560-S7-Re-514G-ranger21-more-wdl-skip training-dataset: /data/S6-514G.binpack early-fen-skipping: 28 start-from-engine-test-net: True nnue-pytorch-branch: linrock/nnue-pytorch/r21-more-wdl-skip num-epochs: 1200 lr: 4.375e-4 gamma: 0.995 start-lambda: 1.0 end-lambda: 0.7 ``` Experiment yaml configs converted to easy_train.sh commands with: https://github.com/linrock/nnue-tools/blob/4339954/yaml_easy_train.py Implementations based off of Sopel's NNUE training & experimentation log: https://docs.google.com/document/d/1gTlrr02qSNKiXNZ_SuO4-RjK4MXBiFlLE6jvNqqMkAY - Experiment 336 - ranger21 https://github.com/Sopel97/nnue-pytorch/tree/experiment_336 - Experiment 351 - more WDL skipping The version of the ranger21 optimizer used is: https://github.com/lessw2020/Ranger21/blob/b507df6/ranger21/ranger21.py The dataset is the exact same as in: https://github.com/official-stockfish/Stockfish/pull/4782 Local elo at 25k nodes per move: nn-epoch619.nnue : 6.2 +/- 4.2 Passed STC: https://tests.stockfishchess.org/tests/view/658a029779aa8af82b94fbe6 LLR: 2.93 (-2.94,2.94) <0.00,2.00> Total: 46528 W: 11985 L: 11650 D: 22893 Ptnml(0-2): 154, 5489, 11688, 5734, 199 Passed LTC: https://tests.stockfishchess.org/tests/view/658a448979aa8af82b95010f LLR: 2.94 (-2.94,2.94) <0.50,2.50> Total: 265326 W: 66378 L: 65574 D: 133374 Ptnml(0-2): 153, 30175, 71254, 30877, 204 This was additionally tested with the latest DualNNUE and passed SPRTs: Passed STC vs. https://github.com/official-stockfish/Stockfish/pull/4919 https://tests.stockfishchess.org/tests/view/658bcd5c79aa8af82b951846 LLR: 2.93 (-2.94,2.94) <0.00,2.00> Total: 296128 W: 76273 L: 75554 D: 144301 Ptnml(0-2): 1223, 35768, 73617, 35979, 1477 Passed LTC vs. https://github.com/official-stockfish/Stockfish/pull/4919 https://tests.stockfishchess.org/tests/view/658c988d79aa8af82b95240f LLR: 2.95 (-2.94,2.94) <0.50,2.50> Total: 75618 W: 19085 L: 18680 D: 37853 Ptnml(0-2): 45, 8420, 20497, 8779, 68 closes https://github.com/official-stockfish/Stockfish/pull/4942 Bench: 1304666
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