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  Update default main net to nn-b1a57edbea57.nnue Febuary 17th (SF The gift that keeps on giving

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LondonFrau
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  Update default main net to nn-b1a57edbea57.nnue   Febuary 17th  (SF The gift that keeps on giving Empty
PostSubject: Update default main net to nn-b1a57edbea57.nnue Febuary 17th (SF The gift that keeps on giving     Update default main net to nn-b1a57edbea57.nnue   Febuary 17th  (SF The gift that keeps on giving EmptyTue Feb 20, 2024 2:41 am

Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: Linmiao Xu
Date: Sat Feb 17 17:11:46 2024 +0100
Timestamp: 1708186306

Update default main net to nn-b1a57edbea57.nnue

Created by retraining the previous main net `nn-baff1edbea57.nnue` with:
- some of the same options as before: ranger21, more WDL skipping
- the addition of T80 nov+dec 2023 data
- increasing loss by 15% when prediction is too high, up from 10%
- use of torch.compile to speed up training by over 25%

```yaml
experiment-name: 2560--S9-514G-T80-augtodec2023-more-wdl-skip-15p-more-loss-high-q-sk28

training-dataset:
# https://github.com/official-stockfish/Stockfish/pull/4782
- /data/S6-514G-1ee1aba5ed.binpack
- /data/test80-aug2023-2tb7p.v6.min.binpack
- /data/test80-sep2023-2tb7p.binpack
- /data/test80-oct2023-2tb7p.binpack
- /data/test80-nov2023-2tb7p.binpack
- /data/test80-dec2023-2tb7p.binpack
early-fen-skipping: 28

start-from-engine-test-net: True
nnue-pytorch-branch: linrock/nnue-pytorch/r21-more-wdl-skip-15p-more-loss-high-q-torch-compile

num-epochs: 1000
lr: 4.375e-4
gamma: 0.995
start-lambda: 1.0
end-lambda: 0.7
```

Epoch 819 trained with the above config led to this PR. Use of torch.compile
decorators in nnue-pytorch model.py was found to speed up training by at least
25% on Ampere gpus when using recent pytorch compiled with cuda 12:
https://catalog.ngc.nvidia.com/orgs/nvidia/containers/pytorch

See recent main net PRs for more info on
- ranger21 and more WDL skipping: https://github.com/official-stockfish/Stockfish/pull/4942
- increasing loss when Q is too high: https://github.com/official-stockfish/Stockfish/pull/4972

Training data can be found at:
https://robotmoon.com/nnue-training-data/

Passed STC:
https://tests.stockfishchess.org/tests/view/65cd76151d8e83c78bfd2f52
LLR: 2.98 (-2.94,2.94) <0.00,2.00>
Total: 78336 W: 20504 L: 20115 D: 37717 Elo +1.73
Ptnml(0-2): 317, 9225, 19721, 9562, 343

Passed LTC:
https://tests.stockfishchess.org/tests/view/65ce5be61d8e83c78bfd43e9
LLR: 2.95 (-2.94,2.94) <0.50,2.50>
Total: 41016 W: 10492 L: 10159 D: 20365 Elo +2.82
Ptnml(0-2): 22, 4533, 11071, 4854, 28

closes https://github.com/official-stockfish/Stockfish/pull/5056

Bench: 1351997
see source

_________________
Bettina...............The greatest happiness of life is the conviction that we are loved.

Victor Hugo

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