Stockfish 2023060619 NNUE for Windows and Linux, interesting compiled by Linmiao Xu Elo (Elo +2.04)

Stockfish 2023060619 - UCI chess engine, compiled by Linmiao Xu
Rating CEDR=3732

Date: Tue Jun 6 21:17:36 2023 +0200

Timestamp: 1686079056

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 Elo +2.00

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 Elo +2.04

Ptnml(0-2): 44, 5607, 17748, 5962, 39

closes https://github.com/official-stockfish/Stockfish/pull/4606

bench 2141197

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