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docs: record CPU training results and model performance Documented the training cycle to demonstrate model stability on non-GPU hardware. Added logs showing loss reduction over time.
Co-Authored-By: Code Addict <267558365+codeaddict-119@users.noreply.github.com>
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‎engine/logs/run_20260430_192930.txt‎

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2026-04-30 19:29:30 | Quadtrix-v1.0
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2026-04-30 19:29:30 | Started 2026-04-30 19:29:30
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2026-04-30 19:29:30 | Device CPU
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2026-04-30 19:29:30 | PyTorch 2.4.1+cpu
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2026-04-30 19:29:30 | Log file C:\Users\Admin\Documents\GitHub\Quadtrix.cpp\engine\logs\run_20260430_192930.txt
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2026-04-30 19:29:39 | ==============================================================================
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2026-04-30 19:29:39 | CONFIG
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2026-04-30 19:29:39 | ==============================================================================
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2026-04-30 19:29:39 | Seed 1337
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2026-04-30 19:29:39 | Batch size 16
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2026-04-30 19:29:39 | Block size 32
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2026-04-30 19:29:39 | Learning rate 0.001
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2026-04-30 19:29:39 | Layers 4
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2026-04-30 19:29:39 | Heads 4
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2026-04-30 19:29:39 | Embedding dim 64
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2026-04-30 19:29:39 | Dropout 0.1
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2026-04-30 19:29:39 | Parameters 6,684,497
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2026-04-30 19:29:39 | Train tokens 7,065,137
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2026-04-30 19:29:39 | Val tokens 785,016
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2026-04-30 19:29:39 | Data file C:\Users\Admin\Documents\GitHub\Quadtrix.cpp\engine\input.txt
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2026-04-30 19:29:39 | ==============================================================================
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2026-04-30 19:29:39 | TRAINING
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2026-04-30 19:29:39 | 7,000 steps | eval every 100 | checkpoint on improvement
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2026-04-30 19:29:39 | ==============================================================================
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2026-04-30 19:29:39 | training loop started
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2026-04-30 19:29:45 | ckpt path=best_model.pt val_loss=10.8238 step=0
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2026-04-30 19:29:45 | train step=0/7000 pct=0.0% loss_train=10.8233 loss_val=10.8238 elapsed=0m 06s eta=0m 00s status=best saved
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2026-04-30 19:30:47 | ckpt path=best_model.pt val_loss=5.7438 step=100
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2026-04-30 19:30:47 | train step=100/7000 pct=1.4% loss_train=5.7755 loss_val=5.7438 elapsed=1m 07s eta=77m 21s status=best saved
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2026-04-30 19:31:46 | ckpt path=best_model.pt val_loss=4.9451 step=200
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2026-04-30 19:31:46 | train step=200/7000 pct=2.9% loss_train=4.9093 loss_val=4.9451 elapsed=2m 07s eta=71m 49s status=best saved
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2026-04-30 19:32:47 | ckpt path=best_model.pt val_loss=4.5030 step=300
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2026-04-30 19:32:47 | train step=300/7000 pct=4.3% loss_train=4.3993 loss_val=4.5030 elapsed=3m 08s eta=69m 46s status=best saved
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2026-04-30 19:33:52 | ckpt path=best_model.pt val_loss=4.2862 step=400
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2026-04-30 19:33:52 | train step=400/7000 pct=5.7% loss_train=4.2381 loss_val=4.2862 elapsed=4m 13s eta=69m 32s status=best saved
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2026-04-30 19:35:00 | ckpt path=best_model.pt val_loss=4.1456 step=500
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2026-04-30 19:35:00 | train step=500/7000 pct=7.1% loss_train=4.0901 loss_val=4.1456 elapsed=5m 21s eta=69m 34s status=best saved
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2026-04-30 19:36:09 | ckpt path=best_model.pt val_loss=3.9721 step=600
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2026-04-30 19:36:09 | train step=600/7000 pct=8.6% loss_train=3.9752 loss_val=3.9721 elapsed=6m 30s eta=69m 22s status=best saved
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2026-04-30 19:37:27 | ckpt path=best_model.pt val_loss=3.9280 step=700
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2026-04-30 19:37:27 | train step=700/7000 pct=10.0% loss_train=3.9418 loss_val=3.9280 elapsed=7m 48s eta=70m 13s status=best saved
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2026-04-30 19:38:50 | ckpt path=best_model.pt val_loss=3.8548 step=800
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2026-04-30 19:38:50 | train step=800/7000 pct=11.4% loss_train=3.8513 loss_val=3.8548 elapsed=9m 10s eta=71m 03s status=best saved
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2026-04-30 19:40:08 | ckpt path=best_model.pt val_loss=3.8441 step=900
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2026-04-30 19:40:08 | train step=900/7000 pct=12.9% loss_train=3.7503 loss_val=3.8441 elapsed=10m 29s eta=71m 02s status=best saved
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2026-04-30 19:41:25 | ckpt path=best_model.pt val_loss=3.7018 step=1000
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2026-04-30 19:41:25 | train step=1000/7000 pct=14.3% loss_train=3.7462 loss_val=3.7018 elapsed=11m 46s eta=70m 32s status=best saved
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2026-04-30 19:42:39 | ckpt path=best_model.pt val_loss=3.5920 step=1100
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2026-04-30 19:42:39 | train step=1100/7000 pct=15.7% loss_train=3.6724 loss_val=3.5920 elapsed=13m 00s eta=69m 42s status=best saved
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2026-04-30 19:44:01 | train step=1200/7000 pct=17.1% loss_train=3.6392 loss_val=3.6451 elapsed=14m 22s eta=69m 25s status=-
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2026-04-30 19:45:20 | train step=1300/7000 pct=18.6% loss_train=3.6044 loss_val=3.6304 elapsed=15m 41s eta=68m 42s status=-
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2026-04-30 19:46:37 | ckpt path=best_model.pt val_loss=3.5047 step=1400
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2026-04-30 19:46:37 | train step=1400/7000 pct=20.0% loss_train=3.5971 loss_val=3.5047 elapsed=16m 58s eta=67m 49s status=best saved
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2026-04-30 19:47:57 | ckpt path=best_model.pt val_loss=3.4660 step=1500
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2026-04-30 19:47:57 | train step=1500/7000 pct=21.4% loss_train=3.4871 loss_val=3.4660 elapsed=18m 17s eta=67m 02s status=best saved
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2026-04-30 19:49:20 | ckpt path=best_model.pt val_loss=3.4297 step=1600
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2026-04-30 19:49:20 | train step=1600/7000 pct=22.9% loss_train=3.5589 loss_val=3.4297 elapsed=19m 41s eta=66m 24s status=best saved
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2026-04-30 19:50:38 | train step=1700/7000 pct=24.3% loss_train=3.5427 loss_val=3.5070 elapsed=20m 59s eta=65m 23s status=-
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2026-04-30 19:51:55 | train step=1800/7000 pct=25.7% loss_train=3.4824 loss_val=3.4823 elapsed=22m 16s eta=64m 17s status=-
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2026-04-30 19:53:06 | train step=1900/7000 pct=27.1% loss_train=3.3928 loss_val=3.4742 elapsed=23m 27s eta=62m 54s status=-
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2026-04-30 19:54:14 | ckpt path=best_model.pt val_loss=3.3804 step=2000
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2026-04-30 19:54:14 | train step=2000/7000 pct=28.6% loss_train=3.4062 loss_val=3.3804 elapsed=24m 35s eta=61m 25s status=best saved
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2026-04-30 19:55:34 | train step=2100/7000 pct=30.0% loss_train=3.3721 loss_val=3.4506 elapsed=25m 55s eta=60m 27s status=-
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2026-04-30 19:56:48 | train step=2200/7000 pct=31.4% loss_train=3.3378 loss_val=3.4076 elapsed=27m 09s eta=59m 11s status=-
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2026-04-30 19:58:03 | train step=2300/7000 pct=32.9% loss_train=3.3475 loss_val=3.4132 elapsed=28m 24s eta=58m 00s status=-
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2026-04-30 19:59:18 | ckpt path=best_model.pt val_loss=3.3732 step=2400
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2026-04-30 19:59:18 | train step=2400/7000 pct=34.3% loss_train=3.3894 loss_val=3.3732 elapsed=29m 39s eta=56m 47s status=best saved
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2026-04-30 20:00:31 | train step=2500/7000 pct=35.7% loss_train=3.3044 loss_val=3.3861 elapsed=30m 52s eta=55m 31s status=-
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2026-04-30 20:01:46 | ckpt path=best_model.pt val_loss=3.3189 step=2600
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2026-04-30 20:01:46 | train step=2600/7000 pct=37.1% loss_train=3.3413 loss_val=3.3189 elapsed=32m 07s eta=54m 20s status=best saved
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2026-04-30 20:03:03 | train step=2700/7000 pct=38.6% loss_train=3.2925 loss_val=3.3664 elapsed=33m 24s eta=53m 10s status=-
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2026-04-30 20:04:17 | ckpt path=best_model.pt val_loss=3.2500 step=2800
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2026-04-30 20:04:17 | train step=2800/7000 pct=40.0% loss_train=3.3272 loss_val=3.2500 elapsed=34m 38s eta=51m 56s status=best saved
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2026-04-30 20:05:30 | train step=2900/7000 pct=41.4% loss_train=3.2794 loss_val=3.2847 elapsed=35m 51s eta=50m 39s status=-
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2026-04-30 20:06:58 | ckpt path=best_model.pt val_loss=3.1849 step=3000
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2026-04-30 20:06:58 | train step=3000/7000 pct=42.9% loss_train=3.2633 loss_val=3.1849 elapsed=37m 19s eta=49m 44s status=best saved
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2026-04-30 20:08:27 | train step=3100/7000 pct=44.3% loss_train=3.2404 loss_val=3.3068 elapsed=38m 48s eta=48m 47s status=-
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2026-04-30 20:09:54 | train step=3200/7000 pct=45.7% loss_train=3.2644 loss_val=3.2376 elapsed=40m 15s eta=47m 46s status=-
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2026-04-30 20:11:18 | train step=3300/7000 pct=47.1% loss_train=3.2435 loss_val=3.2862 elapsed=41m 39s eta=46m 40s status=-
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2026-04-30 20:12:41 | train step=3400/7000 pct=48.6% loss_train=3.1706 loss_val=3.2951 elapsed=43m 02s eta=45m 32s status=-
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2026-04-30 20:13:57 | train step=3500/7000 pct=50.0% loss_train=3.2166 loss_val=3.2736 elapsed=44m 18s eta=44m 16s status=-
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2026-04-30 20:15:14 | train step=3600/7000 pct=51.4% loss_train=3.2782 loss_val=3.2490 elapsed=45m 35s eta=43m 01s status=-
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2026-04-30 20:16:38 | train step=3700/7000 pct=52.9% loss_train=3.2321 loss_val=3.2208 elapsed=46m 59s eta=41m 53s status=-
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2026-04-30 20:17:57 | ckpt path=best_model.pt val_loss=3.1496 step=3800
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2026-04-30 20:17:57 | train step=3800/7000 pct=54.3% loss_train=3.1839 loss_val=3.1496 elapsed=48m 18s eta=40m 39s status=best saved
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2026-04-30 20:19:25 | train step=3900/7000 pct=55.7% loss_train=3.1430 loss_val=3.2825 elapsed=49m 46s eta=39m 32s status=-
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2026-04-30 20:20:46 | train step=4000/7000 pct=57.1% loss_train=3.2546 loss_val=3.1651 elapsed=51m 07s eta=38m 19s status=-
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2026-04-30 20:21:54 | train step=4100/7000 pct=58.6% loss_train=3.1621 loss_val=3.1864 elapsed=52m 15s eta=36m 56s status=-
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2026-04-30 20:22:58 | train step=4200/7000 pct=60.0% loss_train=3.1486 loss_val=3.1607 elapsed=53m 19s eta=35m 31s status=-
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2026-04-30 20:24:03 | train step=4300/7000 pct=61.4% loss_train=3.1192 loss_val=3.1643 elapsed=54m 24s eta=34m 08s status=-
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2026-04-30 20:25:07 | train step=4400/7000 pct=62.9% loss_train=3.2042 loss_val=3.1593 elapsed=55m 28s eta=32m 45s status=-
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2026-04-30 20:26:15 | ckpt path=best_model.pt val_loss=3.1335 step=4500
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2026-04-30 20:26:15 | train step=4500/7000 pct=64.3% loss_train=3.1156 loss_val=3.1335 elapsed=56m 36s eta=31m 25s status=best saved
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2026-04-30 20:27:21 | ckpt path=best_model.pt val_loss=3.0975 step=4600
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2026-04-30 20:27:21 | train step=4600/7000 pct=65.7% loss_train=3.2056 loss_val=3.0975 elapsed=57m 42s eta=30m 05s status=best saved
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2026-04-30 20:28:24 | train step=4700/7000 pct=67.1% loss_train=3.1233 loss_val=3.2438 elapsed=58m 45s eta=28m 44s status=-
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2026-04-30 20:29:28 | train step=4800/7000 pct=68.6% loss_train=3.1778 loss_val=3.1305 elapsed=59m 49s eta=27m 24s status=-
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2026-04-30 20:30:32 | train step=4900/7000 pct=70.0% loss_train=3.1667 loss_val=3.1229 elapsed=60m 53s eta=26m 04s status=-
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2026-04-30 20:31:36 | train step=5000/7000 pct=71.4% loss_train=3.1886 loss_val=3.1594 elapsed=61m 57s eta=24m 45s status=-
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2026-04-30 20:32:39 | train step=5100/7000 pct=72.9% loss_train=3.0988 loss_val=3.1757 elapsed=63m 00s eta=23m 27s status=-
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2026-04-30 20:33:43 | train step=5200/7000 pct=74.3% loss_train=3.1207 loss_val=3.2528 elapsed=64m 04s eta=22m 09s status=-
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2026-04-30 20:34:47 | ckpt path=best_model.pt val_loss=3.0602 step=5300
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2026-04-30 20:34:47 | train step=5300/7000 pct=75.7% loss_train=3.1062 loss_val=3.0602 elapsed=65m 08s eta=20m 52s status=best saved
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2026-04-30 20:35:52 | train step=5400/7000 pct=77.1% loss_train=3.1379 loss_val=3.0691 elapsed=66m 13s eta=19m 36s status=-
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2026-04-30 20:36:57 | train step=5500/7000 pct=78.6% loss_train=3.1076 loss_val=3.1093 elapsed=67m 18s eta=18m 20s status=-
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2026-04-30 20:38:03 | train step=5600/7000 pct=80.0% loss_train=3.1042 loss_val=3.0680 elapsed=68m 24s eta=17m 05s status=-
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2026-04-30 20:39:10 | train step=5700/7000 pct=81.4% loss_train=3.0513 loss_val=3.1711 elapsed=69m 31s eta=15m 50s status=-
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2026-04-30 20:40:15 | train step=5800/7000 pct=82.9% loss_train=3.0684 loss_val=3.1179 elapsed=70m 36s eta=14m 35s status=-
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2026-04-30 20:41:19 | ckpt path=best_model.pt val_loss=3.0557 step=5900
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2026-04-30 20:41:19 | train step=5900/7000 pct=84.3% loss_train=3.0846 loss_val=3.0557 elapsed=71m 40s eta=13m 20s status=best saved
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2026-04-30 20:42:23 | train step=6000/7000 pct=85.7% loss_train=3.1279 loss_val=3.1223 elapsed=72m 44s eta=12m 06s status=-
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2026-04-30 20:43:31 | ckpt path=best_model.pt val_loss=3.0485 step=6100
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2026-04-30 20:43:31 | train step=6100/7000 pct=87.1% loss_train=3.1061 loss_val=3.0485 elapsed=73m 52s eta=10m 53s status=best saved
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2026-04-30 20:44:51 | train step=6200/7000 pct=88.6% loss_train=3.1426 loss_val=3.0637 elapsed=75m 12s eta=9m 41s status=-
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2026-04-30 20:46:14 | train step=6300/7000 pct=90.0% loss_train=3.1334 loss_val=3.0827 elapsed=76m 35s eta=8m 29s status=-
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2026-04-30 20:47:41 | ckpt path=best_model.pt val_loss=3.0063 step=6400
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2026-04-30 20:47:41 | train step=6400/7000 pct=91.4% loss_train=3.0994 loss_val=3.0063 elapsed=78m 01s eta=7m 18s status=best saved
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2026-04-30 20:49:05 | train step=6500/7000 pct=92.9% loss_train=3.0637 loss_val=3.0298 elapsed=79m 26s eta=6m 05s status=-
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2026-04-30 20:50:26 | train step=6600/7000 pct=94.3% loss_train=3.0470 loss_val=3.0918 elapsed=80m 47s eta=4m 53s status=-
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2026-04-30 20:51:48 | train step=6700/7000 pct=95.7% loss_train=3.0393 loss_val=3.1039 elapsed=82m 09s eta=3m 39s status=-
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2026-04-30 20:53:12 | ckpt path=best_model.pt val_loss=2.9971 step=6800
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2026-04-30 20:53:12 | train step=6800/7000 pct=97.1% loss_train=3.0649 loss_val=2.9971 elapsed=83m 33s eta=2m 26s status=best saved
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2026-04-30 20:54:37 | train step=6900/7000 pct=98.6% loss_train=3.0809 loss_val=3.0698 elapsed=84m 58s eta=1m 13s status=-
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2026-04-30 20:56:05 | train step=6999/7000 pct=100.0% loss_train=2.9927 loss_val=3.0494 elapsed=86m 26s eta=0m 00s status=-
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2026-04-30 20:56:07 | ------------------------------------------------------------------------------
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2026-04-30 20:56:07 | Duration 86m 28s
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2026-04-30 20:56:07 | Best val loss 2.9971 best
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2026-04-30 20:56:07 | Checkpoint best_model.pt best
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2026-04-30 20:56:07 | ------------------------------------------------------------------------------
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2026-04-30 20:56:07 | ok Restored best_model.pt | val loss 2.9971
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2026-04-30 20:56:07 | ==============================================================================
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2026-04-30 20:56:07 | INFERENCE
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2026-04-30 20:56:07 | quit / exit / q -> end session
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2026-04-30 20:56:07 | ==============================================================================
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2026-04-30 20:58:55 | ok Interrupted.
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2026-04-30 20:58:55 | ------------------------------------------------------------------------------
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2026-04-30 20:58:55 | Training 86m 28s
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2026-04-30 20:58:55 | Total 89m 24s best
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2026-04-30 20:58:55 | ------------------------------------------------------------------------------
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2026-04-30 20:58:55 | ==============================================================================
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