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+ [2025-10-29 12:45:31] Experiment directory created at results/stage2/hfdata/lightningdit-xl-dinov2-vit-b-spnorm-bf16
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+ [2025-10-29 12:45:33] using MLP layer as FFN
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+ [2025-10-29 12:45:50] Model Parameters: 1202.04M
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+ [2025-10-29 12:45:53] Dataset contains 1,281,167 images (/scratch/xingjian.leng/data/train)
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+ [2025-10-29 12:45:53] Gradient accumulation: steps=1, micro batch=128, per-GPU batch=128, global batch=1024
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+ [2025-10-29 12:45:53] Precision mode: bf16
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+ [2025-10-29 12:45:53] Training configured for 80 epochs, 1251 steps per epoch.
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+ [2025-10-29 12:45:53] Optimizer: ADAMW with lr=0.0002, betas=(0.9, 0.95), weight_decay=0.0, eps=1e-08
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+ Scheduler: linear with warmup_steps=0, decay_end_steps=0, final_lr=0.0002
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+ [2025-10-29 12:45:53] Training for 80 epochs...
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+ [2025-10-29 12:45:53] Beginning epoch 0...
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+ [2025-10-29 13:34:00] Experiment directory created at results/stage2/hfdata/lightningdit-xl-dinov2-vit-b-spnorm-bf16
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+ [2025-10-29 13:34:03] using MLP layer as FFN
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+ [2025-10-29 13:34:19] Model Parameters: 1202.04M
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+ [2025-10-29 13:34:23] Dataset contains 1,281,167 images (/scratch/xingjian.leng/data/train)
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+ [2025-10-29 13:34:23] Gradient accumulation: steps=1, micro batch=128, per-GPU batch=128, global batch=1024
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+ [2025-10-29 13:34:23] Precision mode: bf16
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+ [2025-10-29 13:34:23] Training configured for 80 epochs, 1251 steps per epoch.
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+ [2025-10-29 13:34:23] Optimizer: ADAMW with lr=0.0002, betas=(0.9, 0.95), weight_decay=0.0, eps=1e-08
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+ Scheduler: linear with warmup_steps=0, decay_end_steps=0, final_lr=0.0002
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+ [2025-10-29 13:34:23] Training for 80 epochs...
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+ [2025-10-29 13:34:23] Beginning epoch 0...
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+ [2025-10-29 13:34:28] Generating EMA samples...
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+ [2025-10-29 13:34:57] Generating EMA samples done.
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+ [2025-10-29 13:36:16] (step=0000100) Train Loss: 1.5578, Train Steps/Sec: 0.88
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+ [2025-10-29 13:37:38] (step=0000200) Train Loss: 1.3409, Train Steps/Sec: 1.23
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+ [2025-10-29 13:38:59] (step=0000300) Train Loss: 1.2296, Train Steps/Sec: 1.23
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+ [2025-10-29 13:40:21] (step=0000400) Train Loss: 1.1006, Train Steps/Sec: 1.23
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+ [2025-10-29 13:41:42] (step=0000500) Train Loss: 1.0210, Train Steps/Sec: 1.23
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+ [2025-10-29 13:43:04] (step=0000600) Train Loss: 0.9725, Train Steps/Sec: 1.23
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+ [2025-10-29 13:44:25] (step=0000700) Train Loss: 0.9370, Train Steps/Sec: 1.22
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+ [2025-10-29 13:45:47] (step=0000800) Train Loss: 0.9114, Train Steps/Sec: 1.23
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+ [2025-10-29 13:47:08] (step=0000900) Train Loss: 0.8913, Train Steps/Sec: 1.23
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+ [2025-10-29 13:48:30] (step=0001000) Train Loss: 0.8737, Train Steps/Sec: 1.22
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+ [2025-10-29 13:49:52] (step=0001100) Train Loss: 0.8584, Train Steps/Sec: 1.23
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+ [2025-10-29 13:51:13] (step=0001200) Train Loss: 0.8452, Train Steps/Sec: 1.23
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+ [2025-10-29 13:51:55] Beginning epoch 1...
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+ [2025-10-29 13:52:37] (step=0001300) Train Loss: 0.8344, Train Steps/Sec: 1.19
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+ [2025-10-29 13:53:59] (step=0001400) Train Loss: 0.8252, Train Steps/Sec: 1.23
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+ [2025-10-29 13:55:20] (step=0001500) Train Loss: 0.8152, Train Steps/Sec: 1.23
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+ [2025-10-29 13:56:42] (step=0001600) Train Loss: 0.8079, Train Steps/Sec: 1.23
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+ [2025-10-29 13:58:03] (step=0001700) Train Loss: 0.8022, Train Steps/Sec: 1.23
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+ [2025-10-29 13:59:25] (step=0001800) Train Loss: 0.7955, Train Steps/Sec: 1.23
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+ [2025-10-29 14:00:47] (step=0001900) Train Loss: 0.7895, Train Steps/Sec: 1.23
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+ [2025-10-29 14:02:08] (step=0002000) Train Loss: 0.7850, Train Steps/Sec: 1.23
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+ [2025-10-29 14:03:30] (step=0002100) Train Loss: 0.7789, Train Steps/Sec: 1.22
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+ [2025-10-29 14:04:51] (step=0002200) Train Loss: 0.7756, Train Steps/Sec: 1.23
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+ [2025-10-29 14:06:13] (step=0002300) Train Loss: 0.7714, Train Steps/Sec: 1.23
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+ [2025-10-29 14:07:34] (step=0002400) Train Loss: 0.7682, Train Steps/Sec: 1.23
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+ [2025-10-29 14:08:56] (step=0002500) Train Loss: 0.7638, Train Steps/Sec: 1.23
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+ [2025-10-29 14:08:58] Beginning epoch 2...
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+ [2025-10-29 14:10:21] (step=0002600) Train Loss: 0.7593, Train Steps/Sec: 1.18
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+ [2025-10-29 14:11:42] (step=0002700) Train Loss: 0.7569, Train Steps/Sec: 1.23
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+ [2025-10-29 14:13:04] (step=0002800) Train Loss: 0.7557, Train Steps/Sec: 1.23
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+ [2025-10-29 14:14:25] (step=0002900) Train Loss: 0.7527, Train Steps/Sec: 1.23
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+ [2025-10-29 14:15:47] (step=0003000) Train Loss: 0.7487, Train Steps/Sec: 1.23
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+ [2025-10-29 14:17:08] (step=0003100) Train Loss: 0.7476, Train Steps/Sec: 1.23
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+ [2025-10-29 14:18:30] (step=0003200) Train Loss: 0.7448, Train Steps/Sec: 1.23
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+ [2025-10-29 14:19:51] (step=0003300) Train Loss: 0.7429, Train Steps/Sec: 1.23
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+ [2025-10-29 14:21:13] (step=0003400) Train Loss: 0.7398, Train Steps/Sec: 1.23
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+ [2025-10-29 14:22:35] (step=0003500) Train Loss: 0.7391, Train Steps/Sec: 1.22
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+ [2025-10-29 14:23:56] (step=0003600) Train Loss: 0.7363, Train Steps/Sec: 1.23
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+ [2025-10-29 14:25:18] (step=0003700) Train Loss: 0.7352, Train Steps/Sec: 1.23
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+ [2025-10-29 14:26:02] Beginning epoch 3...
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+ [2025-10-29 14:26:42] (step=0003800) Train Loss: 0.7329, Train Steps/Sec: 1.19
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+ [2025-10-29 14:28:04] (step=0003900) Train Loss: 0.7303, Train Steps/Sec: 1.23
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+ [2025-10-29 14:29:25] (step=0004000) Train Loss: 0.7298, Train Steps/Sec: 1.23
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+ [2025-10-29 14:30:47] (step=0004100) Train Loss: 0.7292, Train Steps/Sec: 1.23
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+ [2025-10-29 14:32:08] (step=0004200) Train Loss: 0.7269, Train Steps/Sec: 1.23
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+ [2025-10-29 14:33:30] (step=0004300) Train Loss: 0.7250, Train Steps/Sec: 1.22
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+ [2025-10-29 14:34:52] (step=0004400) Train Loss: 0.7230, Train Steps/Sec: 1.23
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+ [2025-10-29 14:36:14] (step=0004500) Train Loss: 0.7228, Train Steps/Sec: 1.23
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+ [2025-10-29 14:37:35] (step=0004600) Train Loss: 0.7212, Train Steps/Sec: 1.23
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+ [2025-10-29 14:38:57] (step=0004700) Train Loss: 0.7205, Train Steps/Sec: 1.23
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+ [2025-10-29 14:40:18] (step=0004800) Train Loss: 0.7184, Train Steps/Sec: 1.23
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+ [2025-10-29 14:41:40] (step=0004900) Train Loss: 0.7168, Train Steps/Sec: 1.22
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+ [2025-10-29 14:43:02] (step=0005000) Train Loss: 0.7164, Train Steps/Sec: 1.23
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+ [2025-10-29 14:43:05] Beginning epoch 4...
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+ [2025-10-29 14:44:25] (step=0005100) Train Loss: 0.7141, Train Steps/Sec: 1.19
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+ [2025-10-29 14:45:47] (step=0005200) Train Loss: 0.7143, Train Steps/Sec: 1.23
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+ [2025-10-29 14:47:09] (step=0005300) Train Loss: 0.7137, Train Steps/Sec: 1.23
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+ [2025-10-29 14:48:30] (step=0005400) Train Loss: 0.7111, Train Steps/Sec: 1.23
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+ [2025-10-29 14:49:52] (step=0005500) Train Loss: 0.7103, Train Steps/Sec: 1.23
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+ [2025-10-29 14:51:13] (step=0005600) Train Loss: 0.7097, Train Steps/Sec: 1.23
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+ [2025-10-29 14:52:35] (step=0005700) Train Loss: 0.7081, Train Steps/Sec: 1.23
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+ [2025-10-29 14:53:56] (step=0005800) Train Loss: 0.7089, Train Steps/Sec: 1.23
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+ [2025-10-29 14:55:18] (step=0005900) Train Loss: 0.7071, Train Steps/Sec: 1.23
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+ [2025-10-29 14:56:40] (step=0006000) Train Loss: 0.7061, Train Steps/Sec: 1.22
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+ [2025-10-29 14:58:02] (step=0006100) Train Loss: 0.7053, Train Steps/Sec: 1.23
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+ [2025-10-29 14:59:23] (step=0006200) Train Loss: 0.7042, Train Steps/Sec: 1.23
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+ [2025-10-29 15:00:08] Beginning epoch 5...
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+ [2025-10-29 15:00:47] (step=0006300) Train Loss: 0.7039, Train Steps/Sec: 1.19
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+ [2025-10-29 15:02:09] (step=0006400) Train Loss: 0.7018, Train Steps/Sec: 1.23
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+ [2025-10-29 15:03:30] (step=0006500) Train Loss: 0.7000, Train Steps/Sec: 1.23
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+ [2025-10-29 15:04:52] (step=0006600) Train Loss: 0.7007, Train Steps/Sec: 1.23
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+ [2025-10-29 15:06:13] (step=0006700) Train Loss: 0.6998, Train Steps/Sec: 1.23
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+ [2025-10-29 15:07:35] (step=0006800) Train Loss: 0.6983, Train Steps/Sec: 1.23
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+ [2025-10-29 15:08:56] (step=0006900) Train Loss: 0.6984, Train Steps/Sec: 1.23
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+ [2025-10-29 15:10:18] (step=0007000) Train Loss: 0.6983, Train Steps/Sec: 1.23
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+ [2025-10-29 15:11:39] (step=0007100) Train Loss: 0.6974, Train Steps/Sec: 1.23
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+ [2025-10-29 15:13:01] (step=0007200) Train Loss: 0.6968, Train Steps/Sec: 1.23
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+ [2025-10-29 15:14:23] (step=0007300) Train Loss: 0.6942, Train Steps/Sec: 1.23
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+ [2025-10-29 15:15:44] (step=0007400) Train Loss: 0.6956, Train Steps/Sec: 1.23
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+ [2025-10-29 15:17:06] (step=0007500) Train Loss: 0.6939, Train Steps/Sec: 1.23
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+ [2025-10-29 15:17:11] Beginning epoch 6...
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+ [2025-10-29 15:18:30] (step=0007600) Train Loss: 0.6931, Train Steps/Sec: 1.19
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+ [2025-10-29 15:19:52] (step=0007700) Train Loss: 0.6929, Train Steps/Sec: 1.22
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+ [2025-10-29 15:21:13] (step=0007800) Train Loss: 0.6926, Train Steps/Sec: 1.23
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+ [2025-10-29 15:22:35] (step=0007900) Train Loss: 0.6928, Train Steps/Sec: 1.23
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+ [2025-10-29 15:23:56] (step=0008000) Train Loss: 0.6915, Train Steps/Sec: 1.23
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+ [2025-10-29 15:25:18] (step=0008100) Train Loss: 0.6900, Train Steps/Sec: 1.23
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+ [2025-10-29 15:26:40] (step=0008200) Train Loss: 0.6891, Train Steps/Sec: 1.23
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+ [2025-10-29 15:28:01] (step=0008300) Train Loss: 0.6890, Train Steps/Sec: 1.23
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+ [2025-10-29 15:29:23] (step=0008400) Train Loss: 0.6879, Train Steps/Sec: 1.23
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+ [2025-10-29 15:30:44] (step=0008500) Train Loss: 0.6877, Train Steps/Sec: 1.23
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+ [2025-10-29 15:32:06] (step=0008600) Train Loss: 0.6874, Train Steps/Sec: 1.23
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+ [2025-10-29 15:33:27] (step=0008700) Train Loss: 0.6875, Train Steps/Sec: 1.23
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+ [2025-10-29 15:34:14] Beginning epoch 7...
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+ [2025-10-29 15:34:51] (step=0008800) Train Loss: 0.6867, Train Steps/Sec: 1.19
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+ [2025-10-29 15:36:13] (step=0008900) Train Loss: 0.6851, Train Steps/Sec: 1.23
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+ [2025-10-29 15:37:34] (step=0009000) Train Loss: 0.6839, Train Steps/Sec: 1.23
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+ [2025-10-29 15:38:56] (step=0009100) Train Loss: 0.6849, Train Steps/Sec: 1.23
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+ [2025-10-29 15:40:18] (step=0009200) Train Loss: 0.6850, Train Steps/Sec: 1.22
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+ [2025-10-29 15:41:40] (step=0009300) Train Loss: 0.6840, Train Steps/Sec: 1.21
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+ [2025-10-29 15:43:02] (step=0009400) Train Loss: 0.6843, Train Steps/Sec: 1.23
126
+ [2025-10-29 15:44:23] (step=0009500) Train Loss: 0.6821, Train Steps/Sec: 1.23
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+ [2025-10-29 15:45:45] (step=0009600) Train Loss: 0.6814, Train Steps/Sec: 1.23
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+ [2025-10-29 15:47:06] (step=0009700) Train Loss: 0.6825, Train Steps/Sec: 1.23
129
+ [2025-10-29 15:48:28] (step=0009800) Train Loss: 0.6809, Train Steps/Sec: 1.23
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+ [2025-10-29 15:49:49] (step=0009900) Train Loss: 0.6809, Train Steps/Sec: 1.23
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+ [2025-10-29 15:51:11] (step=0010000) Train Loss: 0.6798, Train Steps/Sec: 1.23
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+ [2025-10-29 15:51:18] Beginning epoch 8...
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+ [2025-10-29 15:52:35] (step=0010100) Train Loss: 0.6788, Train Steps/Sec: 1.19
134
+ [2025-10-29 15:53:57] (step=0010200) Train Loss: 0.6787, Train Steps/Sec: 1.23
135
+ [2025-10-29 15:55:18] (step=0010300) Train Loss: 0.6778, Train Steps/Sec: 1.23
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+ [2025-10-29 15:56:40] (step=0010400) Train Loss: 0.6791, Train Steps/Sec: 1.23
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+ [2025-10-29 15:58:01] (step=0010500) Train Loss: 0.6768, Train Steps/Sec: 1.23
138
+ [2025-10-29 15:59:23] (step=0010600) Train Loss: 0.6769, Train Steps/Sec: 1.22
139
+ [2025-10-29 16:00:44] (step=0010700) Train Loss: 0.6754, Train Steps/Sec: 1.23
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+ [2025-10-29 16:02:06] (step=0010800) Train Loss: 0.6761, Train Steps/Sec: 1.23
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+ [2025-10-29 16:03:28] (step=0010900) Train Loss: 0.6763, Train Steps/Sec: 1.23
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+ [2025-10-29 16:04:50] (step=0011000) Train Loss: 0.6751, Train Steps/Sec: 1.21
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+ [2025-10-29 16:06:12] (step=0011100) Train Loss: 0.6753, Train Steps/Sec: 1.23
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+ [2025-10-29 16:07:33] (step=0011200) Train Loss: 0.6760, Train Steps/Sec: 1.23
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+ [2025-10-29 16:08:22] Beginning epoch 9...
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+ [2025-10-29 16:08:57] (step=0011300) Train Loss: 0.6740, Train Steps/Sec: 1.19
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+ [2025-10-29 16:10:19] (step=0011400) Train Loss: 0.6743, Train Steps/Sec: 1.23
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+ [2025-10-29 16:11:40] (step=0011500) Train Loss: 0.6729, Train Steps/Sec: 1.23
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+ [2025-10-29 16:13:02] (step=0011600) Train Loss: 0.6722, Train Steps/Sec: 1.23
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+ [2025-10-29 16:14:23] (step=0011700) Train Loss: 0.6734, Train Steps/Sec: 1.23
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+ [2025-10-29 16:15:45] (step=0011800) Train Loss: 0.6720, Train Steps/Sec: 1.23
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+ [2025-10-29 16:17:06] (step=0011900) Train Loss: 0.6726, Train Steps/Sec: 1.23
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+ [2025-10-29 16:18:28] (step=0012000) Train Loss: 0.6708, Train Steps/Sec: 1.22
154
+ [2025-10-29 16:19:50] (step=0012100) Train Loss: 0.6709, Train Steps/Sec: 1.23
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+ [2025-10-29 16:21:11] (step=0012200) Train Loss: 0.6708, Train Steps/Sec: 1.23
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+ [2025-10-29 16:22:33] (step=0012300) Train Loss: 0.6692, Train Steps/Sec: 1.23
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+ [2025-10-29 16:23:54] (step=0012400) Train Loss: 0.6691, Train Steps/Sec: 1.23
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+ [2025-10-29 16:25:16] (step=0012500) Train Loss: 0.6697, Train Steps/Sec: 1.23
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+ [2025-10-29 16:25:24] Beginning epoch 10...
160
+ [2025-10-29 16:26:40] (step=0012600) Train Loss: 0.6676, Train Steps/Sec: 1.19
161
+ [2025-10-29 16:28:02] (step=0012700) Train Loss: 0.6686, Train Steps/Sec: 1.21
162
+ [2025-10-29 16:29:23] (step=0012800) Train Loss: 0.6688, Train Steps/Sec: 1.23
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+ [2025-10-29 16:30:45] (step=0012900) Train Loss: 0.6676, Train Steps/Sec: 1.23
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+ [2025-10-29 16:32:07] (step=0013000) Train Loss: 0.6664, Train Steps/Sec: 1.23
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+ [2025-10-29 16:33:28] (step=0013100) Train Loss: 0.6676, Train Steps/Sec: 1.23
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+ [2025-10-29 16:34:50] (step=0013200) Train Loss: 0.6675, Train Steps/Sec: 1.23
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+ [2025-10-29 16:36:11] (step=0013300) Train Loss: 0.6676, Train Steps/Sec: 1.23
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+ [2025-10-29 16:37:33] (step=0013400) Train Loss: 0.6664, Train Steps/Sec: 1.22
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+ [2025-10-29 16:38:54] (step=0013500) Train Loss: 0.6660, Train Steps/Sec: 1.23
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+ [2025-10-29 16:40:16] (step=0013600) Train Loss: 0.6643, Train Steps/Sec: 1.23
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+ [2025-10-29 16:41:37] (step=0013700) Train Loss: 0.6656, Train Steps/Sec: 1.23
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+ [2025-10-29 16:42:28] Beginning epoch 11...
173
+ [2025-10-29 16:43:01] (step=0013800) Train Loss: 0.6642, Train Steps/Sec: 1.19
174
+ [2025-10-29 16:44:23] (step=0013900) Train Loss: 0.6642, Train Steps/Sec: 1.23
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+ [2025-10-29 16:45:44] (step=0014000) Train Loss: 0.6628, Train Steps/Sec: 1.23
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+ [2025-10-29 16:47:06] (step=0014100) Train Loss: 0.6645, Train Steps/Sec: 1.23
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+ [2025-10-29 16:48:27] (step=0014200) Train Loss: 0.6642, Train Steps/Sec: 1.23
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+ [2025-10-29 16:49:50] (step=0014300) Train Loss: 0.6625, Train Steps/Sec: 1.22
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+ [2025-10-29 16:51:12] (step=0014400) Train Loss: 0.6618, Train Steps/Sec: 1.22
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+ [2025-10-29 16:52:33] (step=0014500) Train Loss: 0.6610, Train Steps/Sec: 1.23
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+ [2025-10-29 16:53:55] (step=0014600) Train Loss: 0.6615, Train Steps/Sec: 1.23
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+ [2025-10-29 16:55:16] (step=0014700) Train Loss: 0.6626, Train Steps/Sec: 1.23
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+ [2025-10-29 16:56:38] (step=0014800) Train Loss: 0.6609, Train Steps/Sec: 1.23
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+ [2025-10-29 16:57:59] (step=0014900) Train Loss: 0.6596, Train Steps/Sec: 1.23
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+ [2025-10-29 16:59:21] (step=0015000) Train Loss: 0.6619, Train Steps/Sec: 1.23
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+ [2025-10-29 16:59:31] Beginning epoch 12...
187
+ [2025-10-29 17:00:45] (step=0015100) Train Loss: 0.6600, Train Steps/Sec: 1.19
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+ [2025-10-29 17:02:06] (step=0015200) Train Loss: 0.6580, Train Steps/Sec: 1.23
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+ [2025-10-29 17:03:28] (step=0015300) Train Loss: 0.6602, Train Steps/Sec: 1.23
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+ [2025-10-29 17:04:49] (step=0015400) Train Loss: 0.6600, Train Steps/Sec: 1.23
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+ [2025-10-29 17:06:11] (step=0015500) Train Loss: 0.6595, Train Steps/Sec: 1.23
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+ [2025-10-29 17:07:32] (step=0015600) Train Loss: 0.6588, Train Steps/Sec: 1.23
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+ [2025-10-29 17:08:54] (step=0015700) Train Loss: 0.6584, Train Steps/Sec: 1.23
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+ [2025-10-29 17:10:16] (step=0015800) Train Loss: 0.6587, Train Steps/Sec: 1.23
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+ [2025-10-29 17:11:37] (step=0015900) Train Loss: 0.6574, Train Steps/Sec: 1.23
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+ [2025-10-29 17:12:59] (step=0016000) Train Loss: 0.6576, Train Steps/Sec: 1.21
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+ [2025-10-29 17:14:21] (step=0016100) Train Loss: 0.6586, Train Steps/Sec: 1.23
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+ [2025-10-29 17:15:43] (step=0016200) Train Loss: 0.6575, Train Steps/Sec: 1.22
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+ [2025-10-29 17:16:34] Beginning epoch 13...
200
+ [2025-10-29 17:17:06] (step=0016300) Train Loss: 0.6556, Train Steps/Sec: 1.19
201
+ [2025-10-29 17:18:28] (step=0016400) Train Loss: 0.6558, Train Steps/Sec: 1.23
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+ [2025-10-29 17:19:50] (step=0016500) Train Loss: 0.6544, Train Steps/Sec: 1.23
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+ [2025-10-29 17:21:11] (step=0016600) Train Loss: 0.6552, Train Steps/Sec: 1.23
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+ [2025-10-29 17:22:33] (step=0016700) Train Loss: 0.6570, Train Steps/Sec: 1.23
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+ [2025-10-29 17:23:54] (step=0016800) Train Loss: 0.6554, Train Steps/Sec: 1.23
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+ [2025-10-29 17:25:16] (step=0016900) Train Loss: 0.6549, Train Steps/Sec: 1.23
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+ [2025-10-29 17:26:37] (step=0017000) Train Loss: 0.6536, Train Steps/Sec: 1.23
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+ [2025-10-29 17:27:59] (step=0017100) Train Loss: 0.6554, Train Steps/Sec: 1.23
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+ [2025-10-29 17:29:20] (step=0017200) Train Loss: 0.6547, Train Steps/Sec: 1.23
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+ [2025-10-29 17:30:42] (step=0017300) Train Loss: 0.6540, Train Steps/Sec: 1.23
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+ [2025-10-29 17:32:03] (step=0017400) Train Loss: 0.6532, Train Steps/Sec: 1.23
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+ [2025-10-29 17:33:25] (step=0017500) Train Loss: 0.6544, Train Steps/Sec: 1.23
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+ [2025-10-29 17:33:37] Beginning epoch 14...
214
+ [2025-10-29 17:34:49] (step=0017600) Train Loss: 0.6518, Train Steps/Sec: 1.19
215
+ [2025-10-29 17:36:12] (step=0017700) Train Loss: 0.6514, Train Steps/Sec: 1.21
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+ [2025-10-29 17:37:33] (step=0017800) Train Loss: 0.6515, Train Steps/Sec: 1.23
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+ [2025-10-29 17:38:55] (step=0017900) Train Loss: 0.6524, Train Steps/Sec: 1.23
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+ [2025-10-29 17:40:16] (step=0018000) Train Loss: 0.6525, Train Steps/Sec: 1.23
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+ [2025-10-29 17:41:38] (step=0018100) Train Loss: 0.6508, Train Steps/Sec: 1.23
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+ [2025-10-29 17:42:59] (step=0018200) Train Loss: 0.6508, Train Steps/Sec: 1.23
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+ [2025-10-29 17:44:21] (step=0018300) Train Loss: 0.6514, Train Steps/Sec: 1.23
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+ [2025-10-29 17:45:42] (step=0018400) Train Loss: 0.6510, Train Steps/Sec: 1.23
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+ [2025-10-29 17:47:04] (step=0018500) Train Loss: 0.6507, Train Steps/Sec: 1.23
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+ [2025-10-29 17:48:25] (step=0018600) Train Loss: 0.6513, Train Steps/Sec: 1.23
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+ [2025-10-29 17:49:47] (step=0018700) Train Loss: 0.6505, Train Steps/Sec: 1.23
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+ [2025-10-29 17:50:40] Beginning epoch 15...
227
+ [2025-10-29 17:51:11] (step=0018800) Train Loss: 0.6505, Train Steps/Sec: 1.19
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+ [2025-10-29 17:52:32] (step=0018900) Train Loss: 0.6491, Train Steps/Sec: 1.23
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+ [2025-10-29 17:53:54] (step=0019000) Train Loss: 0.6471, Train Steps/Sec: 1.22
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+ [2025-10-29 17:55:16] (step=0019100) Train Loss: 0.6486, Train Steps/Sec: 1.23
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+ [2025-10-29 17:56:37] (step=0019200) Train Loss: 0.6486, Train Steps/Sec: 1.23
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+ [2025-10-29 17:57:59] (step=0019300) Train Loss: 0.6484, Train Steps/Sec: 1.22
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+ [2025-10-29 17:59:21] (step=0019400) Train Loss: 0.6493, Train Steps/Sec: 1.22
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+ [2025-10-29 18:00:43] (step=0019500) Train Loss: 0.6486, Train Steps/Sec: 1.23
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+ [2025-10-29 18:02:04] (step=0019600) Train Loss: 0.6498, Train Steps/Sec: 1.23
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+ [2025-10-29 18:03:26] (step=0019700) Train Loss: 0.6479, Train Steps/Sec: 1.23
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+ [2025-10-29 18:04:47] (step=0019800) Train Loss: 0.6475, Train Steps/Sec: 1.23
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+ [2025-10-29 18:06:09] (step=0019900) Train Loss: 0.6472, Train Steps/Sec: 1.23
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+ [2025-10-29 18:07:30] (step=0020000) Train Loss: 0.6475, Train Steps/Sec: 1.23
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+ [2025-10-29 18:07:44] Beginning epoch 16...
241
+ [2025-10-29 18:08:54] (step=0020100) Train Loss: 0.6467, Train Steps/Sec: 1.19
242
+ [2025-10-29 18:10:16] (step=0020200) Train Loss: 0.6466, Train Steps/Sec: 1.23
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+ [2025-10-29 18:11:37] (step=0020300) Train Loss: 0.6471, Train Steps/Sec: 1.23
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+ [2025-10-29 18:12:59] (step=0020400) Train Loss: 0.6472, Train Steps/Sec: 1.23
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+ [2025-10-29 18:14:21] (step=0020500) Train Loss: 0.6458, Train Steps/Sec: 1.23
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+ [2025-10-29 18:15:42] (step=0020600) Train Loss: 0.6439, Train Steps/Sec: 1.23
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+ [2025-10-29 18:17:04] (step=0020700) Train Loss: 0.6450, Train Steps/Sec: 1.23
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+ [2025-10-29 18:18:25] (step=0020800) Train Loss: 0.6462, Train Steps/Sec: 1.23
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+ [2025-10-29 18:19:47] (step=0020900) Train Loss: 0.6449, Train Steps/Sec: 1.23
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+ [2025-10-29 18:21:09] (step=0021000) Train Loss: 0.6460, Train Steps/Sec: 1.22
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+ [2025-10-29 18:22:31] (step=0021100) Train Loss: 0.6447, Train Steps/Sec: 1.22
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+ [2025-10-29 18:23:52] (step=0021200) Train Loss: 0.6446, Train Steps/Sec: 1.23
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+ [2025-10-29 18:24:47] Beginning epoch 17...
254
+ [2025-10-29 18:25:16] (step=0021300) Train Loss: 0.6446, Train Steps/Sec: 1.19
255
+ [2025-10-29 18:26:37] (step=0021400) Train Loss: 0.6442, Train Steps/Sec: 1.23
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+ [2025-10-29 18:27:59] (step=0021500) Train Loss: 0.6436, Train Steps/Sec: 1.23
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+ [2025-10-29 18:29:21] (step=0021600) Train Loss: 0.6436, Train Steps/Sec: 1.23
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+ [2025-10-29 18:30:42] (step=0021700) Train Loss: 0.6446, Train Steps/Sec: 1.23
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+ [2025-10-29 18:32:04] (step=0021800) Train Loss: 0.6431, Train Steps/Sec: 1.23
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+ [2025-10-29 18:33:25] (step=0021900) Train Loss: 0.6428, Train Steps/Sec: 1.23
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+ [2025-10-29 18:34:47] (step=0022000) Train Loss: 0.6426, Train Steps/Sec: 1.23
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+ [2025-10-29 18:36:08] (step=0022100) Train Loss: 0.6423, Train Steps/Sec: 1.23
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+ [2025-10-29 18:37:30] (step=0022200) Train Loss: 0.6423, Train Steps/Sec: 1.23
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+ [2025-10-29 18:38:51] (step=0022300) Train Loss: 0.6437, Train Steps/Sec: 1.23
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+ [2025-10-29 18:40:13] (step=0022400) Train Loss: 0.6426, Train Steps/Sec: 1.23
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+ [2025-10-29 18:41:34] (step=0022500) Train Loss: 0.6418, Train Steps/Sec: 1.23
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+ [2025-10-29 18:41:49] Beginning epoch 18...
268
+ [2025-10-29 18:42:58] (step=0022600) Train Loss: 0.6416, Train Steps/Sec: 1.19
269
+ [2025-10-29 18:44:21] (step=0022700) Train Loss: 0.6401, Train Steps/Sec: 1.21
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+ [2025-10-29 18:45:42] (step=0022800) Train Loss: 0.6417, Train Steps/Sec: 1.23
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+ [2025-10-29 18:47:04] (step=0022900) Train Loss: 0.6411, Train Steps/Sec: 1.23
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+ [2025-10-29 18:48:25] (step=0023000) Train Loss: 0.6402, Train Steps/Sec: 1.23
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+ [2025-10-29 18:49:47] (step=0023100) Train Loss: 0.6409, Train Steps/Sec: 1.23
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+ [2025-10-29 18:51:08] (step=0023200) Train Loss: 0.6397, Train Steps/Sec: 1.22
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+ [2025-10-29 18:52:30] (step=0023300) Train Loss: 0.6409, Train Steps/Sec: 1.23
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+ [2025-10-29 18:53:51] (step=0023400) Train Loss: 0.6414, Train Steps/Sec: 1.23
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+ [2025-10-29 18:55:13] (step=0023500) Train Loss: 0.6390, Train Steps/Sec: 1.23
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+ [2025-10-29 18:56:35] (step=0023600) Train Loss: 0.6385, Train Steps/Sec: 1.23
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+ [2025-10-29 18:57:56] (step=0023700) Train Loss: 0.6401, Train Steps/Sec: 1.23
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+ [2025-10-29 18:58:53] Beginning epoch 19...
281
+ [2025-10-29 18:59:20] (step=0023800) Train Loss: 0.6397, Train Steps/Sec: 1.19
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+ [2025-10-29 19:00:41] (step=0023900) Train Loss: 0.6401, Train Steps/Sec: 1.23
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+ [2025-10-29 19:02:03] (step=0024000) Train Loss: 0.6390, Train Steps/Sec: 1.23
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+ [2025-10-29 19:03:24] (step=0024100) Train Loss: 0.6399, Train Steps/Sec: 1.23
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+ [2025-10-29 19:04:46] (step=0024200) Train Loss: 0.6378, Train Steps/Sec: 1.23
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+ [2025-10-29 19:06:08] (step=0024300) Train Loss: 0.6387, Train Steps/Sec: 1.22
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+ [2025-10-29 19:07:30] (step=0024400) Train Loss: 0.6379, Train Steps/Sec: 1.21
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+ [2025-10-29 19:08:51] (step=0024500) Train Loss: 0.6385, Train Steps/Sec: 1.23
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+ [2025-10-29 19:10:13] (step=0024600) Train Loss: 0.6384, Train Steps/Sec: 1.22
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+ [2025-10-29 19:11:35] (step=0024700) Train Loss: 0.6380, Train Steps/Sec: 1.23
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+ [2025-10-29 19:12:56] (step=0024800) Train Loss: 0.6387, Train Steps/Sec: 1.23
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+ [2025-10-29 19:14:18] (step=0024900) Train Loss: 0.6377, Train Steps/Sec: 1.23
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+ [2025-10-29 19:15:39] (step=0025000) Train Loss: 0.6373, Train Steps/Sec: 1.23
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+ [2025-10-29 19:16:29] Saved checkpoint to results/stage2/hfdata/lightningdit-xl-dinov2-vit-b-spnorm-bf16/checkpoints/0025000.pt
295
+ [2025-10-29 19:16:29] Generating EMA samples...
296
+ [2025-10-29 19:16:57] Generating EMA samples done.
297
+ [2025-10-29 19:17:13] Beginning epoch 20...
298
+ [2025-10-29 19:18:20] (step=0025100) Train Loss: 0.6365, Train Steps/Sec: 0.62
299
+ [2025-10-29 19:19:42] (step=0025200) Train Loss: 0.6371, Train Steps/Sec: 1.23
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+ [2025-10-29 19:21:03] (step=0025300) Train Loss: 0.6378, Train Steps/Sec: 1.23
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+ [2025-10-29 19:22:25] (step=0025400) Train Loss: 0.6374, Train Steps/Sec: 1.23
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+ [2025-10-29 19:23:46] (step=0025500) Train Loss: 0.6372, Train Steps/Sec: 1.23
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+ [2025-10-29 19:25:08] (step=0025600) Train Loss: 0.6362, Train Steps/Sec: 1.23
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+ [2025-10-29 19:26:29] (step=0025700) Train Loss: 0.6363, Train Steps/Sec: 1.23
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+ [2025-10-29 19:27:51] (step=0025800) Train Loss: 0.6376, Train Steps/Sec: 1.23
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+ [2025-10-29 19:29:12] (step=0025900) Train Loss: 0.6367, Train Steps/Sec: 1.23
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+ [2025-10-29 19:30:34] (step=0026000) Train Loss: 0.6378, Train Steps/Sec: 1.22
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+ [2025-10-29 19:31:57] (step=0026100) Train Loss: 0.6361, Train Steps/Sec: 1.22
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+ [2025-10-29 19:33:18] (step=0026200) Train Loss: 0.6347, Train Steps/Sec: 1.23
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+ [2025-10-29 19:34:16] Beginning epoch 21...
311
+ [2025-10-29 19:34:42] (step=0026300) Train Loss: 0.6353, Train Steps/Sec: 1.19
312
+ [2025-10-29 19:36:04] (step=0026400) Train Loss: 0.6348, Train Steps/Sec: 1.23
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+ [2025-10-29 19:37:25] (step=0026500) Train Loss: 0.6348, Train Steps/Sec: 1.23
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+ [2025-10-29 19:38:47] (step=0026600) Train Loss: 0.6368, Train Steps/Sec: 1.23
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+ [2025-10-29 19:40:08] (step=0026700) Train Loss: 0.6347, Train Steps/Sec: 1.23
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+ [2025-10-29 19:41:30] (step=0026800) Train Loss: 0.6343, Train Steps/Sec: 1.23
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+ [2025-10-29 19:42:51] (step=0026900) Train Loss: 0.6361, Train Steps/Sec: 1.23
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+ [2025-10-29 19:44:13] (step=0027000) Train Loss: 0.6365, Train Steps/Sec: 1.23
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+ [2025-10-29 19:45:34] (step=0027100) Train Loss: 0.6348, Train Steps/Sec: 1.23
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+ [2025-10-29 19:46:56] (step=0027200) Train Loss: 0.6349, Train Steps/Sec: 1.23
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+ [2025-10-29 19:48:17] (step=0027300) Train Loss: 0.6345, Train Steps/Sec: 1.23
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+ [2025-10-29 19:49:39] (step=0027400) Train Loss: 0.6351, Train Steps/Sec: 1.22
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+ [2025-10-29 19:51:01] (step=0027500) Train Loss: 0.6329, Train Steps/Sec: 1.23
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+ [2025-10-29 19:51:19] Beginning epoch 22...
325
+ [2025-10-29 19:52:25] (step=0027600) Train Loss: 0.6333, Train Steps/Sec: 1.19
326
+ [2025-10-29 19:53:47] (step=0027700) Train Loss: 0.6322, Train Steps/Sec: 1.21
327
+ [2025-10-29 19:55:09] (step=0027800) Train Loss: 0.6335, Train Steps/Sec: 1.22
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+ [2025-10-29 19:56:30] (step=0027900) Train Loss: 0.6332, Train Steps/Sec: 1.23
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+ [2025-10-29 19:57:52] (step=0028000) Train Loss: 0.6337, Train Steps/Sec: 1.23
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+ [2025-10-29 19:59:14] (step=0028100) Train Loss: 0.6319, Train Steps/Sec: 1.23
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+ [2025-10-29 20:00:35] (step=0028200) Train Loss: 0.6340, Train Steps/Sec: 1.23
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+ [2025-10-29 20:01:57] (step=0028300) Train Loss: 0.6327, Train Steps/Sec: 1.23
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+ [2025-10-29 20:03:18] (step=0028400) Train Loss: 0.6325, Train Steps/Sec: 1.23
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+ [2025-10-29 20:04:40] (step=0028500) Train Loss: 0.6328, Train Steps/Sec: 1.23
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+ [2025-10-29 20:06:01] (step=0028600) Train Loss: 0.6330, Train Steps/Sec: 1.23
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+ [2025-10-29 20:07:23] (step=0028700) Train Loss: 0.6330, Train Steps/Sec: 1.23
337
+ [2025-10-29 20:08:23] Beginning epoch 23...
338
+ [2025-10-29 20:08:47] (step=0028800) Train Loss: 0.6320, Train Steps/Sec: 1.19
339
+ [2025-10-29 20:10:08] (step=0028900) Train Loss: 0.6322, Train Steps/Sec: 1.23
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+ [2025-10-29 20:11:30] (step=0029000) Train Loss: 0.6318, Train Steps/Sec: 1.23
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+ [2025-10-29 20:12:51] (step=0029100) Train Loss: 0.6327, Train Steps/Sec: 1.23
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+ [2025-10-29 20:14:13] (step=0029200) Train Loss: 0.6325, Train Steps/Sec: 1.23
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+ [2025-10-29 20:15:34] (step=0029300) Train Loss: 0.6312, Train Steps/Sec: 1.23
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+ [2025-10-29 20:16:57] (step=0029400) Train Loss: 0.6301, Train Steps/Sec: 1.21
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+ [2025-10-29 20:18:19] (step=0029500) Train Loss: 0.6295, Train Steps/Sec: 1.22
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+ [2025-10-29 20:19:40] (step=0029600) Train Loss: 0.6318, Train Steps/Sec: 1.23
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+ [2025-10-29 20:21:02] (step=0029700) Train Loss: 0.6315, Train Steps/Sec: 1.23
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+ [2025-10-29 20:22:23] (step=0029800) Train Loss: 0.6317, Train Steps/Sec: 1.23
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+ [2025-10-29 20:23:45] (step=0029900) Train Loss: 0.6317, Train Steps/Sec: 1.23
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+ [2025-10-29 20:25:06] (step=0030000) Train Loss: 0.6310, Train Steps/Sec: 1.23
351
+ [2025-10-29 20:25:26] Beginning epoch 24...
352
+ [2025-10-29 20:26:30] (step=0030100) Train Loss: 0.6316, Train Steps/Sec: 1.19
353
+ [2025-10-29 20:27:52] (step=0030200) Train Loss: 0.6309, Train Steps/Sec: 1.23
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+ [2025-10-29 20:29:13] (step=0030300) Train Loss: 0.6314, Train Steps/Sec: 1.23
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+ [2025-10-29 20:30:35] (step=0030400) Train Loss: 0.6292, Train Steps/Sec: 1.23
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+ [2025-10-29 20:31:56] (step=0030500) Train Loss: 0.6289, Train Steps/Sec: 1.23
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+ [2025-10-29 20:33:18] (step=0030600) Train Loss: 0.6312, Train Steps/Sec: 1.23
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+ [2025-10-29 20:34:39] (step=0030700) Train Loss: 0.6300, Train Steps/Sec: 1.23
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+ [2025-10-29 20:36:01] (step=0030800) Train Loss: 0.6299, Train Steps/Sec: 1.23
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+ [2025-10-29 20:37:23] (step=0030900) Train Loss: 0.6301, Train Steps/Sec: 1.23
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+ [2025-10-29 20:38:44] (step=0031000) Train Loss: 0.6288, Train Steps/Sec: 1.22
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+ [2025-10-29 20:40:06] (step=0031100) Train Loss: 0.6297, Train Steps/Sec: 1.22
363
+ [2025-10-29 20:41:28] (step=0031200) Train Loss: 0.6290, Train Steps/Sec: 1.23
364
+ [2025-10-29 20:42:30] Beginning epoch 25...
365
+ [2025-10-29 20:42:52] (step=0031300) Train Loss: 0.6287, Train Steps/Sec: 1.19
366
+ [2025-10-29 20:44:13] (step=0031400) Train Loss: 0.6295, Train Steps/Sec: 1.23
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+ [2025-10-29 20:45:35] (step=0031500) Train Loss: 0.6290, Train Steps/Sec: 1.23
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+ [2025-10-29 20:46:56] (step=0031600) Train Loss: 0.6285, Train Steps/Sec: 1.23
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+ [2025-10-29 20:48:18] (step=0031700) Train Loss: 0.6294, Train Steps/Sec: 1.23
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+ [2025-10-29 20:49:40] (step=0031800) Train Loss: 0.6280, Train Steps/Sec: 1.23
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+ [2025-10-29 20:51:01] (step=0031900) Train Loss: 0.6270, Train Steps/Sec: 1.23
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+ [2025-10-29 20:52:23] (step=0032000) Train Loss: 0.6279, Train Steps/Sec: 1.23
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+ [2025-10-29 20:53:44] (step=0032100) Train Loss: 0.6285, Train Steps/Sec: 1.23
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+ [2025-10-29 20:55:06] (step=0032200) Train Loss: 0.6294, Train Steps/Sec: 1.23
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+ [2025-10-29 20:56:27] (step=0032300) Train Loss: 0.6291, Train Steps/Sec: 1.23
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+ [2025-10-29 20:57:49] (step=0032400) Train Loss: 0.6279, Train Steps/Sec: 1.23
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+ [2025-10-29 20:59:10] (step=0032500) Train Loss: 0.6288, Train Steps/Sec: 1.23
378
+ [2025-10-29 20:59:32] Beginning epoch 26...
379
+ [2025-10-29 21:00:34] (step=0032600) Train Loss: 0.6279, Train Steps/Sec: 1.19
380
+ [2025-10-29 21:01:56] (step=0032700) Train Loss: 0.6265, Train Steps/Sec: 1.22
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+ [2025-10-29 21:03:18] (step=0032800) Train Loss: 0.6268, Train Steps/Sec: 1.22
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+ [2025-10-29 21:04:40] (step=0032900) Train Loss: 0.6264, Train Steps/Sec: 1.23
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+ [2025-10-29 21:06:01] (step=0033000) Train Loss: 0.6281, Train Steps/Sec: 1.23
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+ [2025-10-29 21:07:23] (step=0033100) Train Loss: 0.6282, Train Steps/Sec: 1.22
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+ [2025-10-29 21:08:45] (step=0033200) Train Loss: 0.6273, Train Steps/Sec: 1.23
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+ [2025-10-29 21:10:06] (step=0033300) Train Loss: 0.6280, Train Steps/Sec: 1.23
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+ [2025-10-29 21:11:28] (step=0033400) Train Loss: 0.6307, Train Steps/Sec: 1.23
388
+ [2025-10-29 21:12:49] (step=0033500) Train Loss: 0.6290, Train Steps/Sec: 1.23
389
+ [2025-10-29 21:14:11] (step=0033600) Train Loss: 0.6278, Train Steps/Sec: 1.23
390
+ [2025-10-29 21:15:32] (step=0033700) Train Loss: 0.6261, Train Steps/Sec: 1.23
391
+ [2025-10-29 21:16:36] Beginning epoch 27...
392
+ [2025-10-29 21:16:56] (step=0033800) Train Loss: 0.6268, Train Steps/Sec: 1.19
393
+ [2025-10-29 21:18:18] (step=0033900) Train Loss: 0.6278, Train Steps/Sec: 1.23
394
+ [2025-10-29 21:19:39] (step=0034000) Train Loss: 0.6268, Train Steps/Sec: 1.23
395
+ [2025-10-29 21:21:01] (step=0034100) Train Loss: 0.6269, Train Steps/Sec: 1.23
396
+ [2025-10-29 21:22:22] (step=0034200) Train Loss: 0.6274, Train Steps/Sec: 1.23
397
+ [2025-10-29 21:23:44] (step=0034300) Train Loss: 0.6259, Train Steps/Sec: 1.23
398
+ [2025-10-29 21:25:06] (step=0034400) Train Loss: 0.6252, Train Steps/Sec: 1.21
399
+ [2025-10-29 21:26:28] (step=0034500) Train Loss: 0.6251, Train Steps/Sec: 1.22
400
+ [2025-10-29 21:27:50] (step=0034600) Train Loss: 0.6270, Train Steps/Sec: 1.23
401
+ [2025-10-29 21:29:11] (step=0034700) Train Loss: 0.6264, Train Steps/Sec: 1.23
402
+ [2025-10-29 21:30:33] (step=0034800) Train Loss: 0.6265, Train Steps/Sec: 1.23
403
+ [2025-10-29 21:31:54] (step=0034900) Train Loss: 0.6260, Train Steps/Sec: 1.23
404
+ [2025-10-29 21:33:16] (step=0035000) Train Loss: 0.6262, Train Steps/Sec: 1.23
405
+ [2025-10-29 21:33:39] Beginning epoch 28...
406
+ [2025-10-29 21:34:40] (step=0035100) Train Loss: 0.6254, Train Steps/Sec: 1.19
407
+ [2025-10-29 21:36:01] (step=0035200) Train Loss: 0.6261, Train Steps/Sec: 1.23
408
+ [2025-10-29 21:37:22] (step=0035300) Train Loss: 0.6256, Train Steps/Sec: 1.23
409
+ [2025-10-29 21:38:44] (step=0035400) Train Loss: 0.6267, Train Steps/Sec: 1.23
410
+ [2025-10-29 21:40:06] (step=0035500) Train Loss: 0.6242, Train Steps/Sec: 1.23
411
+ [2025-10-29 21:41:27] (step=0035600) Train Loss: 0.6251, Train Steps/Sec: 1.23
412
+ [2025-10-29 21:42:49] (step=0035700) Train Loss: 0.6238, Train Steps/Sec: 1.23
413
+ [2025-10-29 21:44:10] (step=0035800) Train Loss: 0.6243, Train Steps/Sec: 1.23
414
+ [2025-10-29 21:45:32] (step=0035900) Train Loss: 0.6258, Train Steps/Sec: 1.23
415
+ [2025-10-29 21:46:53] (step=0036000) Train Loss: 0.6256, Train Steps/Sec: 1.22
416
+ [2025-10-29 21:48:16] (step=0036100) Train Loss: 0.6248, Train Steps/Sec: 1.22
417
+ [2025-10-29 21:49:37] (step=0036200) Train Loss: 0.6249, Train Steps/Sec: 1.23
418
+ [2025-10-29 21:50:42] Beginning epoch 29...
419
+ [2025-10-29 21:51:01] (step=0036300) Train Loss: 0.6251, Train Steps/Sec: 1.19
420
+ [2025-10-29 21:52:23] (step=0036400) Train Loss: 0.6247, Train Steps/Sec: 1.23
421
+ [2025-10-29 21:53:44] (step=0036500) Train Loss: 0.6234, Train Steps/Sec: 1.23
422
+ [2025-10-29 21:55:06] (step=0036600) Train Loss: 0.6236, Train Steps/Sec: 1.23
423
+ [2025-10-29 21:56:27] (step=0036700) Train Loss: 0.6246, Train Steps/Sec: 1.23
424
+ [2025-10-29 21:57:49] (step=0036800) Train Loss: 0.6247, Train Steps/Sec: 1.23
425
+ [2025-10-29 21:59:10] (step=0036900) Train Loss: 0.6247, Train Steps/Sec: 1.23
426
+ [2025-10-29 22:00:32] (step=0037000) Train Loss: 0.6244, Train Steps/Sec: 1.23
427
+ [2025-10-29 22:01:53] (step=0037100) Train Loss: 0.6241, Train Steps/Sec: 1.23
428
+ [2025-10-29 22:03:15] (step=0037200) Train Loss: 0.6230, Train Steps/Sec: 1.23
429
+ [2025-10-29 22:04:36] (step=0037300) Train Loss: 0.6242, Train Steps/Sec: 1.23
430
+ [2025-10-29 22:05:58] (step=0037400) Train Loss: 0.6226, Train Steps/Sec: 1.23
431
+ [2025-10-29 22:07:19] (step=0037500) Train Loss: 0.6234, Train Steps/Sec: 1.23
432
+ [2025-10-29 22:07:44] Beginning epoch 30...
433
+ [2025-10-29 22:08:43] (step=0037600) Train Loss: 0.6236, Train Steps/Sec: 1.19
434
+ [2025-10-29 22:10:05] (step=0037700) Train Loss: 0.6243, Train Steps/Sec: 1.22
435
+ [2025-10-29 22:11:27] (step=0037800) Train Loss: 0.6244, Train Steps/Sec: 1.22
436
+ [2025-10-29 22:12:49] (step=0037900) Train Loss: 0.6237, Train Steps/Sec: 1.23
437
+ [2025-10-29 22:14:10] (step=0038000) Train Loss: 0.6231, Train Steps/Sec: 1.23
438
+ [2025-10-29 22:15:32] (step=0038100) Train Loss: 0.6232, Train Steps/Sec: 1.23
439
+ [2025-10-29 22:16:53] (step=0038200) Train Loss: 0.6239, Train Steps/Sec: 1.23
440
+ [2025-10-29 22:18:15] (step=0038300) Train Loss: 0.6237, Train Steps/Sec: 1.23
441
+ [2025-10-29 22:19:36] (step=0038400) Train Loss: 0.6230, Train Steps/Sec: 1.23
442
+ [2025-10-29 22:20:58] (step=0038500) Train Loss: 0.6227, Train Steps/Sec: 1.23
443
+ [2025-10-29 22:22:19] (step=0038600) Train Loss: 0.6212, Train Steps/Sec: 1.23
444
+ [2025-10-29 22:23:41] (step=0038700) Train Loss: 0.6238, Train Steps/Sec: 1.23
445
+ [2025-10-29 22:24:48] Beginning epoch 31...
446
+ [2025-10-29 22:25:06] (step=0038800) Train Loss: 0.6240, Train Steps/Sec: 1.18
447
+ [2025-10-29 22:26:27] (step=0038900) Train Loss: 0.6232, Train Steps/Sec: 1.23
448
+ [2025-10-29 22:27:49] (step=0039000) Train Loss: 0.6213, Train Steps/Sec: 1.23
449
+ [2025-10-29 22:29:10] (step=0039100) Train Loss: 0.6226, Train Steps/Sec: 1.23
450
+ [2025-10-29 22:30:32] (step=0039200) Train Loss: 0.6217, Train Steps/Sec: 1.23
451
+ [2025-10-29 22:31:53] (step=0039300) Train Loss: 0.6231, Train Steps/Sec: 1.23
452
+ [2025-10-29 22:33:15] (step=0039400) Train Loss: 0.6217, Train Steps/Sec: 1.22
453
+ [2025-10-29 22:34:37] (step=0039500) Train Loss: 0.6214, Train Steps/Sec: 1.22
454
+ [2025-10-29 22:35:59] (step=0039600) Train Loss: 0.6215, Train Steps/Sec: 1.23
455
+ [2025-10-29 22:37:20] (step=0039700) Train Loss: 0.6231, Train Steps/Sec: 1.23
456
+ [2025-10-29 22:38:42] (step=0039800) Train Loss: 0.6220, Train Steps/Sec: 1.23
457
+ [2025-10-29 22:40:03] (step=0039900) Train Loss: 0.6229, Train Steps/Sec: 1.23
458
+ [2025-10-29 22:41:25] (step=0040000) Train Loss: 0.6220, Train Steps/Sec: 1.23
459
+ [2025-10-29 22:41:52] Beginning epoch 32...
460
+ [2025-10-29 22:42:50] (step=0040100) Train Loss: 0.6213, Train Steps/Sec: 1.18
461
+ [2025-10-29 22:44:11] (step=0040200) Train Loss: 0.6229, Train Steps/Sec: 1.22
462
+ [2025-10-29 22:45:33] (step=0040300) Train Loss: 0.6216, Train Steps/Sec: 1.23
463
+ [2025-10-29 22:46:54] (step=0040400) Train Loss: 0.6218, Train Steps/Sec: 1.23
464
+ [2025-10-29 22:48:16] (step=0040500) Train Loss: 0.6197, Train Steps/Sec: 1.23
465
+ [2025-10-29 22:49:37] (step=0040600) Train Loss: 0.6215, Train Steps/Sec: 1.23
466
+ [2025-10-29 22:50:59] (step=0040700) Train Loss: 0.6228, Train Steps/Sec: 1.23
467
+ [2025-10-29 22:52:20] (step=0040800) Train Loss: 0.6203, Train Steps/Sec: 1.23
468
+ [2025-10-29 22:53:42] (step=0040900) Train Loss: 0.6197, Train Steps/Sec: 1.23
469
+ [2025-10-29 22:55:03] (step=0041000) Train Loss: 0.6214, Train Steps/Sec: 1.23
470
+ [2025-10-29 22:56:25] (step=0041100) Train Loss: 0.6199, Train Steps/Sec: 1.22
471
+ [2025-10-29 22:57:47] (step=0041200) Train Loss: 0.6201, Train Steps/Sec: 1.22
472
+ [2025-10-29 22:58:55] Beginning epoch 33...
473
+ [2025-10-29 22:59:11] (step=0041300) Train Loss: 0.6208, Train Steps/Sec: 1.19
474
+ [2025-10-29 23:00:32] (step=0041400) Train Loss: 0.6202, Train Steps/Sec: 1.23
475
+ [2025-10-29 23:01:54] (step=0041500) Train Loss: 0.6197, Train Steps/Sec: 1.23
476
+ [2025-10-29 23:03:16] (step=0041600) Train Loss: 0.6208, Train Steps/Sec: 1.23
477
+ [2025-10-29 23:04:37] (step=0041700) Train Loss: 0.6198, Train Steps/Sec: 1.23
478
+ [2025-10-29 23:05:59] (step=0041800) Train Loss: 0.6198, Train Steps/Sec: 1.23
479
+ [2025-10-29 23:07:20] (step=0041900) Train Loss: 0.6218, Train Steps/Sec: 1.23
480
+ [2025-10-29 23:08:41] (step=0042000) Train Loss: 0.6204, Train Steps/Sec: 1.23
481
+ [2025-10-29 23:10:03] (step=0042100) Train Loss: 0.6209, Train Steps/Sec: 1.23
482
+ [2025-10-29 23:11:24] (step=0042200) Train Loss: 0.6198, Train Steps/Sec: 1.23
483
+ [2025-10-29 23:12:46] (step=0042300) Train Loss: 0.6200, Train Steps/Sec: 1.23
484
+ [2025-10-29 23:14:07] (step=0042400) Train Loss: 0.6196, Train Steps/Sec: 1.23
485
+ [2025-10-29 23:15:29] (step=0042500) Train Loss: 0.6186, Train Steps/Sec: 1.23
486
+ [2025-10-29 23:15:57] Beginning epoch 34...
487
+ [2025-10-29 23:16:53] (step=0042600) Train Loss: 0.6204, Train Steps/Sec: 1.19
488
+ [2025-10-29 23:18:15] (step=0042700) Train Loss: 0.6199, Train Steps/Sec: 1.22
489
+ [2025-10-29 23:19:37] (step=0042800) Train Loss: 0.6206, Train Steps/Sec: 1.22
490
+ [2025-10-29 23:20:58] (step=0042900) Train Loss: 0.6195, Train Steps/Sec: 1.23
491
+ [2025-10-29 23:22:20] (step=0043000) Train Loss: 0.6205, Train Steps/Sec: 1.22
492
+ [2025-10-29 23:23:42] (step=0043100) Train Loss: 0.6180, Train Steps/Sec: 1.23
493
+ [2025-10-29 23:25:03] (step=0043200) Train Loss: 0.6208, Train Steps/Sec: 1.23
494
+ [2025-10-29 23:26:25] (step=0043300) Train Loss: 0.6193, Train Steps/Sec: 1.23
495
+ [2025-10-29 23:27:46] (step=0043400) Train Loss: 0.6203, Train Steps/Sec: 1.23
496
+ [2025-10-29 23:29:08] (step=0043500) Train Loss: 0.6197, Train Steps/Sec: 1.23
497
+ [2025-10-29 23:30:29] (step=0043600) Train Loss: 0.6196, Train Steps/Sec: 1.23
498
+ [2025-10-29 23:31:50] (step=0043700) Train Loss: 0.6193, Train Steps/Sec: 1.23
499
+ [2025-10-29 23:33:00] Beginning epoch 35...
500
+ [2025-10-29 23:33:14] (step=0043800) Train Loss: 0.6201, Train Steps/Sec: 1.19
501
+ [2025-10-29 23:34:36] (step=0043900) Train Loss: 0.6189, Train Steps/Sec: 1.23
502
+ [2025-10-29 23:35:57] (step=0044000) Train Loss: 0.6185, Train Steps/Sec: 1.23
503
+ [2025-10-29 23:37:19] (step=0044100) Train Loss: 0.6194, Train Steps/Sec: 1.23
504
+ [2025-10-29 23:38:40] (step=0044200) Train Loss: 0.6191, Train Steps/Sec: 1.23
505
+ [2025-10-29 23:40:02] (step=0044300) Train Loss: 0.6194, Train Steps/Sec: 1.23
506
+ [2025-10-29 23:41:24] (step=0044400) Train Loss: 0.6179, Train Steps/Sec: 1.22
507
+ [2025-10-29 23:42:46] (step=0044500) Train Loss: 0.6185, Train Steps/Sec: 1.22
508
+ [2025-10-29 23:44:08] (step=0044600) Train Loss: 0.6180, Train Steps/Sec: 1.23
509
+ [2025-10-29 23:45:29] (step=0044700) Train Loss: 0.6207, Train Steps/Sec: 1.23
510
+ [2025-10-29 23:46:51] (step=0044800) Train Loss: 0.6189, Train Steps/Sec: 1.23
511
+ [2025-10-29 23:48:12] (step=0044900) Train Loss: 0.6183, Train Steps/Sec: 1.23
512
+ [2025-10-29 23:49:34] (step=0045000) Train Loss: 0.6190, Train Steps/Sec: 1.23
513
+ [2025-10-29 23:50:03] Beginning epoch 36...
514
+ [2025-10-29 23:50:58] (step=0045100) Train Loss: 0.6198, Train Steps/Sec: 1.19
515
+ [2025-10-29 23:52:19] (step=0045200) Train Loss: 0.6184, Train Steps/Sec: 1.23
516
+ [2025-10-29 23:53:41] (step=0045300) Train Loss: 0.6175, Train Steps/Sec: 1.23
517
+ [2025-10-29 23:55:02] (step=0045400) Train Loss: 0.6187, Train Steps/Sec: 1.23
518
+ [2025-10-29 23:56:24] (step=0045500) Train Loss: 0.6187, Train Steps/Sec: 1.23
519
+ [2025-10-29 23:57:45] (step=0045600) Train Loss: 0.6181, Train Steps/Sec: 1.23
520
+ [2025-10-29 23:59:07] (step=0045700) Train Loss: 0.6185, Train Steps/Sec: 1.23
521
+ [2025-10-30 00:00:28] (step=0045800) Train Loss: 0.6188, Train Steps/Sec: 1.23
522
+ [2025-10-30 00:01:50] (step=0045900) Train Loss: 0.6170, Train Steps/Sec: 1.22
523
+ [2025-10-30 00:03:11] (step=0046000) Train Loss: 0.6172, Train Steps/Sec: 1.23
524
+ [2025-10-30 00:04:34] (step=0046100) Train Loss: 0.6168, Train Steps/Sec: 1.22
525
+ [2025-10-30 00:05:55] (step=0046200) Train Loss: 0.6189, Train Steps/Sec: 1.22
526
+ [2025-10-30 00:07:07] Beginning epoch 37...
527
+ [2025-10-30 00:07:19] (step=0046300) Train Loss: 0.6189, Train Steps/Sec: 1.19
528
+ [2025-10-30 00:08:41] (step=0046400) Train Loss: 0.6191, Train Steps/Sec: 1.23
529
+ [2025-10-30 00:10:02] (step=0046500) Train Loss: 0.6166, Train Steps/Sec: 1.23
530
+ [2025-10-30 00:11:24] (step=0046600) Train Loss: 0.6165, Train Steps/Sec: 1.23
531
+ [2025-10-30 00:12:45] (step=0046700) Train Loss: 0.6171, Train Steps/Sec: 1.23
532
+ [2025-10-30 00:14:07] (step=0046800) Train Loss: 0.6173, Train Steps/Sec: 1.23
533
+ [2025-10-30 00:15:28] (step=0046900) Train Loss: 0.6184, Train Steps/Sec: 1.23
534
+ [2025-10-30 00:16:50] (step=0047000) Train Loss: 0.6170, Train Steps/Sec: 1.23
535
+ [2025-10-30 00:18:11] (step=0047100) Train Loss: 0.6176, Train Steps/Sec: 1.23
536
+ [2025-10-30 00:19:33] (step=0047200) Train Loss: 0.6187, Train Steps/Sec: 1.23
537
+ [2025-10-30 00:20:54] (step=0047300) Train Loss: 0.6184, Train Steps/Sec: 1.23
538
+ [2025-10-30 00:22:16] (step=0047400) Train Loss: 0.6178, Train Steps/Sec: 1.23
539
+ [2025-10-30 00:23:37] (step=0047500) Train Loss: 0.6177, Train Steps/Sec: 1.23
540
+ [2025-10-30 00:24:09] Beginning epoch 38...
541
+ [2025-10-30 00:25:01] (step=0047600) Train Loss: 0.6160, Train Steps/Sec: 1.19
542
+ [2025-10-30 00:26:23] (step=0047700) Train Loss: 0.6170, Train Steps/Sec: 1.22
543
+ [2025-10-30 00:27:45] (step=0047800) Train Loss: 0.6161, Train Steps/Sec: 1.22
544
+ [2025-10-30 00:29:07] (step=0047900) Train Loss: 0.6175, Train Steps/Sec: 1.23
545
+ [2025-10-30 00:30:28] (step=0048000) Train Loss: 0.6173, Train Steps/Sec: 1.23
546
+ [2025-10-30 00:31:50] (step=0048100) Train Loss: 0.6187, Train Steps/Sec: 1.23
547
+ [2025-10-30 00:33:11] (step=0048200) Train Loss: 0.6191, Train Steps/Sec: 1.23
548
+ [2025-10-30 00:34:33] (step=0048300) Train Loss: 0.6159, Train Steps/Sec: 1.23
549
+ [2025-10-30 00:35:54] (step=0048400) Train Loss: 0.6183, Train Steps/Sec: 1.23
550
+ [2025-10-30 00:37:16] (step=0048500) Train Loss: 0.6165, Train Steps/Sec: 1.23
551
+ [2025-10-30 00:38:37] (step=0048600) Train Loss: 0.6171, Train Steps/Sec: 1.23
552
+ [2025-10-30 00:39:59] (step=0048700) Train Loss: 0.6174, Train Steps/Sec: 1.23
553
+ [2025-10-30 00:41:12] Beginning epoch 39...
554
+ [2025-10-30 00:41:23] (step=0048800) Train Loss: 0.6161, Train Steps/Sec: 1.19
555
+ [2025-10-30 00:42:45] (step=0048900) Train Loss: 0.6137, Train Steps/Sec: 1.23
556
+ [2025-10-30 00:44:06] (step=0049000) Train Loss: 0.6157, Train Steps/Sec: 1.23
557
+ [2025-10-30 00:45:28] (step=0049100) Train Loss: 0.6157, Train Steps/Sec: 1.23
558
+ [2025-10-30 00:46:49] (step=0049200) Train Loss: 0.6173, Train Steps/Sec: 1.23
559
+ [2025-10-30 00:48:11] (step=0049300) Train Loss: 0.6155, Train Steps/Sec: 1.23
560
+ [2025-10-30 00:49:32] (step=0049400) Train Loss: 0.6157, Train Steps/Sec: 1.22
561
+ [2025-10-30 00:50:55] (step=0049500) Train Loss: 0.6156, Train Steps/Sec: 1.22
562
+ [2025-10-30 00:52:16] (step=0049600) Train Loss: 0.6152, Train Steps/Sec: 1.23
563
+ [2025-10-30 00:53:38] (step=0049700) Train Loss: 0.6167, Train Steps/Sec: 1.23
564
+ [2025-10-30 00:54:59] (step=0049800) Train Loss: 0.6150, Train Steps/Sec: 1.23
565
+ [2025-10-30 00:56:21] (step=0049900) Train Loss: 0.6153, Train Steps/Sec: 1.23
566
+ [2025-10-30 00:57:42] (step=0050000) Train Loss: 0.6171, Train Steps/Sec: 1.23
567
+ [2025-10-30 00:58:38] Saved checkpoint to results/stage2/hfdata/lightningdit-xl-dinov2-vit-b-spnorm-bf16/checkpoints/0050000.pt
568
+ [2025-10-30 00:58:38] Generating EMA samples...
569
+ [2025-10-30 00:59:06] Generating EMA samples done.
570
+ [2025-10-30 00:59:39] Beginning epoch 40...
571
+ [2025-10-30 01:00:29] (step=0050100) Train Loss: 0.6155, Train Steps/Sec: 0.60
572
+ [2025-10-30 01:01:51] (step=0050200) Train Loss: 0.6157, Train Steps/Sec: 1.23
573
+ [2025-10-30 01:03:12] (step=0050300) Train Loss: 0.6158, Train Steps/Sec: 1.23
574
+ [2025-10-30 01:04:34] (step=0050400) Train Loss: 0.6179, Train Steps/Sec: 1.23
575
+ [2025-10-30 01:05:55] (step=0050500) Train Loss: 0.6155, Train Steps/Sec: 1.23
576
+ [2025-10-30 01:07:17] (step=0050600) Train Loss: 0.6144, Train Steps/Sec: 1.23
577
+ [2025-10-30 01:08:38] (step=0050700) Train Loss: 0.6157, Train Steps/Sec: 1.23
578
+ [2025-10-30 01:10:00] (step=0050800) Train Loss: 0.6172, Train Steps/Sec: 1.23
579
+ [2025-10-30 01:11:21] (step=0050900) Train Loss: 0.6173, Train Steps/Sec: 1.23
580
+ [2025-10-30 01:12:43] (step=0051000) Train Loss: 0.6164, Train Steps/Sec: 1.23
581
+ [2025-10-30 01:14:05] (step=0051100) Train Loss: 0.6165, Train Steps/Sec: 1.22
582
+ [2025-10-30 01:15:27] (step=0051200) Train Loss: 0.6156, Train Steps/Sec: 1.22
583
+ [2025-10-30 01:16:41] Beginning epoch 41...
584
+ [2025-10-30 01:16:50] (step=0051300) Train Loss: 0.6145, Train Steps/Sec: 1.19
585
+ [2025-10-30 01:18:12] (step=0051400) Train Loss: 0.6152, Train Steps/Sec: 1.23
586
+ [2025-10-30 01:19:34] (step=0051500) Train Loss: 0.6149, Train Steps/Sec: 1.22
587
+ [2025-10-30 01:20:55] (step=0051600) Train Loss: 0.6157, Train Steps/Sec: 1.23
588
+ [2025-10-30 01:22:17] (step=0051700) Train Loss: 0.6152, Train Steps/Sec: 1.23
589
+ [2025-10-30 01:23:38] (step=0051800) Train Loss: 0.6169, Train Steps/Sec: 1.23
590
+ [2025-10-30 01:25:00] (step=0051900) Train Loss: 0.6166, Train Steps/Sec: 1.23
591
+ [2025-10-30 01:26:21] (step=0052000) Train Loss: 0.6167, Train Steps/Sec: 1.23
592
+ [2025-10-30 01:27:43] (step=0052100) Train Loss: 0.6168, Train Steps/Sec: 1.23
593
+ [2025-10-30 01:29:04] (step=0052200) Train Loss: 0.6165, Train Steps/Sec: 1.23
594
+ [2025-10-30 01:30:25] (step=0052300) Train Loss: 0.6166, Train Steps/Sec: 1.23
595
+ [2025-10-30 01:31:47] (step=0052400) Train Loss: 0.6166, Train Steps/Sec: 1.23
596
+ [2025-10-30 01:33:08] (step=0052500) Train Loss: 1.4301, Train Steps/Sec: 1.23
597
+ [2025-10-30 01:33:43] Beginning epoch 42...
598
+ [2025-10-30 01:34:32] (step=0052600) Train Loss: 1.6885, Train Steps/Sec: 1.19
599
+ [2025-10-30 01:35:54] (step=0052700) Train Loss: 1.6226, Train Steps/Sec: 1.23
600
+ [2025-10-30 01:37:16] (step=0052800) Train Loss: 2.1252, Train Steps/Sec: 1.22
601
+ [2025-10-30 01:38:34] (step=0052900) Train Loss: nan, Train Steps/Sec: 1.28
602
+ [2025-10-30 01:39:52] (step=0053000) Train Loss: nan, Train Steps/Sec: 1.29
603
+ [2025-10-30 01:41:09] (step=0053100) Train Loss: nan, Train Steps/Sec: 1.29
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+ [2025-10-30 01:42:27] (step=0053200) Train Loss: nan, Train Steps/Sec: 1.29
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+ [2025-10-30 01:43:44] (step=0053300) Train Loss: nan, Train Steps/Sec: 1.29
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+ [2025-10-30 01:45:02] (step=0053400) Train Loss: nan, Train Steps/Sec: 1.29
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+ [2025-10-30 01:46:19] (step=0053500) Train Loss: nan, Train Steps/Sec: 1.29
608
+ [2025-10-30 01:47:37] (step=0053600) Train Loss: nan, Train Steps/Sec: 1.29
609
+ [2025-10-30 01:48:54] (step=0053700) Train Loss: nan, Train Steps/Sec: 1.29
610
+ [2025-10-30 01:50:07] Beginning epoch 43...
611
+ [2025-10-30 01:50:14] (step=0053800) Train Loss: nan, Train Steps/Sec: 1.25
612
+ [2025-10-30 01:51:32] (step=0053900) Train Loss: nan, Train Steps/Sec: 1.29
613
+ [2025-10-30 01:52:49] (step=0054000) Train Loss: nan, Train Steps/Sec: 1.29
614
+ [2025-10-30 01:54:07] (step=0054100) Train Loss: nan, Train Steps/Sec: 1.29
615
+ [2025-10-30 01:55:24] (step=0054200) Train Loss: nan, Train Steps/Sec: 1.29
616
+ [2025-10-30 01:56:42] (step=0054300) Train Loss: nan, Train Steps/Sec: 1.29
617
+ [2025-10-30 01:58:00] (step=0054400) Train Loss: nan, Train Steps/Sec: 1.28
618
+ [2025-10-30 01:59:18] (step=0054500) Train Loss: nan, Train Steps/Sec: 1.28
619
+ [2025-10-30 02:00:36] (step=0054600) Train Loss: nan, Train Steps/Sec: 1.29
620
+ [2025-10-30 02:01:53] (step=0054700) Train Loss: nan, Train Steps/Sec: 1.29
621
+ [2025-10-30 02:03:11] (step=0054800) Train Loss: nan, Train Steps/Sec: 1.29
622
+ [2025-10-30 02:04:28] (step=0054900) Train Loss: nan, Train Steps/Sec: 1.29
623
+ [2025-10-30 02:05:46] (step=0055000) Train Loss: nan, Train Steps/Sec: 1.29
624
+ [2025-10-30 02:06:20] Beginning epoch 44...
625
+ [2025-10-30 02:07:06] (step=0055100) Train Loss: nan, Train Steps/Sec: 1.25
626
+ [2025-10-30 02:08:23] (step=0055200) Train Loss: nan, Train Steps/Sec: 1.29
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+ [2025-10-30 02:09:41] (step=0055300) Train Loss: nan, Train Steps/Sec: 1.29
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+ [2025-10-30 02:10:58] (step=0055400) Train Loss: nan, Train Steps/Sec: 1.29
629
+ [2025-10-30 02:12:16] (step=0055500) Train Loss: nan, Train Steps/Sec: 1.29
630
+ [2025-10-30 02:13:33] (step=0055600) Train Loss: nan, Train Steps/Sec: 1.29
631
+ [2025-10-30 02:14:51] (step=0055700) Train Loss: nan, Train Steps/Sec: 1.29
632
+ [2025-10-30 02:16:08] (step=0055800) Train Loss: nan, Train Steps/Sec: 1.29
633
+ [2025-10-30 02:17:26] (step=0055900) Train Loss: nan, Train Steps/Sec: 1.29
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+ [2025-10-30 02:18:43] (step=0056000) Train Loss: nan, Train Steps/Sec: 1.29
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+ [2025-10-30 02:20:01] (step=0056100) Train Loss: nan, Train Steps/Sec: 1.29
636
+ [2025-10-30 02:21:19] (step=0056200) Train Loss: nan, Train Steps/Sec: 1.28
637
+ [2025-10-30 02:22:34] Beginning epoch 45...
638
+ [2025-10-30 02:22:39] (step=0056300) Train Loss: nan, Train Steps/Sec: 1.25
639
+ [2025-10-30 02:23:57] (step=0056400) Train Loss: nan, Train Steps/Sec: 1.29
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+ [2025-10-30 02:25:14] (step=0056500) Train Loss: nan, Train Steps/Sec: 1.29
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+ [2025-10-30 02:26:32] (step=0056600) Train Loss: nan, Train Steps/Sec: 1.29
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+ [2025-10-30 02:27:49] (step=0056700) Train Loss: nan, Train Steps/Sec: 1.29
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+ [2025-10-30 02:29:07] (step=0056800) Train Loss: nan, Train Steps/Sec: 1.29
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+ [2025-10-30 02:30:25] (step=0056900) Train Loss: nan, Train Steps/Sec: 1.29