xingjianleng commited on
Commit
4ef9a4c
·
verified ·
1 Parent(s): 65c4c1d

Upload folder using huggingface_hub

Browse files
stage2/lightningdit-xl-spatialpe-vit-g-bf16/checkpoints/0025000.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:bc073e7b9e0baf0e6f698c7fd4bfbc2172c3b32cc39993ec9150b7590a7eb1b2
3
+ size 19268192626
stage2/lightningdit-xl-spatialpe-vit-g-bf16/checkpoints/0050000.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:2efceb9187404edb8aecff939bfa976eb34be22938ab730f244944ed2389e38f
3
+ size 19268192626
stage2/lightningdit-xl-spatialpe-vit-g-bf16/log.txt ADDED
@@ -0,0 +1,967 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [2025-10-28 00:21:17] Experiment directory created at results/stage2/hfdata/lightningdit-xl-spatialpe-vit-g-bf16
2
+ [2025-10-28 00:21:39] Missing keys for loading vision encoder: []
3
+ [2025-10-28 00:21:39] Unexpected keys for loading vision encoder: []
4
+ [2025-10-28 00:21:55] Model Parameters: 1204.40M
5
+ [2025-10-28 00:22:01] Dataset contains 1,281,167 images (/scratch/xingjian.leng/data/train)
6
+ [2025-10-28 00:22:01] Gradient accumulation: steps=1, micro batch=128, per-GPU batch=128, global batch=1024
7
+ [2025-10-28 00:22:01] Precision mode: bf16
8
+ [2025-10-28 00:22:01] Training configured for 80 epochs, 1251 steps per epoch.
9
+ [2025-10-28 00:22:01] Optimizer: ADAMW with lr=0.0002, betas=(0.9, 0.95), weight_decay=0.0, eps=1e-08
10
+ Scheduler: linear with warmup_steps=0, decay_end_steps=0, final_lr=0.0002
11
+ [2025-10-28 00:22:01] Training for 80 epochs...
12
+ [2025-10-28 00:22:01] Beginning epoch 0...
13
+ [2025-10-28 00:53:57] Experiment directory created at results/stage2/hfdata/lightningdit-xl-spatialpe-vit-g-bf16
14
+ [2025-10-28 00:54:18] Missing keys for loading vision encoder: []
15
+ [2025-10-28 00:54:18] Unexpected keys for loading vision encoder: []
16
+ [2025-10-28 00:54:36] Model Parameters: 1204.40M
17
+ [2025-10-28 00:54:40] Dataset contains 1,281,167 images (/scratch/xingjian.leng/data/spatialpe-vit-g_hfdataset_precentercrop_True_train_bfloat16)
18
+ [2025-10-28 00:54:40] Gradient accumulation: steps=1, micro batch=128, per-GPU batch=128, global batch=1024
19
+ [2025-10-28 00:54:40] Precision mode: bf16
20
+ [2025-10-28 00:54:40] Training configured for 80 epochs, 1251 steps per epoch.
21
+ [2025-10-28 00:54:40] Optimizer: ADAMW with lr=0.0002, betas=(0.9, 0.95), weight_decay=0.0, eps=1e-08
22
+ Scheduler: linear with warmup_steps=0, decay_end_steps=0, final_lr=0.0002
23
+ [2025-10-28 00:54:41] Training for 80 epochs...
24
+ [2025-10-28 00:54:41] Beginning epoch 0...
25
+ [2025-10-28 00:54:52] Generating EMA samples...
26
+ [2025-10-28 00:55:21] Generating EMA samples done.
27
+ [2025-10-28 00:56:49] (step=0000100) Train Loss: 1.6467, Train Steps/Sec: 0.78
28
+ [2025-10-28 00:58:17] (step=0000200) Train Loss: 1.2729, Train Steps/Sec: 1.13
29
+ [2025-10-28 00:59:45] (step=0000300) Train Loss: 1.1285, Train Steps/Sec: 1.13
30
+ [2025-10-28 01:01:14] (step=0000400) Train Loss: 1.0258, Train Steps/Sec: 1.13
31
+ [2025-10-28 01:02:42] (step=0000500) Train Loss: 0.9680, Train Steps/Sec: 1.13
32
+ [2025-10-28 01:04:10] (step=0000600) Train Loss: 0.9305, Train Steps/Sec: 1.13
33
+ [2025-10-28 01:05:38] (step=0000700) Train Loss: 0.9013, Train Steps/Sec: 1.13
34
+ [2025-10-28 01:07:07] (step=0000800) Train Loss: 0.8809, Train Steps/Sec: 1.13
35
+ [2025-10-28 01:08:35] (step=0000900) Train Loss: 0.8634, Train Steps/Sec: 1.13
36
+ [2025-10-28 01:10:03] (step=0001000) Train Loss: 0.8494, Train Steps/Sec: 1.13
37
+ [2025-10-28 01:11:31] (step=0001100) Train Loss: 0.8368, Train Steps/Sec: 1.13
38
+ [2025-10-28 01:13:00] (step=0001200) Train Loss: 0.8263, Train Steps/Sec: 1.13
39
+ [2025-10-28 01:13:46] Beginning epoch 1...
40
+ [2025-10-28 01:14:32] (step=0001300) Train Loss: 0.8144, Train Steps/Sec: 1.08
41
+ [2025-10-28 01:16:00] (step=0001400) Train Loss: 0.8063, Train Steps/Sec: 1.13
42
+ [2025-10-28 01:17:29] (step=0001500) Train Loss: 0.7979, Train Steps/Sec: 1.13
43
+ [2025-10-28 01:18:57] (step=0001600) Train Loss: 0.7920, Train Steps/Sec: 1.13
44
+ [2025-10-28 01:20:25] (step=0001700) Train Loss: 0.7843, Train Steps/Sec: 1.13
45
+ [2025-10-28 01:21:54] (step=0001800) Train Loss: 0.7783, Train Steps/Sec: 1.13
46
+ [2025-10-28 01:23:22] (step=0001900) Train Loss: 0.7735, Train Steps/Sec: 1.13
47
+ [2025-10-28 01:24:50] (step=0002000) Train Loss: 0.7679, Train Steps/Sec: 1.13
48
+ [2025-10-28 01:26:18] (step=0002100) Train Loss: 0.7632, Train Steps/Sec: 1.13
49
+ [2025-10-28 01:27:47] (step=0002200) Train Loss: 0.7598, Train Steps/Sec: 1.13
50
+ [2025-10-28 01:29:15] (step=0002300) Train Loss: 0.7543, Train Steps/Sec: 1.13
51
+ [2025-10-28 01:30:43] (step=0002400) Train Loss: 0.7508, Train Steps/Sec: 1.13
52
+ [2025-10-28 01:32:11] (step=0002500) Train Loss: 0.7472, Train Steps/Sec: 1.13
53
+ [2025-10-28 01:32:14] Beginning epoch 2...
54
+ [2025-10-28 01:33:44] (step=0002600) Train Loss: 0.7452, Train Steps/Sec: 1.08
55
+ [2025-10-28 01:35:13] (step=0002700) Train Loss: 0.7403, Train Steps/Sec: 1.13
56
+ [2025-10-28 01:36:41] (step=0002800) Train Loss: 0.7364, Train Steps/Sec: 1.13
57
+ [2025-10-28 01:38:09] (step=0002900) Train Loss: 0.7343, Train Steps/Sec: 1.13
58
+ [2025-10-28 01:39:37] (step=0003000) Train Loss: 0.7326, Train Steps/Sec: 1.13
59
+ [2025-10-28 01:41:06] (step=0003100) Train Loss: 0.7286, Train Steps/Sec: 1.13
60
+ [2025-10-28 01:42:34] (step=0003200) Train Loss: 0.7265, Train Steps/Sec: 1.13
61
+ [2025-10-28 01:44:02] (step=0003300) Train Loss: 0.7241, Train Steps/Sec: 1.13
62
+ [2025-10-28 01:45:30] (step=0003400) Train Loss: 0.7216, Train Steps/Sec: 1.13
63
+ [2025-10-28 01:46:58] (step=0003500) Train Loss: 0.7196, Train Steps/Sec: 1.13
64
+ [2025-10-28 01:48:27] (step=0003600) Train Loss: 0.7174, Train Steps/Sec: 1.13
65
+ [2025-10-28 01:49:55] (step=0003700) Train Loss: 0.7139, Train Steps/Sec: 1.13
66
+ [2025-10-28 01:50:42] Beginning epoch 3...
67
+ [2025-10-28 01:51:27] (step=0003800) Train Loss: 0.7134, Train Steps/Sec: 1.08
68
+ [2025-10-28 01:52:55] (step=0003900) Train Loss: 0.7109, Train Steps/Sec: 1.13
69
+ [2025-10-28 01:54:24] (step=0004000) Train Loss: 0.7099, Train Steps/Sec: 1.13
70
+ [2025-10-28 01:55:52] (step=0004100) Train Loss: 0.7072, Train Steps/Sec: 1.13
71
+ [2025-10-28 01:57:20] (step=0004200) Train Loss: 0.7056, Train Steps/Sec: 1.13
72
+ [2025-10-28 01:58:48] (step=0004300) Train Loss: 0.7053, Train Steps/Sec: 1.13
73
+ [2025-10-28 02:00:17] (step=0004400) Train Loss: 0.7026, Train Steps/Sec: 1.13
74
+ [2025-10-28 02:01:45] (step=0004500) Train Loss: 0.7022, Train Steps/Sec: 1.13
75
+ [2025-10-28 02:03:13] (step=0004600) Train Loss: 0.6998, Train Steps/Sec: 1.13
76
+ [2025-10-28 02:04:41] (step=0004700) Train Loss: 0.6991, Train Steps/Sec: 1.13
77
+ [2025-10-28 02:06:10] (step=0004800) Train Loss: 0.6981, Train Steps/Sec: 1.13
78
+ [2025-10-28 02:07:38] (step=0004900) Train Loss: 0.6953, Train Steps/Sec: 1.13
79
+ [2025-10-28 02:09:06] (step=0005000) Train Loss: 0.6943, Train Steps/Sec: 1.13
80
+ [2025-10-28 02:09:10] Beginning epoch 4...
81
+ [2025-10-28 02:10:38] (step=0005100) Train Loss: 0.6928, Train Steps/Sec: 1.09
82
+ [2025-10-28 02:12:06] (step=0005200) Train Loss: 0.6915, Train Steps/Sec: 1.13
83
+ [2025-10-28 02:13:35] (step=0005300) Train Loss: 0.6908, Train Steps/Sec: 1.13
84
+ [2025-10-28 02:15:03] (step=0005400) Train Loss: 0.6895, Train Steps/Sec: 1.13
85
+ [2025-10-28 02:16:31] (step=0005500) Train Loss: 0.6878, Train Steps/Sec: 1.13
86
+ [2025-10-28 02:17:59] (step=0005600) Train Loss: 0.6867, Train Steps/Sec: 1.13
87
+ [2025-10-28 02:19:28] (step=0005700) Train Loss: 0.6863, Train Steps/Sec: 1.13
88
+ [2025-10-28 02:20:56] (step=0005800) Train Loss: 0.6855, Train Steps/Sec: 1.13
89
+ [2025-10-28 02:22:24] (step=0005900) Train Loss: 0.6830, Train Steps/Sec: 1.13
90
+ [2025-10-28 02:23:52] (step=0006000) Train Loss: 0.6835, Train Steps/Sec: 1.13
91
+ [2025-10-28 02:25:21] (step=0006100) Train Loss: 0.6826, Train Steps/Sec: 1.13
92
+ [2025-10-28 02:26:49] (step=0006200) Train Loss: 0.6804, Train Steps/Sec: 1.13
93
+ [2025-10-28 02:27:38] Beginning epoch 5...
94
+ [2025-10-28 02:28:21] (step=0006300) Train Loss: 0.6793, Train Steps/Sec: 1.08
95
+ [2025-10-28 02:29:49] (step=0006400) Train Loss: 0.6804, Train Steps/Sec: 1.13
96
+ [2025-10-28 02:31:17] (step=0006500) Train Loss: 0.6790, Train Steps/Sec: 1.13
97
+ [2025-10-28 02:32:46] (step=0006600) Train Loss: 0.6786, Train Steps/Sec: 1.13
98
+ [2025-10-28 02:34:14] (step=0006700) Train Loss: 0.6768, Train Steps/Sec: 1.13
99
+ [2025-10-28 02:35:42] (step=0006800) Train Loss: 0.6757, Train Steps/Sec: 1.13
100
+ [2025-10-28 02:37:10] (step=0006900) Train Loss: 0.6750, Train Steps/Sec: 1.13
101
+ [2025-10-28 02:38:39] (step=0007000) Train Loss: 0.6742, Train Steps/Sec: 1.13
102
+ [2025-10-28 02:40:07] (step=0007100) Train Loss: 0.6740, Train Steps/Sec: 1.13
103
+ [2025-10-28 02:41:36] (step=0007200) Train Loss: 0.6729, Train Steps/Sec: 1.13
104
+ [2025-10-28 02:43:04] (step=0007300) Train Loss: 0.6710, Train Steps/Sec: 1.13
105
+ [2025-10-28 02:44:32] (step=0007400) Train Loss: 0.6710, Train Steps/Sec: 1.13
106
+ [2025-10-28 02:46:00] (step=0007500) Train Loss: 0.6711, Train Steps/Sec: 1.13
107
+ [2025-10-28 02:46:06] Beginning epoch 6...
108
+ [2025-10-28 02:47:33] (step=0007600) Train Loss: 0.6697, Train Steps/Sec: 1.08
109
+ [2025-10-28 02:49:01] (step=0007700) Train Loss: 0.6690, Train Steps/Sec: 1.13
110
+ [2025-10-28 02:50:29] (step=0007800) Train Loss: 0.6689, Train Steps/Sec: 1.13
111
+ [2025-10-28 02:51:58] (step=0007900) Train Loss: 0.6681, Train Steps/Sec: 1.12
112
+ [2025-10-28 02:53:27] (step=0008000) Train Loss: 0.6663, Train Steps/Sec: 1.13
113
+ [2025-10-28 02:54:55] (step=0008100) Train Loss: 0.6675, Train Steps/Sec: 1.13
114
+ [2025-10-28 02:56:23] (step=0008200) Train Loss: 0.6660, Train Steps/Sec: 1.13
115
+ [2025-10-28 02:57:51] (step=0008300) Train Loss: 0.6654, Train Steps/Sec: 1.13
116
+ [2025-10-28 02:59:19] (step=0008400) Train Loss: 0.6652, Train Steps/Sec: 1.13
117
+ [2025-10-28 03:00:47] (step=0008500) Train Loss: 0.6633, Train Steps/Sec: 1.13
118
+ [2025-10-28 03:02:15] (step=0008600) Train Loss: 0.6641, Train Steps/Sec: 1.13
119
+ [2025-10-28 03:03:44] (step=0008700) Train Loss: 0.6649, Train Steps/Sec: 1.13
120
+ [2025-10-28 03:04:35] Beginning epoch 7...
121
+ [2025-10-28 03:05:17] (step=0008800) Train Loss: 0.6632, Train Steps/Sec: 1.08
122
+ [2025-10-28 03:06:45] (step=0008900) Train Loss: 0.6617, Train Steps/Sec: 1.13
123
+ [2025-10-28 03:08:13] (step=0009000) Train Loss: 0.6620, Train Steps/Sec: 1.13
124
+ [2025-10-28 03:09:41] (step=0009100) Train Loss: 0.6619, Train Steps/Sec: 1.13
125
+ [2025-10-28 03:11:09] (step=0009200) Train Loss: 0.6627, Train Steps/Sec: 1.13
126
+ [2025-10-28 03:12:37] (step=0009300) Train Loss: 0.6606, Train Steps/Sec: 1.13
127
+ [2025-10-28 03:14:06] (step=0009400) Train Loss: 0.6597, Train Steps/Sec: 1.13
128
+ [2025-10-28 03:15:34] (step=0009500) Train Loss: 0.6597, Train Steps/Sec: 1.13
129
+ [2025-10-28 03:17:03] (step=0009600) Train Loss: 0.6586, Train Steps/Sec: 1.12
130
+ [2025-10-28 03:18:31] (step=0009700) Train Loss: 0.6590, Train Steps/Sec: 1.13
131
+ [2025-10-28 03:19:59] (step=0009800) Train Loss: 0.6580, Train Steps/Sec: 1.13
132
+ [2025-10-28 03:21:27] (step=0009900) Train Loss: 0.6586, Train Steps/Sec: 1.13
133
+ [2025-10-28 03:22:55] (step=0010000) Train Loss: 0.6574, Train Steps/Sec: 1.13
134
+ [2025-10-28 03:23:03] Beginning epoch 8...
135
+ [2025-10-28 03:24:28] (step=0010100) Train Loss: 0.6546, Train Steps/Sec: 1.08
136
+ [2025-10-28 03:25:56] (step=0010200) Train Loss: 0.6576, Train Steps/Sec: 1.13
137
+ [2025-10-28 03:27:24] (step=0010300) Train Loss: 0.6554, Train Steps/Sec: 1.13
138
+ [2025-10-28 03:28:53] (step=0010400) Train Loss: 0.6555, Train Steps/Sec: 1.13
139
+ [2025-10-28 03:30:21] (step=0010500) Train Loss: 0.6551, Train Steps/Sec: 1.13
140
+ [2025-10-28 03:31:50] (step=0010600) Train Loss: 0.6548, Train Steps/Sec: 1.13
141
+ [2025-10-28 03:33:18] (step=0010700) Train Loss: 0.6542, Train Steps/Sec: 1.13
142
+ [2025-10-28 03:34:46] (step=0010800) Train Loss: 0.6531, Train Steps/Sec: 1.13
143
+ [2025-10-28 03:36:14] (step=0010900) Train Loss: 0.6550, Train Steps/Sec: 1.13
144
+ [2025-10-28 03:37:42] (step=0011000) Train Loss: 0.6528, Train Steps/Sec: 1.13
145
+ [2025-10-28 03:39:10] (step=0011100) Train Loss: 0.6522, Train Steps/Sec: 1.13
146
+ [2025-10-28 03:40:39] (step=0011200) Train Loss: 0.6531, Train Steps/Sec: 1.13
147
+ [2025-10-28 03:41:31] Beginning epoch 9...
148
+ [2025-10-28 03:42:11] (step=0011300) Train Loss: 0.6510, Train Steps/Sec: 1.08
149
+ [2025-10-28 03:43:40] (step=0011400) Train Loss: 0.6498, Train Steps/Sec: 1.13
150
+ [2025-10-28 03:45:08] (step=0011500) Train Loss: 0.6505, Train Steps/Sec: 1.13
151
+ [2025-10-28 03:46:36] (step=0011600) Train Loss: 0.6502, Train Steps/Sec: 1.13
152
+ [2025-10-28 03:48:04] (step=0011700) Train Loss: 0.6510, Train Steps/Sec: 1.13
153
+ [2025-10-28 03:49:32] (step=0011800) Train Loss: 0.6499, Train Steps/Sec: 1.13
154
+ [2025-10-28 03:51:00] (step=0011900) Train Loss: 0.6501, Train Steps/Sec: 1.13
155
+ [2025-10-28 03:52:29] (step=0012000) Train Loss: 0.6498, Train Steps/Sec: 1.13
156
+ [2025-10-28 03:53:57] (step=0012100) Train Loss: 0.6496, Train Steps/Sec: 1.13
157
+ [2025-10-28 03:55:25] (step=0012200) Train Loss: 0.6475, Train Steps/Sec: 1.13
158
+ [2025-10-28 03:56:54] (step=0012300) Train Loss: 0.6481, Train Steps/Sec: 1.13
159
+ [2025-10-28 03:58:22] (step=0012400) Train Loss: 0.6480, Train Steps/Sec: 1.13
160
+ [2025-10-28 03:59:50] (step=0012500) Train Loss: 0.6485, Train Steps/Sec: 1.13
161
+ [2025-10-28 03:59:59] Beginning epoch 10...
162
+ [2025-10-28 04:01:22] (step=0012600) Train Loss: 0.6469, Train Steps/Sec: 1.08
163
+ [2025-10-28 04:02:50] (step=0012700) Train Loss: 0.6476, Train Steps/Sec: 1.13
164
+ [2025-10-28 04:04:19] (step=0012800) Train Loss: 0.6462, Train Steps/Sec: 1.13
165
+ [2025-10-28 04:05:47] (step=0012900) Train Loss: 0.6465, Train Steps/Sec: 1.13
166
+ [2025-10-28 04:07:15] (step=0013000) Train Loss: 0.6462, Train Steps/Sec: 1.13
167
+ [2025-10-28 04:08:44] (step=0013100) Train Loss: 0.6459, Train Steps/Sec: 1.13
168
+ [2025-10-28 04:10:12] (step=0013200) Train Loss: 0.6466, Train Steps/Sec: 1.13
169
+ [2025-10-28 04:11:40] (step=0013300) Train Loss: 0.6445, Train Steps/Sec: 1.13
170
+ [2025-10-28 04:13:08] (step=0013400) Train Loss: 0.6452, Train Steps/Sec: 1.13
171
+ [2025-10-28 04:14:37] (step=0013500) Train Loss: 0.6446, Train Steps/Sec: 1.13
172
+ [2025-10-28 04:16:05] (step=0013600) Train Loss: 0.6456, Train Steps/Sec: 1.13
173
+ [2025-10-28 04:17:33] (step=0013700) Train Loss: 0.6440, Train Steps/Sec: 1.13
174
+ [2025-10-28 04:18:27] Beginning epoch 11...
175
+ [2025-10-28 04:19:05] (step=0013800) Train Loss: 0.6437, Train Steps/Sec: 1.08
176
+ [2025-10-28 04:20:34] (step=0013900) Train Loss: 0.6437, Train Steps/Sec: 1.13
177
+ [2025-10-28 04:22:02] (step=0014000) Train Loss: 0.6426, Train Steps/Sec: 1.13
178
+ [2025-10-28 04:23:31] (step=0014100) Train Loss: 0.6432, Train Steps/Sec: 1.13
179
+ [2025-10-28 04:24:59] (step=0014200) Train Loss: 0.6430, Train Steps/Sec: 1.13
180
+ [2025-10-28 04:26:27] (step=0014300) Train Loss: 0.6429, Train Steps/Sec: 1.13
181
+ [2025-10-28 04:27:55] (step=0014400) Train Loss: 0.6420, Train Steps/Sec: 1.13
182
+ [2025-10-28 04:29:23] (step=0014500) Train Loss: 0.6418, Train Steps/Sec: 1.13
183
+ [2025-10-28 04:30:51] (step=0014600) Train Loss: 0.6419, Train Steps/Sec: 1.13
184
+ [2025-10-28 04:32:20] (step=0014700) Train Loss: 0.6424, Train Steps/Sec: 1.13
185
+ [2025-10-28 04:33:48] (step=0014800) Train Loss: 0.6415, Train Steps/Sec: 1.13
186
+ [2025-10-28 04:35:17] (step=0014900) Train Loss: 0.6423, Train Steps/Sec: 1.13
187
+ [2025-10-28 04:36:45] (step=0015000) Train Loss: 0.6396, Train Steps/Sec: 1.14
188
+ [2025-10-28 04:36:56] Beginning epoch 12...
189
+ [2025-10-28 04:38:17] (step=0015100) Train Loss: 0.6412, Train Steps/Sec: 1.09
190
+ [2025-10-28 04:39:45] (step=0015200) Train Loss: 0.6398, Train Steps/Sec: 1.13
191
+ [2025-10-28 04:41:13] (step=0015300) Train Loss: 0.6419, Train Steps/Sec: 1.13
192
+ [2025-10-28 04:42:41] (step=0015400) Train Loss: 0.6394, Train Steps/Sec: 1.13
193
+ [2025-10-28 04:44:09] (step=0015500) Train Loss: 0.6407, Train Steps/Sec: 1.13
194
+ [2025-10-28 04:45:38] (step=0015600) Train Loss: 0.6386, Train Steps/Sec: 1.13
195
+ [2025-10-28 04:47:07] (step=0015700) Train Loss: 0.6402, Train Steps/Sec: 1.13
196
+ [2025-10-28 04:48:35] (step=0015800) Train Loss: 0.6393, Train Steps/Sec: 1.13
197
+ [2025-10-28 04:50:03] (step=0015900) Train Loss: 0.6389, Train Steps/Sec: 1.13
198
+ [2025-10-28 04:51:31] (step=0016000) Train Loss: 0.6368, Train Steps/Sec: 1.13
199
+ [2025-10-28 04:52:59] (step=0016100) Train Loss: 0.6388, Train Steps/Sec: 1.13
200
+ [2025-10-28 04:54:27] (step=0016200) Train Loss: 0.6387, Train Steps/Sec: 1.13
201
+ [2025-10-28 04:55:24] Beginning epoch 13...
202
+ [2025-10-28 04:56:00] (step=0016300) Train Loss: 0.6379, Train Steps/Sec: 1.08
203
+ [2025-10-28 04:57:28] (step=0016400) Train Loss: 0.6376, Train Steps/Sec: 1.13
204
+ [2025-10-28 04:58:57] (step=0016500) Train Loss: 0.6372, Train Steps/Sec: 1.12
205
+ [2025-10-28 05:00:25] (step=0016600) Train Loss: 0.6386, Train Steps/Sec: 1.13
206
+ [2025-10-28 05:01:53] (step=0016700) Train Loss: 0.6349, Train Steps/Sec: 1.13
207
+ [2025-10-28 05:03:21] (step=0016800) Train Loss: 0.6376, Train Steps/Sec: 1.13
208
+ [2025-10-28 05:04:49] (step=0016900) Train Loss: 0.6372, Train Steps/Sec: 1.13
209
+ [2025-10-28 05:06:18] (step=0017000) Train Loss: 0.6366, Train Steps/Sec: 1.13
210
+ [2025-10-28 05:07:46] (step=0017100) Train Loss: 0.6371, Train Steps/Sec: 1.13
211
+ [2025-10-28 05:09:14] (step=0017200) Train Loss: 0.6364, Train Steps/Sec: 1.13
212
+ [2025-10-28 05:10:42] (step=0017300) Train Loss: 0.6362, Train Steps/Sec: 1.13
213
+ [2025-10-28 05:12:11] (step=0017400) Train Loss: 0.6338, Train Steps/Sec: 1.13
214
+ [2025-10-28 05:13:39] (step=0017500) Train Loss: 0.6364, Train Steps/Sec: 1.14
215
+ [2025-10-28 05:13:52] Beginning epoch 14...
216
+ [2025-10-28 05:15:11] (step=0017600) Train Loss: 0.6349, Train Steps/Sec: 1.08
217
+ [2025-10-28 05:16:39] (step=0017700) Train Loss: 0.6349, Train Steps/Sec: 1.13
218
+ [2025-10-28 05:18:07] (step=0017800) Train Loss: 0.6342, Train Steps/Sec: 1.13
219
+ [2025-10-28 05:19:36] (step=0017900) Train Loss: 0.6349, Train Steps/Sec: 1.13
220
+ [2025-10-28 05:21:04] (step=0018000) Train Loss: 0.6350, Train Steps/Sec: 1.13
221
+ [2025-10-28 05:22:32] (step=0018100) Train Loss: 0.6350, Train Steps/Sec: 1.13
222
+ [2025-10-28 05:24:01] (step=0018200) Train Loss: 0.6348, Train Steps/Sec: 1.13
223
+ [2025-10-28 05:25:29] (step=0018300) Train Loss: 0.6347, Train Steps/Sec: 1.13
224
+ [2025-10-28 05:26:57] (step=0018400) Train Loss: 0.6344, Train Steps/Sec: 1.14
225
+ [2025-10-28 05:28:25] (step=0018500) Train Loss: 0.6341, Train Steps/Sec: 1.13
226
+ [2025-10-28 05:29:53] (step=0018600) Train Loss: 0.6328, Train Steps/Sec: 1.13
227
+ [2025-10-28 05:31:21] (step=0018700) Train Loss: 0.6325, Train Steps/Sec: 1.13
228
+ [2025-10-28 05:32:19] Beginning epoch 15...
229
+ [2025-10-28 05:32:54] (step=0018800) Train Loss: 0.6343, Train Steps/Sec: 1.08
230
+ [2025-10-28 05:34:22] (step=0018900) Train Loss: 0.6322, Train Steps/Sec: 1.13
231
+ [2025-10-28 05:35:50] (step=0019000) Train Loss: 0.6319, Train Steps/Sec: 1.13
232
+ [2025-10-28 05:37:19] (step=0019100) Train Loss: 0.6316, Train Steps/Sec: 1.13
233
+ [2025-10-28 05:38:47] (step=0019200) Train Loss: 0.6314, Train Steps/Sec: 1.14
234
+ [2025-10-28 05:40:15] (step=0019300) Train Loss: 0.6320, Train Steps/Sec: 1.14
235
+ [2025-10-28 05:41:43] (step=0019400) Train Loss: 0.6315, Train Steps/Sec: 1.14
236
+ [2025-10-28 05:43:12] (step=0019500) Train Loss: 0.6316, Train Steps/Sec: 1.14
237
+ [2025-10-28 05:44:40] (step=0019600) Train Loss: 0.6315, Train Steps/Sec: 1.13
238
+ [2025-10-28 05:46:08] (step=0019700) Train Loss: 0.6298, Train Steps/Sec: 1.14
239
+ [2025-10-28 05:47:36] (step=0019800) Train Loss: 0.6320, Train Steps/Sec: 1.13
240
+ [2025-10-28 05:49:04] (step=0019900) Train Loss: 0.6316, Train Steps/Sec: 1.13
241
+ [2025-10-28 05:50:33] (step=0020000) Train Loss: 0.6305, Train Steps/Sec: 1.13
242
+ [2025-10-28 05:50:47] Beginning epoch 16...
243
+ [2025-10-28 05:52:05] (step=0020100) Train Loss: 0.6315, Train Steps/Sec: 1.08
244
+ [2025-10-28 05:53:33] (step=0020200) Train Loss: 0.6302, Train Steps/Sec: 1.14
245
+ [2025-10-28 05:55:01] (step=0020300) Train Loss: 0.6309, Train Steps/Sec: 1.13
246
+ [2025-10-28 05:56:30] (step=0020400) Train Loss: 0.6304, Train Steps/Sec: 1.13
247
+ [2025-10-28 05:57:58] (step=0020500) Train Loss: 0.6301, Train Steps/Sec: 1.13
248
+ [2025-10-28 05:59:26] (step=0020600) Train Loss: 0.6294, Train Steps/Sec: 1.13
249
+ [2025-10-28 06:00:54] (step=0020700) Train Loss: 0.6307, Train Steps/Sec: 1.13
250
+ [2025-10-28 06:02:23] (step=0020800) Train Loss: 0.6294, Train Steps/Sec: 1.12
251
+ [2025-10-28 06:03:51] (step=0020900) Train Loss: 0.6306, Train Steps/Sec: 1.13
252
+ [2025-10-28 06:05:19] (step=0021000) Train Loss: 0.6300, Train Steps/Sec: 1.14
253
+ [2025-10-28 06:06:47] (step=0021100) Train Loss: 0.6280, Train Steps/Sec: 1.13
254
+ [2025-10-28 06:08:16] (step=0021200) Train Loss: 0.6287, Train Steps/Sec: 1.13
255
+ [2025-10-28 06:09:15] Beginning epoch 17...
256
+ [2025-10-28 06:09:48] (step=0021300) Train Loss: 0.6290, Train Steps/Sec: 1.08
257
+ [2025-10-28 06:11:16] (step=0021400) Train Loss: 0.6286, Train Steps/Sec: 1.13
258
+ [2025-10-28 06:12:44] (step=0021500) Train Loss: 0.6289, Train Steps/Sec: 1.13
259
+ [2025-10-28 06:14:12] (step=0021600) Train Loss: 0.6297, Train Steps/Sec: 1.13
260
+ [2025-10-28 06:15:41] (step=0021700) Train Loss: 0.6299, Train Steps/Sec: 1.13
261
+ [2025-10-28 06:17:09] (step=0021800) Train Loss: 0.6293, Train Steps/Sec: 1.13
262
+ [2025-10-28 06:18:38] (step=0021900) Train Loss: 0.6270, Train Steps/Sec: 1.13
263
+ [2025-10-28 06:20:06] (step=0022000) Train Loss: 0.6276, Train Steps/Sec: 1.13
264
+ [2025-10-28 06:21:34] (step=0022100) Train Loss: 0.6285, Train Steps/Sec: 1.13
265
+ [2025-10-28 06:23:02] (step=0022200) Train Loss: 0.6283, Train Steps/Sec: 1.13
266
+ [2025-10-28 06:24:30] (step=0022300) Train Loss: 0.6266, Train Steps/Sec: 1.13
267
+ [2025-10-28 06:25:59] (step=0022400) Train Loss: 0.6267, Train Steps/Sec: 1.13
268
+ [2025-10-28 06:27:27] (step=0022500) Train Loss: 0.6276, Train Steps/Sec: 1.13
269
+ [2025-10-28 06:27:44] Beginning epoch 18...
270
+ [2025-10-28 06:29:00] (step=0022600) Train Loss: 0.6264, Train Steps/Sec: 1.07
271
+ [2025-10-28 06:30:28] (step=0022700) Train Loss: 0.6271, Train Steps/Sec: 1.13
272
+ [2025-10-28 06:31:57] (step=0022800) Train Loss: 0.6280, Train Steps/Sec: 1.13
273
+ [2025-10-28 06:33:25] (step=0022900) Train Loss: 0.6261, Train Steps/Sec: 1.13
274
+ [2025-10-28 06:34:53] (step=0023000) Train Loss: 0.6253, Train Steps/Sec: 1.13
275
+ [2025-10-28 06:36:21] (step=0023100) Train Loss: 0.6253, Train Steps/Sec: 1.13
276
+ [2025-10-28 06:37:49] (step=0023200) Train Loss: 0.6273, Train Steps/Sec: 1.13
277
+ [2025-10-28 06:39:18] (step=0023300) Train Loss: 0.6282, Train Steps/Sec: 1.13
278
+ [2025-10-28 06:40:46] (step=0023400) Train Loss: 0.6258, Train Steps/Sec: 1.13
279
+ [2025-10-28 06:42:15] (step=0023500) Train Loss: 0.6261, Train Steps/Sec: 1.13
280
+ [2025-10-28 06:43:43] (step=0023600) Train Loss: 0.6269, Train Steps/Sec: 1.13
281
+ [2025-10-28 06:45:11] (step=0023700) Train Loss: 0.6246, Train Steps/Sec: 1.13
282
+ [2025-10-28 06:46:12] Beginning epoch 19...
283
+ [2025-10-28 06:46:44] (step=0023800) Train Loss: 0.6247, Train Steps/Sec: 1.08
284
+ [2025-10-28 06:48:12] (step=0023900) Train Loss: 0.6260, Train Steps/Sec: 1.13
285
+ [2025-10-28 06:49:40] (step=0024000) Train Loss: 0.6254, Train Steps/Sec: 1.13
286
+ [2025-10-28 06:51:08] (step=0024100) Train Loss: 0.6239, Train Steps/Sec: 1.13
287
+ [2025-10-28 06:52:37] (step=0024200) Train Loss: 0.6239, Train Steps/Sec: 1.13
288
+ [2025-10-28 06:54:06] (step=0024300) Train Loss: 0.6246, Train Steps/Sec: 1.12
289
+ [2025-10-28 06:55:34] (step=0024400) Train Loss: 0.6266, Train Steps/Sec: 1.13
290
+ [2025-10-28 06:57:02] (step=0024500) Train Loss: 0.6251, Train Steps/Sec: 1.13
291
+ [2025-10-28 06:58:30] (step=0024600) Train Loss: 0.6253, Train Steps/Sec: 1.13
292
+ [2025-10-28 06:59:58] (step=0024700) Train Loss: 0.6251, Train Steps/Sec: 1.13
293
+ [2025-10-28 07:01:27] (step=0024800) Train Loss: 0.6234, Train Steps/Sec: 1.13
294
+ [2025-10-28 07:02:55] (step=0024900) Train Loss: 0.6241, Train Steps/Sec: 1.13
295
+ [2025-10-28 07:04:23] (step=0025000) Train Loss: 0.6254, Train Steps/Sec: 1.13
296
+ [2025-10-28 07:05:16] Saved checkpoint to results/stage2/hfdata/lightningdit-xl-spatialpe-vit-g-bf16/checkpoints/0025000.pt
297
+ [2025-10-28 07:05:16] Generating EMA samples...
298
+ [2025-10-28 07:05:44] Generating EMA samples done.
299
+ [2025-10-28 07:06:02] Beginning epoch 20...
300
+ [2025-10-28 07:07:19] (step=0025100) Train Loss: 0.6230, Train Steps/Sec: 0.57
301
+ [2025-10-28 07:08:47] (step=0025200) Train Loss: 0.6256, Train Steps/Sec: 1.13
302
+ [2025-10-28 07:10:15] (step=0025300) Train Loss: 0.6237, Train Steps/Sec: 1.13
303
+ [2025-10-28 07:11:43] (step=0025400) Train Loss: 0.6248, Train Steps/Sec: 1.13
304
+ [2025-10-28 07:13:12] (step=0025500) Train Loss: 0.6239, Train Steps/Sec: 1.13
305
+ [2025-10-28 07:14:40] (step=0025600) Train Loss: 0.6244, Train Steps/Sec: 1.13
306
+ [2025-10-28 07:16:08] (step=0025700) Train Loss: 0.6225, Train Steps/Sec: 1.13
307
+ [2025-10-28 07:17:36] (step=0025800) Train Loss: 0.6226, Train Steps/Sec: 1.13
308
+ [2025-10-28 07:19:05] (step=0025900) Train Loss: 0.6219, Train Steps/Sec: 1.13
309
+ [2025-10-28 07:20:33] (step=0026000) Train Loss: 0.6232, Train Steps/Sec: 1.13
310
+ [2025-10-28 07:22:01] (step=0026100) Train Loss: 0.6223, Train Steps/Sec: 1.13
311
+ [2025-10-28 07:23:29] (step=0026200) Train Loss: 0.6219, Train Steps/Sec: 1.13
312
+ [2025-10-28 07:24:33] Beginning epoch 21...
313
+ [2025-10-28 07:25:03] (step=0026300) Train Loss: 0.6226, Train Steps/Sec: 1.06
314
+ [2025-10-28 07:26:32] (step=0026400) Train Loss: 0.6217, Train Steps/Sec: 1.13
315
+ [2025-10-28 07:28:00] (step=0026500) Train Loss: 0.6226, Train Steps/Sec: 1.13
316
+ [2025-10-28 07:29:28] (step=0026600) Train Loss: 0.6232, Train Steps/Sec: 1.13
317
+ [2025-10-28 07:30:56] (step=0026700) Train Loss: 0.6232, Train Steps/Sec: 1.13
318
+ [2025-10-28 07:32:25] (step=0026800) Train Loss: 0.6212, Train Steps/Sec: 1.13
319
+ [2025-10-28 07:33:54] (step=0026900) Train Loss: 0.6229, Train Steps/Sec: 1.13
320
+ [2025-10-28 07:35:22] (step=0027000) Train Loss: 0.6219, Train Steps/Sec: 1.13
321
+ [2025-10-28 07:36:50] (step=0027100) Train Loss: 0.6225, Train Steps/Sec: 1.13
322
+ [2025-10-28 07:38:18] (step=0027200) Train Loss: 0.6208, Train Steps/Sec: 1.13
323
+ [2025-10-28 07:39:47] (step=0027300) Train Loss: 0.6220, Train Steps/Sec: 1.13
324
+ [2025-10-28 07:41:15] (step=0027400) Train Loss: 0.6211, Train Steps/Sec: 1.13
325
+ [2025-10-28 07:42:43] (step=0027500) Train Loss: 0.6218, Train Steps/Sec: 1.13
326
+ [2025-10-28 07:43:03] Beginning epoch 22...
327
+ [2025-10-28 07:44:17] (step=0027600) Train Loss: 0.6206, Train Steps/Sec: 1.06
328
+ [2025-10-28 07:45:46] (step=0027700) Train Loss: 0.6204, Train Steps/Sec: 1.13
329
+ [2025-10-28 07:47:14] (step=0027800) Train Loss: 0.6209, Train Steps/Sec: 1.13
330
+ [2025-10-28 07:48:42] (step=0027900) Train Loss: 0.6205, Train Steps/Sec: 1.13
331
+ [2025-10-28 07:50:10] (step=0028000) Train Loss: 0.6210, Train Steps/Sec: 1.13
332
+ [2025-10-28 07:51:38] (step=0028100) Train Loss: 0.6207, Train Steps/Sec: 1.13
333
+ [2025-10-28 07:53:07] (step=0028200) Train Loss: 0.6197, Train Steps/Sec: 1.13
334
+ [2025-10-28 07:54:35] (step=0028300) Train Loss: 0.6223, Train Steps/Sec: 1.13
335
+ [2025-10-28 07:56:03] (step=0028400) Train Loss: 0.6207, Train Steps/Sec: 1.13
336
+ [2025-10-28 07:57:31] (step=0028500) Train Loss: 0.6216, Train Steps/Sec: 1.13
337
+ [2025-10-28 07:59:00] (step=0028600) Train Loss: 0.6201, Train Steps/Sec: 1.13
338
+ [2025-10-28 08:00:28] (step=0028700) Train Loss: 0.6212, Train Steps/Sec: 1.14
339
+ [2025-10-28 08:01:33] Beginning epoch 23...
340
+ [2025-10-28 08:02:02] (step=0028800) Train Loss: 0.6197, Train Steps/Sec: 1.06
341
+ [2025-10-28 08:03:30] (step=0028900) Train Loss: 0.6197, Train Steps/Sec: 1.13
342
+ [2025-10-28 08:04:58] (step=0029000) Train Loss: 0.6210, Train Steps/Sec: 1.13
343
+ [2025-10-28 08:06:26] (step=0029100) Train Loss: 0.6204, Train Steps/Sec: 1.13
344
+ [2025-10-28 08:07:55] (step=0029200) Train Loss: 0.6204, Train Steps/Sec: 1.13
345
+ [2025-10-28 08:09:23] (step=0029300) Train Loss: 0.6207, Train Steps/Sec: 1.14
346
+ [2025-10-28 08:10:51] (step=0029400) Train Loss: 0.6183, Train Steps/Sec: 1.13
347
+ [2025-10-28 08:12:20] (step=0029500) Train Loss: 0.6204, Train Steps/Sec: 1.13
348
+ [2025-10-28 08:13:48] (step=0029600) Train Loss: 0.6204, Train Steps/Sec: 1.13
349
+ [2025-10-28 08:15:16] (step=0029700) Train Loss: 0.6193, Train Steps/Sec: 1.14
350
+ [2025-10-28 08:16:44] (step=0029800) Train Loss: 0.6176, Train Steps/Sec: 1.13
351
+ [2025-10-28 08:18:12] (step=0029900) Train Loss: 0.6210, Train Steps/Sec: 1.13
352
+ [2025-10-28 08:19:40] (step=0030000) Train Loss: 0.6184, Train Steps/Sec: 1.13
353
+ [2025-10-28 08:20:02] Beginning epoch 24...
354
+ [2025-10-28 08:21:14] (step=0030100) Train Loss: 0.6196, Train Steps/Sec: 1.07
355
+ [2025-10-28 08:22:42] (step=0030200) Train Loss: 0.6187, Train Steps/Sec: 1.13
356
+ [2025-10-28 08:24:11] (step=0030300) Train Loss: 0.6185, Train Steps/Sec: 1.12
357
+ [2025-10-28 08:25:39] (step=0030400) Train Loss: 0.6190, Train Steps/Sec: 1.14
358
+ [2025-10-28 08:27:07] (step=0030500) Train Loss: 0.6188, Train Steps/Sec: 1.13
359
+ [2025-10-28 08:28:35] (step=0030600) Train Loss: 0.6179, Train Steps/Sec: 1.14
360
+ [2025-10-28 08:30:03] (step=0030700) Train Loss: 0.6191, Train Steps/Sec: 1.13
361
+ [2025-10-28 08:31:32] (step=0030800) Train Loss: 0.6186, Train Steps/Sec: 1.13
362
+ [2025-10-28 08:33:00] (step=0030900) Train Loss: 0.6195, Train Steps/Sec: 1.13
363
+ [2025-10-28 08:34:28] (step=0031000) Train Loss: 0.6174, Train Steps/Sec: 1.13
364
+ [2025-10-28 08:35:56] (step=0031100) Train Loss: 0.6193, Train Steps/Sec: 1.13
365
+ [2025-10-28 08:37:25] (step=0031200) Train Loss: 0.6173, Train Steps/Sec: 1.13
366
+ [2025-10-28 08:38:31] Beginning epoch 25...
367
+ [2025-10-28 08:38:58] (step=0031300) Train Loss: 0.6201, Train Steps/Sec: 1.07
368
+ [2025-10-28 08:40:26] (step=0031400) Train Loss: 0.6174, Train Steps/Sec: 1.13
369
+ [2025-10-28 08:41:55] (step=0031500) Train Loss: 0.6172, Train Steps/Sec: 1.13
370
+ [2025-10-28 08:43:23] (step=0031600) Train Loss: 0.6191, Train Steps/Sec: 1.13
371
+ [2025-10-28 08:44:51] (step=0031700) Train Loss: 0.6172, Train Steps/Sec: 1.13
372
+ [2025-10-28 08:46:19] (step=0031800) Train Loss: 0.6167, Train Steps/Sec: 1.13
373
+ [2025-10-28 08:47:47] (step=0031900) Train Loss: 0.6161, Train Steps/Sec: 1.13
374
+ [2025-10-28 08:49:16] (step=0032000) Train Loss: 0.6171, Train Steps/Sec: 1.13
375
+ [2025-10-28 08:50:44] (step=0032100) Train Loss: 0.6175, Train Steps/Sec: 1.13
376
+ [2025-10-28 08:52:13] (step=0032200) Train Loss: 0.6168, Train Steps/Sec: 1.13
377
+ [2025-10-28 08:53:41] (step=0032300) Train Loss: 0.6180, Train Steps/Sec: 1.13
378
+ [2025-10-28 08:55:09] (step=0032400) Train Loss: 0.6164, Train Steps/Sec: 1.13
379
+ [2025-10-28 08:56:37] (step=0032500) Train Loss: 0.6182, Train Steps/Sec: 1.13
380
+ [2025-10-28 08:57:00] Beginning epoch 26...
381
+ [2025-10-28 08:58:10] (step=0032600) Train Loss: 0.6173, Train Steps/Sec: 1.07
382
+ [2025-10-28 08:59:38] (step=0032700) Train Loss: 0.6171, Train Steps/Sec: 1.13
383
+ [2025-10-28 09:01:07] (step=0032800) Train Loss: 0.6161, Train Steps/Sec: 1.13
384
+ [2025-10-28 09:02:36] (step=0032900) Train Loss: 0.6182, Train Steps/Sec: 1.12
385
+ [2025-10-28 09:04:04] (step=0033000) Train Loss: 0.6163, Train Steps/Sec: 1.13
386
+ [2025-10-28 09:05:32] (step=0033100) Train Loss: 0.6171, Train Steps/Sec: 1.14
387
+ [2025-10-28 09:07:00] (step=0033200) Train Loss: 0.6146, Train Steps/Sec: 1.13
388
+ [2025-10-28 09:08:28] (step=0033300) Train Loss: 0.6183, Train Steps/Sec: 1.13
389
+ [2025-10-28 09:09:56] (step=0033400) Train Loss: 0.6166, Train Steps/Sec: 1.13
390
+ [2025-10-28 09:11:25] (step=0033500) Train Loss: 0.6160, Train Steps/Sec: 1.13
391
+ [2025-10-28 09:12:53] (step=0033600) Train Loss: 0.6164, Train Steps/Sec: 1.13
392
+ [2025-10-28 09:14:21] (step=0033700) Train Loss: 0.6154, Train Steps/Sec: 1.13
393
+ [2025-10-28 09:15:30] Beginning epoch 27...
394
+ [2025-10-28 09:15:54] (step=0033800) Train Loss: 0.6158, Train Steps/Sec: 1.07
395
+ [2025-10-28 09:17:23] (step=0033900) Train Loss: 0.6157, Train Steps/Sec: 1.13
396
+ [2025-10-28 09:18:51] (step=0034000) Train Loss: 0.6159, Train Steps/Sec: 1.13
397
+ [2025-10-28 09:20:19] (step=0034100) Train Loss: 0.6153, Train Steps/Sec: 1.13
398
+ [2025-10-28 09:21:47] (step=0034200) Train Loss: 0.6168, Train Steps/Sec: 1.13
399
+ [2025-10-28 09:23:15] (step=0034300) Train Loss: 0.6142, Train Steps/Sec: 1.13
400
+ [2025-10-28 09:24:44] (step=0034400) Train Loss: 0.6138, Train Steps/Sec: 1.13
401
+ [2025-10-28 09:26:12] (step=0034500) Train Loss: 0.6157, Train Steps/Sec: 1.13
402
+ [2025-10-28 09:27:41] (step=0034600) Train Loss: 0.6171, Train Steps/Sec: 1.13
403
+ [2025-10-28 09:29:09] (step=0034700) Train Loss: 0.6165, Train Steps/Sec: 1.13
404
+ [2025-10-28 09:30:37] (step=0034800) Train Loss: 0.6148, Train Steps/Sec: 1.13
405
+ [2025-10-28 09:32:05] (step=0034900) Train Loss: 0.6143, Train Steps/Sec: 1.13
406
+ [2025-10-28 09:33:34] (step=0035000) Train Loss: 0.6129, Train Steps/Sec: 1.13
407
+ [2025-10-28 09:33:59] Beginning epoch 28...
408
+ [2025-10-28 09:35:07] (step=0035100) Train Loss: 0.6157, Train Steps/Sec: 1.07
409
+ [2025-10-28 09:36:36] (step=0035200) Train Loss: 0.6147, Train Steps/Sec: 1.13
410
+ [2025-10-28 09:38:04] (step=0035300) Train Loss: 0.6135, Train Steps/Sec: 1.13
411
+ [2025-10-28 09:39:32] (step=0035400) Train Loss: 0.6167, Train Steps/Sec: 1.13
412
+ [2025-10-28 09:41:01] (step=0035500) Train Loss: 0.6127, Train Steps/Sec: 1.12
413
+ [2025-10-28 09:42:29] (step=0035600) Train Loss: 0.6131, Train Steps/Sec: 1.13
414
+ [2025-10-28 09:43:57] (step=0035700) Train Loss: 0.6148, Train Steps/Sec: 1.13
415
+ [2025-10-28 09:45:25] (step=0035800) Train Loss: 0.6143, Train Steps/Sec: 1.13
416
+ [2025-10-28 09:46:54] (step=0035900) Train Loss: 0.6140, Train Steps/Sec: 1.13
417
+ [2025-10-28 09:48:22] (step=0036000) Train Loss: 0.6146, Train Steps/Sec: 1.13
418
+ [2025-10-28 09:49:50] (step=0036100) Train Loss: 0.6137, Train Steps/Sec: 1.13
419
+ [2025-10-28 09:51:18] (step=0036200) Train Loss: 0.6140, Train Steps/Sec: 1.13
420
+ [2025-10-28 09:52:29] Beginning epoch 29...
421
+ [2025-10-28 09:52:53] (step=0036300) Train Loss: 0.6143, Train Steps/Sec: 1.05
422
+ [2025-10-28 09:54:22] (step=0036400) Train Loss: 0.6139, Train Steps/Sec: 1.13
423
+ [2025-10-28 09:55:50] (step=0036500) Train Loss: 0.6147, Train Steps/Sec: 1.13
424
+ [2025-10-28 09:57:18] (step=0036600) Train Loss: 0.6128, Train Steps/Sec: 1.13
425
+ [2025-10-28 09:58:46] (step=0036700) Train Loss: 0.6130, Train Steps/Sec: 1.13
426
+ [2025-10-28 10:00:15] (step=0036800) Train Loss: 0.6144, Train Steps/Sec: 1.13
427
+ [2025-10-28 10:01:43] (step=0036900) Train Loss: 0.6138, Train Steps/Sec: 1.13
428
+ [2025-10-28 10:03:11] (step=0037000) Train Loss: 0.6131, Train Steps/Sec: 1.13
429
+ [2025-10-28 10:04:39] (step=0037100) Train Loss: 0.6143, Train Steps/Sec: 1.13
430
+ [2025-10-28 10:06:08] (step=0037200) Train Loss: 0.6116, Train Steps/Sec: 1.13
431
+ [2025-10-28 10:07:36] (step=0037300) Train Loss: 0.6127, Train Steps/Sec: 1.13
432
+ [2025-10-28 10:09:04] (step=0037400) Train Loss: 0.6139, Train Steps/Sec: 1.13
433
+ [2025-10-28 10:10:32] (step=0037500) Train Loss: 0.6139, Train Steps/Sec: 1.13
434
+ [2025-10-28 10:10:59] Beginning epoch 30...
435
+ [2025-10-28 10:12:06] (step=0037600) Train Loss: 0.6143, Train Steps/Sec: 1.07
436
+ [2025-10-28 10:13:34] (step=0037700) Train Loss: 0.6123, Train Steps/Sec: 1.13
437
+ [2025-10-28 10:15:02] (step=0037800) Train Loss: 0.6135, Train Steps/Sec: 1.13
438
+ [2025-10-28 10:16:30] (step=0037900) Train Loss: 0.6126, Train Steps/Sec: 1.13
439
+ [2025-10-28 10:17:58] (step=0038000) Train Loss: 0.6124, Train Steps/Sec: 1.13
440
+ [2025-10-28 10:19:27] (step=0038100) Train Loss: 0.6123, Train Steps/Sec: 1.13
441
+ [2025-10-28 10:20:55] (step=0038200) Train Loss: 0.6132, Train Steps/Sec: 1.13
442
+ [2025-10-28 10:22:24] (step=0038300) Train Loss: 0.6136, Train Steps/Sec: 1.13
443
+ [2025-10-28 10:23:52] (step=0038400) Train Loss: 0.6122, Train Steps/Sec: 1.13
444
+ [2025-10-28 10:25:20] (step=0038500) Train Loss: 0.6115, Train Steps/Sec: 1.13
445
+ [2025-10-28 10:26:48] (step=0038600) Train Loss: 0.6123, Train Steps/Sec: 1.13
446
+ [2025-10-28 10:28:16] (step=0038700) Train Loss: 0.6124, Train Steps/Sec: 1.13
447
+ [2025-10-28 10:29:28] Beginning epoch 31...
448
+ [2025-10-28 10:29:50] (step=0038800) Train Loss: 0.6129, Train Steps/Sec: 1.07
449
+ [2025-10-28 10:31:19] (step=0038900) Train Loss: 0.6122, Train Steps/Sec: 1.13
450
+ [2025-10-28 10:32:47] (step=0039000) Train Loss: 0.6119, Train Steps/Sec: 1.13
451
+ [2025-10-28 10:34:15] (step=0039100) Train Loss: 0.6120, Train Steps/Sec: 1.13
452
+ [2025-10-28 10:35:43] (step=0039200) Train Loss: 0.6127, Train Steps/Sec: 1.13
453
+ [2025-10-28 10:37:11] (step=0039300) Train Loss: 0.6125, Train Steps/Sec: 1.13
454
+ [2025-10-28 10:38:40] (step=0039400) Train Loss: 0.6122, Train Steps/Sec: 1.13
455
+ [2025-10-28 10:40:08] (step=0039500) Train Loss: 0.6141, Train Steps/Sec: 1.13
456
+ [2025-10-28 10:41:36] (step=0039600) Train Loss: 0.6121, Train Steps/Sec: 1.13
457
+ [2025-10-28 10:43:04] (step=0039700) Train Loss: 0.6128, Train Steps/Sec: 1.14
458
+ [2025-10-28 10:44:33] (step=0039800) Train Loss: 0.6131, Train Steps/Sec: 1.13
459
+ [2025-10-28 10:46:01] (step=0039900) Train Loss: 0.6123, Train Steps/Sec: 1.13
460
+ [2025-10-28 10:47:29] (step=0040000) Train Loss: 0.6114, Train Steps/Sec: 1.13
461
+ [2025-10-28 10:47:58] Beginning epoch 32...
462
+ [2025-10-28 10:49:02] (step=0040100) Train Loss: 0.6120, Train Steps/Sec: 1.07
463
+ [2025-10-28 10:50:31] (step=0040200) Train Loss: 0.6122, Train Steps/Sec: 1.13
464
+ [2025-10-28 10:51:59] (step=0040300) Train Loss: 0.6118, Train Steps/Sec: 1.14
465
+ [2025-10-28 10:53:27] (step=0040400) Train Loss: 0.6111, Train Steps/Sec: 1.14
466
+ [2025-10-28 10:54:55] (step=0040500) Train Loss: 0.6115, Train Steps/Sec: 1.14
467
+ [2025-10-28 10:56:23] (step=0040600) Train Loss: 0.6140, Train Steps/Sec: 1.13
468
+ [2025-10-28 10:57:52] (step=0040700) Train Loss: 0.6114, Train Steps/Sec: 1.13
469
+ [2025-10-28 10:59:20] (step=0040800) Train Loss: 0.6126, Train Steps/Sec: 1.13
470
+ [2025-10-28 11:00:48] (step=0040900) Train Loss: 0.6101, Train Steps/Sec: 1.13
471
+ [2025-10-28 11:02:16] (step=0041000) Train Loss: 0.6097, Train Steps/Sec: 1.14
472
+ [2025-10-28 11:03:44] (step=0041100) Train Loss: 0.6113, Train Steps/Sec: 1.13
473
+ [2025-10-28 11:05:12] (step=0041200) Train Loss: 0.6121, Train Steps/Sec: 1.13
474
+ [2025-10-28 11:06:26] Beginning epoch 33...
475
+ [2025-10-28 11:06:46] (step=0041300) Train Loss: 0.6104, Train Steps/Sec: 1.07
476
+ [2025-10-28 11:08:14] (step=0041400) Train Loss: 0.6115, Train Steps/Sec: 1.13
477
+ [2025-10-28 11:09:43] (step=0041500) Train Loss: 0.6104, Train Steps/Sec: 1.12
478
+ [2025-10-28 11:11:12] (step=0041600) Train Loss: 0.6105, Train Steps/Sec: 1.13
479
+ [2025-10-28 11:12:40] (step=0041700) Train Loss: 0.6109, Train Steps/Sec: 1.14
480
+ [2025-10-28 11:14:08] (step=0041800) Train Loss: 0.6109, Train Steps/Sec: 1.13
481
+ [2025-10-28 11:15:36] (step=0041900) Train Loss: 0.6108, Train Steps/Sec: 1.13
482
+ [2025-10-28 11:17:04] (step=0042000) Train Loss: 0.6109, Train Steps/Sec: 1.13
483
+ [2025-10-28 11:18:32] (step=0042100) Train Loss: 0.6113, Train Steps/Sec: 1.13
484
+ [2025-10-28 11:20:00] (step=0042200) Train Loss: 0.6111, Train Steps/Sec: 1.13
485
+ [2025-10-28 11:21:29] (step=0042300) Train Loss: 0.6104, Train Steps/Sec: 1.13
486
+ [2025-10-28 11:22:57] (step=0042400) Train Loss: 0.6105, Train Steps/Sec: 1.13
487
+ [2025-10-28 11:24:25] (step=0042500) Train Loss: 0.6102, Train Steps/Sec: 1.13
488
+ [2025-10-28 11:24:56] Beginning epoch 34...
489
+ [2025-10-28 11:25:59] (step=0042600) Train Loss: 0.6113, Train Steps/Sec: 1.07
490
+ [2025-10-28 11:27:27] (step=0042700) Train Loss: 0.6102, Train Steps/Sec: 1.13
491
+ [2025-10-28 11:28:56] (step=0042800) Train Loss: 0.6095, Train Steps/Sec: 1.13
492
+ [2025-10-28 11:30:24] (step=0042900) Train Loss: 0.6112, Train Steps/Sec: 1.13
493
+ [2025-10-28 11:31:52] (step=0043000) Train Loss: 0.6100, Train Steps/Sec: 1.13
494
+ [2025-10-28 11:33:20] (step=0043100) Train Loss: 0.6120, Train Steps/Sec: 1.13
495
+ [2025-10-28 11:34:49] (step=0043200) Train Loss: 0.6102, Train Steps/Sec: 1.13
496
+ [2025-10-28 11:36:17] (step=0043300) Train Loss: 0.6098, Train Steps/Sec: 1.13
497
+ [2025-10-28 11:37:45] (step=0043400) Train Loss: 0.6086, Train Steps/Sec: 1.13
498
+ [2025-10-28 11:39:14] (step=0043500) Train Loss: 0.6084, Train Steps/Sec: 1.13
499
+ [2025-10-28 11:40:42] (step=0043600) Train Loss: 0.6096, Train Steps/Sec: 1.13
500
+ [2025-10-28 11:42:10] (step=0043700) Train Loss: 0.6083, Train Steps/Sec: 1.13
501
+ [2025-10-28 11:43:25] Beginning epoch 35...
502
+ [2025-10-28 11:43:44] (step=0043800) Train Loss: 0.6108, Train Steps/Sec: 1.07
503
+ [2025-10-28 11:45:12] (step=0043900) Train Loss: 0.6087, Train Steps/Sec: 1.13
504
+ [2025-10-28 11:46:40] (step=0044000) Train Loss: 0.6102, Train Steps/Sec: 1.13
505
+ [2025-10-28 11:48:09] (step=0044100) Train Loss: 0.6090, Train Steps/Sec: 1.13
506
+ [2025-10-28 11:49:37] (step=0044200) Train Loss: 0.6084, Train Steps/Sec: 1.13
507
+ [2025-10-28 11:51:05] (step=0044300) Train Loss: 0.6080, Train Steps/Sec: 1.13
508
+ [2025-10-28 11:52:34] (step=0044400) Train Loss: 0.6097, Train Steps/Sec: 1.13
509
+ [2025-10-28 11:54:02] (step=0044500) Train Loss: 0.6076, Train Steps/Sec: 1.13
510
+ [2025-10-28 11:55:30] (step=0044600) Train Loss: 0.6100, Train Steps/Sec: 1.13
511
+ [2025-10-28 11:56:58] (step=0044700) Train Loss: 0.6096, Train Steps/Sec: 1.13
512
+ [2025-10-28 11:58:26] (step=0044800) Train Loss: 0.6083, Train Steps/Sec: 1.13
513
+ [2025-10-28 11:59:55] (step=0044900) Train Loss: 0.6092, Train Steps/Sec: 1.13
514
+ [2025-10-28 12:01:23] (step=0045000) Train Loss: 0.6091, Train Steps/Sec: 1.13
515
+ [2025-10-28 12:01:55] Beginning epoch 36...
516
+ [2025-10-28 12:02:57] (step=0045100) Train Loss: 0.6082, Train Steps/Sec: 1.07
517
+ [2025-10-28 12:04:25] (step=0045200) Train Loss: 0.6090, Train Steps/Sec: 1.13
518
+ [2025-10-28 12:05:53] (step=0045300) Train Loss: 0.6081, Train Steps/Sec: 1.13
519
+ [2025-10-28 12:07:21] (step=0045400) Train Loss: 0.6091, Train Steps/Sec: 1.13
520
+ [2025-10-28 12:08:50] (step=0045500) Train Loss: 0.6080, Train Steps/Sec: 1.13
521
+ [2025-10-28 12:10:18] (step=0045600) Train Loss: 0.6084, Train Steps/Sec: 1.13
522
+ [2025-10-28 12:11:46] (step=0045700) Train Loss: 0.6097, Train Steps/Sec: 1.13
523
+ [2025-10-28 12:13:14] (step=0045800) Train Loss: 0.6080, Train Steps/Sec: 1.13
524
+ [2025-10-28 12:14:43] (step=0045900) Train Loss: 0.6093, Train Steps/Sec: 1.13
525
+ [2025-10-28 12:16:11] (step=0046000) Train Loss: 0.6083, Train Steps/Sec: 1.13
526
+ [2025-10-28 12:17:39] (step=0046100) Train Loss: 0.6086, Train Steps/Sec: 1.13
527
+ [2025-10-28 12:19:07] (step=0046200) Train Loss: 0.6085, Train Steps/Sec: 1.13
528
+ [2025-10-28 12:20:25] Beginning epoch 37...
529
+ [2025-10-28 12:20:41] (step=0046300) Train Loss: 0.6082, Train Steps/Sec: 1.07
530
+ [2025-10-28 12:22:09] (step=0046400) Train Loss: 0.6088, Train Steps/Sec: 1.13
531
+ [2025-10-28 12:23:37] (step=0046500) Train Loss: 0.6083, Train Steps/Sec: 1.13
532
+ [2025-10-28 12:25:06] (step=0046600) Train Loss: 0.6077, Train Steps/Sec: 1.13
533
+ [2025-10-28 12:26:35] (step=0046700) Train Loss: 0.6070, Train Steps/Sec: 1.12
534
+ [2025-10-28 12:28:03] (step=0046800) Train Loss: 0.6078, Train Steps/Sec: 1.13
535
+ [2025-10-28 12:29:31] (step=0046900) Train Loss: 0.6079, Train Steps/Sec: 1.13
536
+ [2025-10-28 12:30:59] (step=0047000) Train Loss: 0.6081, Train Steps/Sec: 1.13
537
+ [2025-10-28 12:32:27] (step=0047100) Train Loss: 0.6099, Train Steps/Sec: 1.13
538
+ [2025-10-28 12:33:55] (step=0047200) Train Loss: 0.6084, Train Steps/Sec: 1.14
539
+ [2025-10-28 12:35:24] (step=0047300) Train Loss: 0.6086, Train Steps/Sec: 1.13
540
+ [2025-10-28 12:36:52] (step=0047400) Train Loss: 0.6074, Train Steps/Sec: 1.13
541
+ [2025-10-28 12:38:20] (step=0047500) Train Loss: 0.6070, Train Steps/Sec: 1.13
542
+ [2025-10-28 12:38:54] Beginning epoch 38...
543
+ [2025-10-28 12:39:55] (step=0047600) Train Loss: 0.6065, Train Steps/Sec: 1.06
544
+ [2025-10-28 12:41:23] (step=0047700) Train Loss: 0.6081, Train Steps/Sec: 1.13
545
+ [2025-10-28 12:42:51] (step=0047800) Train Loss: 0.6073, Train Steps/Sec: 1.13
546
+ [2025-10-28 12:44:19] (step=0047900) Train Loss: 0.6057, Train Steps/Sec: 1.13
547
+ [2025-10-28 12:45:47] (step=0048000) Train Loss: 0.6072, Train Steps/Sec: 1.13
548
+ [2025-10-28 12:47:15] (step=0048100) Train Loss: 0.6056, Train Steps/Sec: 1.13
549
+ [2025-10-28 12:48:44] (step=0048200) Train Loss: 0.6075, Train Steps/Sec: 1.13
550
+ [2025-10-28 12:50:12] (step=0048300) Train Loss: 0.6075, Train Steps/Sec: 1.13
551
+ [2025-10-28 12:51:40] (step=0048400) Train Loss: 0.6072, Train Steps/Sec: 1.13
552
+ [2025-10-28 12:53:09] (step=0048500) Train Loss: 0.6081, Train Steps/Sec: 1.13
553
+ [2025-10-28 12:54:37] (step=0048600) Train Loss: 0.6083, Train Steps/Sec: 1.13
554
+ [2025-10-28 12:56:05] (step=0048700) Train Loss: 0.6076, Train Steps/Sec: 1.13
555
+ [2025-10-28 12:57:24] Beginning epoch 39...
556
+ [2025-10-28 12:57:38] (step=0048800) Train Loss: 0.6070, Train Steps/Sec: 1.07
557
+ [2025-10-28 12:59:06] (step=0048900) Train Loss: 0.6084, Train Steps/Sec: 1.13
558
+ [2025-10-28 13:00:34] (step=0049000) Train Loss: 0.6067, Train Steps/Sec: 1.13
559
+ [2025-10-28 13:02:02] (step=0049100) Train Loss: 0.6064, Train Steps/Sec: 1.13
560
+ [2025-10-28 13:03:31] (step=0049200) Train Loss: 0.6064, Train Steps/Sec: 1.13
561
+ [2025-10-28 13:04:59] (step=0049300) Train Loss: 0.6074, Train Steps/Sec: 1.13
562
+ [2025-10-28 13:06:28] (step=0049400) Train Loss: 0.6061, Train Steps/Sec: 1.13
563
+ [2025-10-28 13:07:56] (step=0049500) Train Loss: 0.6058, Train Steps/Sec: 1.13
564
+ [2025-10-28 13:09:24] (step=0049600) Train Loss: 0.6061, Train Steps/Sec: 1.13
565
+ [2025-10-28 13:10:52] (step=0049700) Train Loss: 0.6065, Train Steps/Sec: 1.14
566
+ [2025-10-28 13:12:20] (step=0049800) Train Loss: 0.6058, Train Steps/Sec: 1.13
567
+ [2025-10-28 13:13:48] (step=0049900) Train Loss: 0.6079, Train Steps/Sec: 1.13
568
+ [2025-10-28 13:15:17] (step=0050000) Train Loss: 0.6078, Train Steps/Sec: 1.13
569
+ [2025-10-28 13:16:10] Saved checkpoint to results/stage2/hfdata/lightningdit-xl-spatialpe-vit-g-bf16/checkpoints/0050000.pt
570
+ [2025-10-28 13:16:10] Generating EMA samples...
571
+ [2025-10-28 13:16:38] Generating EMA samples done.
572
+ [2025-10-28 13:17:14] Beginning epoch 40...
573
+ [2025-10-28 13:18:13] (step=0050100) Train Loss: 0.6052, Train Steps/Sec: 0.57
574
+ [2025-10-28 13:19:42] (step=0050200) Train Loss: 0.6061, Train Steps/Sec: 1.13
575
+ [2025-10-28 13:21:10] (step=0050300) Train Loss: 0.6062, Train Steps/Sec: 1.13
576
+ [2025-10-28 13:22:38] (step=0050400) Train Loss: 0.6056, Train Steps/Sec: 1.13
577
+ [2025-10-28 13:24:06] (step=0050500) Train Loss: 0.6058, Train Steps/Sec: 1.14
578
+ [2025-10-28 13:25:34] (step=0050600) Train Loss: 0.6065, Train Steps/Sec: 1.13
579
+ [2025-10-28 13:27:02] (step=0050700) Train Loss: 0.6079, Train Steps/Sec: 1.13
580
+ [2025-10-28 13:28:31] (step=0050800) Train Loss: 0.6059, Train Steps/Sec: 1.13
581
+ [2025-10-28 13:29:59] (step=0050900) Train Loss: 0.6054, Train Steps/Sec: 1.13
582
+ [2025-10-28 13:31:27] (step=0051000) Train Loss: 0.6071, Train Steps/Sec: 1.13
583
+ [2025-10-28 13:32:55] (step=0051100) Train Loss: 0.6063, Train Steps/Sec: 1.13
584
+ [2025-10-28 13:34:24] (step=0051200) Train Loss: 0.6051, Train Steps/Sec: 1.13
585
+ [2025-10-28 13:35:44] Beginning epoch 41...
586
+ [2025-10-28 13:35:58] (step=0051300) Train Loss: 0.6070, Train Steps/Sec: 1.06
587
+ [2025-10-28 13:37:26] (step=0051400) Train Loss: 0.6052, Train Steps/Sec: 1.13
588
+ [2025-10-28 13:38:54] (step=0051500) Train Loss: 0.6052, Train Steps/Sec: 1.13
589
+ [2025-10-28 13:40:22] (step=0051600) Train Loss: 0.6068, Train Steps/Sec: 1.13
590
+ [2025-10-28 13:41:51] (step=0051700) Train Loss: 0.6047, Train Steps/Sec: 1.13
591
+ [2025-10-28 13:43:19] (step=0051800) Train Loss: 0.6050, Train Steps/Sec: 1.13
592
+ [2025-10-28 13:44:47] (step=0051900) Train Loss: 0.6054, Train Steps/Sec: 1.13
593
+ [2025-10-28 13:46:15] (step=0052000) Train Loss: 0.6045, Train Steps/Sec: 1.13
594
+ [2025-10-28 13:47:44] (step=0052100) Train Loss: 0.6065, Train Steps/Sec: 1.13
595
+ [2025-10-28 13:49:12] (step=0052200) Train Loss: 0.6063, Train Steps/Sec: 1.13
596
+ [2025-10-28 13:50:40] (step=0052300) Train Loss: 0.6062, Train Steps/Sec: 1.13
597
+ [2025-10-28 13:52:08] (step=0052400) Train Loss: 0.6061, Train Steps/Sec: 1.13
598
+ [2025-10-28 13:53:36] (step=0052500) Train Loss: 0.6053, Train Steps/Sec: 1.13
599
+ [2025-10-28 13:54:14] Beginning epoch 42...
600
+ [2025-10-28 13:55:11] (step=0052600) Train Loss: 0.6049, Train Steps/Sec: 1.06
601
+ [2025-10-28 13:56:39] (step=0052700) Train Loss: 0.6051, Train Steps/Sec: 1.13
602
+ [2025-10-28 13:58:08] (step=0052800) Train Loss: 0.6065, Train Steps/Sec: 1.13
603
+ [2025-10-28 13:59:36] (step=0052900) Train Loss: 0.6067, Train Steps/Sec: 1.13
604
+ [2025-10-28 14:01:04] (step=0053000) Train Loss: 0.6045, Train Steps/Sec: 1.13
605
+ [2025-10-28 14:02:32] (step=0053100) Train Loss: 0.6047, Train Steps/Sec: 1.13
606
+ [2025-10-28 14:04:00] (step=0053200) Train Loss: 0.6050, Train Steps/Sec: 1.13
607
+ [2025-10-28 14:05:29] (step=0053300) Train Loss: 0.6049, Train Steps/Sec: 1.13
608
+ [2025-10-28 14:06:57] (step=0053400) Train Loss: 0.6043, Train Steps/Sec: 1.13
609
+ [2025-10-28 14:08:25] (step=0053500) Train Loss: 0.6057, Train Steps/Sec: 1.13
610
+ [2025-10-28 14:09:54] (step=0053600) Train Loss: 0.6059, Train Steps/Sec: 1.13
611
+ [2025-10-28 14:11:22] (step=0053700) Train Loss: 0.6055, Train Steps/Sec: 1.13
612
+ [2025-10-28 14:12:45] Beginning epoch 43...
613
+ [2025-10-28 14:12:56] (step=0053800) Train Loss: 0.6055, Train Steps/Sec: 1.06
614
+ [2025-10-28 14:14:24] (step=0053900) Train Loss: 0.6038, Train Steps/Sec: 1.13
615
+ [2025-10-28 14:15:53] (step=0054000) Train Loss: 0.6040, Train Steps/Sec: 1.13
616
+ [2025-10-28 14:17:21] (step=0054100) Train Loss: 0.6062, Train Steps/Sec: 1.13
617
+ [2025-10-28 14:18:49] (step=0054200) Train Loss: 0.6034, Train Steps/Sec: 1.13
618
+ [2025-10-28 14:20:17] (step=0054300) Train Loss: 0.6054, Train Steps/Sec: 1.13
619
+ [2025-10-28 14:21:46] (step=0054400) Train Loss: 0.6052, Train Steps/Sec: 1.13
620
+ [2025-10-28 14:23:14] (step=0054500) Train Loss: 0.6048, Train Steps/Sec: 1.13
621
+ [2025-10-28 14:24:43] (step=0054600) Train Loss: 0.6039, Train Steps/Sec: 1.13
622
+ [2025-10-28 14:26:11] (step=0054700) Train Loss: 0.6042, Train Steps/Sec: 1.13
623
+ [2025-10-28 14:27:39] (step=0054800) Train Loss: 0.6042, Train Steps/Sec: 1.13
624
+ [2025-10-28 14:29:07] (step=0054900) Train Loss: 0.6048, Train Steps/Sec: 1.13
625
+ [2025-10-28 14:30:35] (step=0055000) Train Loss: 0.6047, Train Steps/Sec: 1.13
626
+ [2025-10-28 14:31:15] Beginning epoch 44...
627
+ [2025-10-28 14:32:10] (step=0055100) Train Loss: 0.6055, Train Steps/Sec: 1.06
628
+ [2025-10-28 14:33:38] (step=0055200) Train Loss: 0.6041, Train Steps/Sec: 1.13
629
+ [2025-10-28 14:35:06] (step=0055300) Train Loss: 0.6041, Train Steps/Sec: 1.13
630
+ [2025-10-28 14:36:35] (step=0055400) Train Loss: 0.6042, Train Steps/Sec: 1.13
631
+ [2025-10-28 14:38:03] (step=0055500) Train Loss: 0.6044, Train Steps/Sec: 1.13
632
+ [2025-10-28 14:39:31] (step=0055600) Train Loss: 0.6042, Train Steps/Sec: 1.13
633
+ [2025-10-28 14:41:00] (step=0055700) Train Loss: 0.6046, Train Steps/Sec: 1.13
634
+ [2025-10-28 14:42:28] (step=0055800) Train Loss: 0.6037, Train Steps/Sec: 1.13
635
+ [2025-10-28 14:43:56] (step=0055900) Train Loss: 0.6048, Train Steps/Sec: 1.13
636
+ [2025-10-28 14:45:24] (step=0056000) Train Loss: 0.6031, Train Steps/Sec: 1.13
637
+ [2025-10-28 14:46:52] (step=0056100) Train Loss: 0.6028, Train Steps/Sec: 1.13
638
+ [2025-10-28 14:48:21] (step=0056200) Train Loss: 0.6044, Train Steps/Sec: 1.13
639
+ [2025-10-28 14:49:45] Beginning epoch 45...
640
+ [2025-10-28 14:49:55] (step=0056300) Train Loss: 0.6057, Train Steps/Sec: 1.06
641
+ [2025-10-28 14:51:23] (step=0056400) Train Loss: 0.6026, Train Steps/Sec: 1.13
642
+ [2025-10-28 14:52:51] (step=0056500) Train Loss: 0.6051, Train Steps/Sec: 1.13
643
+ [2025-10-28 14:54:20] (step=0056600) Train Loss: 0.6034, Train Steps/Sec: 1.13
644
+ [2025-10-28 14:55:48] (step=0056700) Train Loss: 0.6039, Train Steps/Sec: 1.13
645
+ [2025-10-28 14:57:16] (step=0056800) Train Loss: 0.6026, Train Steps/Sec: 1.13
646
+ [2025-10-28 14:58:44] (step=0056900) Train Loss: 0.6033, Train Steps/Sec: 1.13
647
+ [2025-10-28 15:00:12] (step=0057000) Train Loss: 0.6042, Train Steps/Sec: 1.13
648
+ [2025-10-28 15:01:41] (step=0057100) Train Loss: 0.6040, Train Steps/Sec: 1.13
649
+ [2025-10-28 15:03:09] (step=0057200) Train Loss: 0.6039, Train Steps/Sec: 1.13
650
+ [2025-10-28 15:04:37] (step=0057300) Train Loss: 0.6042, Train Steps/Sec: 1.13
651
+ [2025-10-28 15:06:06] (step=0057400) Train Loss: 0.6032, Train Steps/Sec: 1.13
652
+ [2025-10-28 15:07:34] (step=0057500) Train Loss: 0.6044, Train Steps/Sec: 1.13
653
+ [2025-10-28 15:08:15] Beginning epoch 46...
654
+ [2025-10-28 15:09:08] (step=0057600) Train Loss: 0.6027, Train Steps/Sec: 1.06
655
+ [2025-10-28 15:10:36] (step=0057700) Train Loss: 0.6038, Train Steps/Sec: 1.13
656
+ [2025-10-28 15:12:04] (step=0057800) Train Loss: 0.6042, Train Steps/Sec: 1.13
657
+ [2025-10-28 15:13:33] (step=0057900) Train Loss: 0.6047, Train Steps/Sec: 1.13
658
+ [2025-10-28 15:15:02] (step=0058000) Train Loss: 0.6041, Train Steps/Sec: 1.13
659
+ [2025-10-28 15:16:30] (step=0058100) Train Loss: 0.6026, Train Steps/Sec: 1.13
660
+ [2025-10-28 15:17:58] (step=0058200) Train Loss: 0.6053, Train Steps/Sec: 1.13
661
+ [2025-10-28 15:19:26] (step=0058300) Train Loss: 0.6044, Train Steps/Sec: 1.13
662
+ [2025-10-28 15:20:54] (step=0058400) Train Loss: 0.6056, Train Steps/Sec: 1.13
663
+ [2025-10-28 15:22:22] (step=0058500) Train Loss: 1.6813, Train Steps/Sec: 1.13
664
+ [2025-10-28 15:23:50] (step=0058600) Train Loss: 1.9872, Train Steps/Sec: 1.13
665
+ [2025-10-28 15:25:19] (step=0058700) Train Loss: 1.7171, Train Steps/Sec: 1.13
666
+ [2025-10-28 15:26:45] Beginning epoch 47...
667
+ [2025-10-28 15:26:53] (step=0058800) Train Loss: 1.7091, Train Steps/Sec: 1.06
668
+ [2025-10-28 15:28:21] (step=0058900) Train Loss: 1.7624, Train Steps/Sec: 1.13
669
+ [2025-10-28 15:29:49] (step=0059000) Train Loss: 2.8110, Train Steps/Sec: 1.13
670
+ [2025-10-28 15:31:18] (step=0059100) Train Loss: 1.5612, Train Steps/Sec: 1.13
671
+ [2025-10-28 15:32:46] (step=0059200) Train Loss: 1.4085, Train Steps/Sec: 1.13
672
+ [2025-10-28 15:34:14] (step=0059300) Train Loss: 1.7414, Train Steps/Sec: 1.13
673
+ [2025-10-28 15:35:42] (step=0059400) Train Loss: 1.4169, Train Steps/Sec: 1.13
674
+ [2025-10-28 15:37:10] (step=0059500) Train Loss: 1.6964, Train Steps/Sec: 1.13
675
+ [2025-10-28 15:38:39] (step=0059600) Train Loss: 1.6169, Train Steps/Sec: 1.13
676
+ [2025-10-28 15:40:07] (step=0059700) Train Loss: 1.4081, Train Steps/Sec: 1.13
677
+ [2025-10-28 15:41:36] (step=0059800) Train Loss: 1.4212, Train Steps/Sec: 1.13
678
+ [2025-10-28 15:43:04] (step=0059900) Train Loss: 1.5733, Train Steps/Sec: 1.13
679
+ [2025-10-28 15:44:32] (step=0060000) Train Loss: 1.3904, Train Steps/Sec: 1.13
680
+ [2025-10-28 15:45:15] Beginning epoch 48...
681
+ [2025-10-28 15:46:06] (step=0060100) Train Loss: 1.0895, Train Steps/Sec: 1.06
682
+ [2025-10-28 15:47:34] (step=0060200) Train Loss: 1.2682, Train Steps/Sec: 1.13
683
+ [2025-10-28 15:49:02] (step=0060300) Train Loss: 1.4114, Train Steps/Sec: 1.13
684
+ [2025-10-28 15:50:31] (step=0060400) Train Loss: 1.4329, Train Steps/Sec: 1.13
685
+ [2025-10-28 15:51:59] (step=0060500) Train Loss: 1.2282, Train Steps/Sec: 1.13
686
+ [2025-10-28 15:53:28] (step=0060600) Train Loss: 1.2971, Train Steps/Sec: 1.13
687
+ [2025-10-28 15:54:56] (step=0060700) Train Loss: 1.5380, Train Steps/Sec: 1.13
688
+ [2025-10-28 15:56:24] (step=0060800) Train Loss: 1.4680, Train Steps/Sec: 1.13
689
+ [2025-10-28 15:57:52] (step=0060900) Train Loss: 1.4340, Train Steps/Sec: 1.13
690
+ [2025-10-28 15:59:20] (step=0061000) Train Loss: 1.2399, Train Steps/Sec: 1.13
691
+ [2025-10-28 16:00:49] (step=0061100) Train Loss: 1.0848, Train Steps/Sec: 1.13
692
+ [2025-10-28 16:02:17] (step=0061200) Train Loss: 1.4618, Train Steps/Sec: 1.13
693
+ [2025-10-28 16:03:45] Beginning epoch 49...
694
+ [2025-10-28 16:03:51] (step=0061300) Train Loss: 1.0316, Train Steps/Sec: 1.06
695
+ [2025-10-28 16:05:20] (step=0061400) Train Loss: 0.8428, Train Steps/Sec: 1.13
696
+ [2025-10-28 16:06:48] (step=0061500) Train Loss: 1.3772, Train Steps/Sec: 1.13
697
+ [2025-10-28 16:08:16] (step=0061600) Train Loss: 1.5703, Train Steps/Sec: 1.13
698
+ [2025-10-28 16:09:45] (step=0061700) Train Loss: 1.4128, Train Steps/Sec: 1.13
699
+ [2025-10-28 16:11:13] (step=0061800) Train Loss: 1.4401, Train Steps/Sec: 1.13
700
+ [2025-10-28 16:12:41] (step=0061900) Train Loss: 1.2260, Train Steps/Sec: 1.13
701
+ [2025-10-28 16:14:09] (step=0062000) Train Loss: 1.3542, Train Steps/Sec: 1.13
702
+ [2025-10-28 16:15:37] (step=0062100) Train Loss: 1.6677, Train Steps/Sec: 1.13
703
+ [2025-10-28 16:17:06] (step=0062200) Train Loss: 4.1388, Train Steps/Sec: 1.13
704
+ [2025-10-28 16:18:34] (step=0062300) Train Loss: 1.0619, Train Steps/Sec: 1.13
705
+ [2025-10-28 16:20:02] (step=0062400) Train Loss: 3.5517, Train Steps/Sec: 1.13
706
+ [2025-10-28 16:21:30] (step=0062500) Train Loss: 1.8764, Train Steps/Sec: 1.13
707
+ [2025-10-28 16:22:15] Beginning epoch 50...
708
+ [2025-10-28 16:23:05] (step=0062600) Train Loss: 1.6090, Train Steps/Sec: 1.06
709
+ [2025-10-28 16:24:33] (step=0062700) Train Loss: 2.1292, Train Steps/Sec: 1.13
710
+ [2025-10-28 16:26:01] (step=0062800) Train Loss: 2.4507, Train Steps/Sec: 1.13
711
+ [2025-10-28 16:27:30] (step=0062900) Train Loss: 2.4119, Train Steps/Sec: 1.13
712
+ [2025-10-28 16:28:58] (step=0063000) Train Loss: nan, Train Steps/Sec: 1.13
713
+ [2025-10-28 16:30:23] (step=0063100) Train Loss: nan, Train Steps/Sec: 1.18
714
+ [2025-10-28 16:31:47] (step=0063200) Train Loss: nan, Train Steps/Sec: 1.18
715
+ [2025-10-28 16:33:12] (step=0063300) Train Loss: nan, Train Steps/Sec: 1.18
716
+ [2025-10-28 16:34:36] (step=0063400) Train Loss: nan, Train Steps/Sec: 1.18
717
+ [2025-10-28 16:36:01] (step=0063500) Train Loss: nan, Train Steps/Sec: 1.18
718
+ [2025-10-28 16:37:25] (step=0063600) Train Loss: nan, Train Steps/Sec: 1.18
719
+ [2025-10-28 16:38:50] (step=0063700) Train Loss: nan, Train Steps/Sec: 1.18
720
+ [2025-10-28 16:40:14] (step=0063800) Train Loss: nan, Train Steps/Sec: 1.19
721
+ [2025-10-28 16:40:15] Beginning epoch 51...
722
+ [2025-10-28 16:41:44] (step=0063900) Train Loss: nan, Train Steps/Sec: 1.11
723
+ [2025-10-28 16:43:09] (step=0064000) Train Loss: nan, Train Steps/Sec: 1.18
724
+ [2025-10-28 16:44:34] (step=0064100) Train Loss: nan, Train Steps/Sec: 1.18
725
+ [2025-10-28 16:45:58] (step=0064200) Train Loss: nan, Train Steps/Sec: 1.18
726
+ [2025-10-28 16:47:23] (step=0064300) Train Loss: nan, Train Steps/Sec: 1.18
727
+ [2025-10-28 16:48:47] (step=0064400) Train Loss: nan, Train Steps/Sec: 1.18
728
+ [2025-10-28 16:50:11] (step=0064500) Train Loss: nan, Train Steps/Sec: 1.18
729
+ [2025-10-28 16:51:36] (step=0064600) Train Loss: nan, Train Steps/Sec: 1.18
730
+ [2025-10-28 16:53:00] (step=0064700) Train Loss: nan, Train Steps/Sec: 1.18
731
+ [2025-10-28 16:54:25] (step=0064800) Train Loss: nan, Train Steps/Sec: 1.18
732
+ [2025-10-28 16:55:50] (step=0064900) Train Loss: nan, Train Steps/Sec: 1.18
733
+ [2025-10-28 16:57:14] (step=0065000) Train Loss: nan, Train Steps/Sec: 1.18
734
+ [2025-10-28 16:57:59] Beginning epoch 52...
735
+ [2025-10-28 16:58:45] (step=0065100) Train Loss: nan, Train Steps/Sec: 1.10
736
+ [2025-10-28 17:00:10] (step=0065200) Train Loss: nan, Train Steps/Sec: 1.18
737
+ [2025-10-28 17:01:34] (step=0065300) Train Loss: nan, Train Steps/Sec: 1.18
738
+ [2025-10-28 17:02:59] (step=0065400) Train Loss: nan, Train Steps/Sec: 1.18
739
+ [2025-10-28 17:04:23] (step=0065500) Train Loss: nan, Train Steps/Sec: 1.18
740
+ [2025-10-28 17:05:47] (step=0065600) Train Loss: nan, Train Steps/Sec: 1.18
741
+ [2025-10-28 17:07:12] (step=0065700) Train Loss: nan, Train Steps/Sec: 1.18
742
+ [2025-10-28 17:08:37] (step=0065800) Train Loss: nan, Train Steps/Sec: 1.18
743
+ [2025-10-28 17:10:01] (step=0065900) Train Loss: nan, Train Steps/Sec: 1.18
744
+ [2025-10-28 17:11:26] (step=0066000) Train Loss: nan, Train Steps/Sec: 1.18
745
+ [2025-10-28 17:12:50] (step=0066100) Train Loss: nan, Train Steps/Sec: 1.18
746
+ [2025-10-28 17:14:14] (step=0066200) Train Loss: nan, Train Steps/Sec: 1.18
747
+ [2025-10-28 17:15:39] (step=0066300) Train Loss: nan, Train Steps/Sec: 1.19
748
+ [2025-10-28 17:15:42] Beginning epoch 53...
749
+ [2025-10-28 17:17:10] (step=0066400) Train Loss: nan, Train Steps/Sec: 1.10
750
+ [2025-10-28 17:18:35] (step=0066500) Train Loss: nan, Train Steps/Sec: 1.18
751
+ [2025-10-28 17:20:00] (step=0066600) Train Loss: nan, Train Steps/Sec: 1.18
752
+ [2025-10-28 17:21:24] (step=0066700) Train Loss: nan, Train Steps/Sec: 1.18
753
+ [2025-10-28 17:22:49] (step=0066800) Train Loss: nan, Train Steps/Sec: 1.18
754
+ [2025-10-28 17:24:13] (step=0066900) Train Loss: nan, Train Steps/Sec: 1.18
755
+ [2025-10-28 17:25:37] (step=0067000) Train Loss: nan, Train Steps/Sec: 1.18
756
+ [2025-10-28 17:27:02] (step=0067100) Train Loss: nan, Train Steps/Sec: 1.18
757
+ [2025-10-28 17:28:26] (step=0067200) Train Loss: nan, Train Steps/Sec: 1.18
758
+ [2025-10-28 17:29:51] (step=0067300) Train Loss: nan, Train Steps/Sec: 1.18
759
+ [2025-10-28 17:31:16] (step=0067400) Train Loss: nan, Train Steps/Sec: 1.18
760
+ [2025-10-28 17:32:40] (step=0067500) Train Loss: nan, Train Steps/Sec: 1.18
761
+ [2025-10-28 17:33:26] Beginning epoch 54...
762
+ [2025-10-28 17:34:11] (step=0067600) Train Loss: nan, Train Steps/Sec: 1.10
763
+ [2025-10-28 17:35:36] (step=0067700) Train Loss: nan, Train Steps/Sec: 1.18
764
+ [2025-10-28 17:37:00] (step=0067800) Train Loss: nan, Train Steps/Sec: 1.18
765
+ [2025-10-28 17:38:25] (step=0067900) Train Loss: nan, Train Steps/Sec: 1.18
766
+ [2025-10-28 17:39:49] (step=0068000) Train Loss: nan, Train Steps/Sec: 1.18
767
+ [2025-10-28 17:41:13] (step=0068100) Train Loss: nan, Train Steps/Sec: 1.18
768
+ [2025-10-28 17:42:38] (step=0068200) Train Loss: nan, Train Steps/Sec: 1.18
769
+ [2025-10-28 17:44:03] (step=0068300) Train Loss: nan, Train Steps/Sec: 1.18
770
+ [2025-10-28 17:45:27] (step=0068400) Train Loss: nan, Train Steps/Sec: 1.18
771
+ [2025-10-28 17:46:52] (step=0068500) Train Loss: nan, Train Steps/Sec: 1.18
772
+ [2025-10-28 17:48:16] (step=0068600) Train Loss: nan, Train Steps/Sec: 1.18
773
+ [2025-10-28 17:49:41] (step=0068700) Train Loss: nan, Train Steps/Sec: 1.18
774
+ [2025-10-28 17:51:05] (step=0068800) Train Loss: nan, Train Steps/Sec: 1.18
775
+ [2025-10-28 17:51:10] Beginning epoch 55...
776
+ [2025-10-28 17:52:35] (step=0068900) Train Loss: nan, Train Steps/Sec: 1.11
777
+ [2025-10-28 17:54:00] (step=0069000) Train Loss: nan, Train Steps/Sec: 1.18
778
+ [2025-10-28 17:55:25] (step=0069100) Train Loss: nan, Train Steps/Sec: 1.18
779
+ [2025-10-28 17:56:50] (step=0069200) Train Loss: nan, Train Steps/Sec: 1.18
780
+ [2025-10-28 17:58:14] (step=0069300) Train Loss: nan, Train Steps/Sec: 1.18
781
+ [2025-10-28 17:59:39] (step=0069400) Train Loss: nan, Train Steps/Sec: 1.18
782
+ [2025-10-28 18:01:03] (step=0069500) Train Loss: nan, Train Steps/Sec: 1.18
783
+ [2025-10-28 18:02:27] (step=0069600) Train Loss: nan, Train Steps/Sec: 1.18
784
+ [2025-10-28 18:03:52] (step=0069700) Train Loss: nan, Train Steps/Sec: 1.18
785
+ [2025-10-28 18:05:16] (step=0069800) Train Loss: nan, Train Steps/Sec: 1.18
786
+ [2025-10-28 18:06:41] (step=0069900) Train Loss: nan, Train Steps/Sec: 1.18
787
+ [2025-10-28 18:08:06] (step=0070000) Train Loss: nan, Train Steps/Sec: 1.18
788
+ [2025-10-28 18:08:54] Beginning epoch 56...
789
+ [2025-10-28 18:09:36] (step=0070100) Train Loss: nan, Train Steps/Sec: 1.11
790
+ [2025-10-28 18:11:00] (step=0070200) Train Loss: nan, Train Steps/Sec: 1.18
791
+ [2025-10-28 18:12:25] (step=0070300) Train Loss: nan, Train Steps/Sec: 1.18
792
+ [2025-10-28 18:13:49] (step=0070400) Train Loss: nan, Train Steps/Sec: 1.18
793
+ [2025-10-28 18:15:14] (step=0070500) Train Loss: nan, Train Steps/Sec: 1.18
794
+ [2025-10-28 18:16:38] (step=0070600) Train Loss: nan, Train Steps/Sec: 1.18
795
+ [2025-10-28 18:18:03] (step=0070700) Train Loss: nan, Train Steps/Sec: 1.18
796
+ [2025-10-28 18:19:27] (step=0070800) Train Loss: nan, Train Steps/Sec: 1.18
797
+ [2025-10-28 18:20:52] (step=0070900) Train Loss: nan, Train Steps/Sec: 1.18
798
+ [2025-10-28 18:22:17] (step=0071000) Train Loss: nan, Train Steps/Sec: 1.18
799
+ [2025-10-28 18:23:41] (step=0071100) Train Loss: nan, Train Steps/Sec: 1.18
800
+ [2025-10-28 18:25:06] (step=0071200) Train Loss: nan, Train Steps/Sec: 1.18
801
+ [2025-10-28 18:26:30] (step=0071300) Train Loss: nan, Train Steps/Sec: 1.18
802
+ [2025-10-28 18:26:37] Beginning epoch 57...
803
+ [2025-10-28 18:28:00] (step=0071400) Train Loss: nan, Train Steps/Sec: 1.11
804
+ [2025-10-28 18:29:25] (step=0071500) Train Loss: nan, Train Steps/Sec: 1.18
805
+ [2025-10-28 18:30:49] (step=0071600) Train Loss: nan, Train Steps/Sec: 1.18
806
+ [2025-10-28 18:32:14] (step=0071700) Train Loss: nan, Train Steps/Sec: 1.18
807
+ [2025-10-28 18:33:39] (step=0071800) Train Loss: nan, Train Steps/Sec: 1.18
808
+ [2025-10-28 18:35:03] (step=0071900) Train Loss: nan, Train Steps/Sec: 1.18
809
+ [2025-10-28 18:36:27] (step=0072000) Train Loss: nan, Train Steps/Sec: 1.18
810
+ [2025-10-28 18:37:52] (step=0072100) Train Loss: nan, Train Steps/Sec: 1.18
811
+ [2025-10-28 18:39:16] (step=0072200) Train Loss: nan, Train Steps/Sec: 1.18
812
+ [2025-10-28 18:40:41] (step=0072300) Train Loss: nan, Train Steps/Sec: 1.18
813
+ [2025-10-28 18:42:05] (step=0072400) Train Loss: nan, Train Steps/Sec: 1.18
814
+ [2025-10-28 18:43:30] (step=0072500) Train Loss: nan, Train Steps/Sec: 1.18
815
+ [2025-10-28 18:44:20] Beginning epoch 58...
816
+ [2025-10-28 18:45:02] (step=0072600) Train Loss: nan, Train Steps/Sec: 1.09
817
+ [2025-10-28 18:46:26] (step=0072700) Train Loss: nan, Train Steps/Sec: 1.18
818
+ [2025-10-28 18:47:50] (step=0072800) Train Loss: nan, Train Steps/Sec: 1.18
819
+ [2025-10-28 18:49:15] (step=0072900) Train Loss: nan, Train Steps/Sec: 1.18
820
+ [2025-10-28 18:50:40] (step=0073000) Train Loss: nan, Train Steps/Sec: 1.18
821
+ [2025-10-28 18:52:04] (step=0073100) Train Loss: nan, Train Steps/Sec: 1.18
822
+ [2025-10-28 18:53:28] (step=0073200) Train Loss: nan, Train Steps/Sec: 1.18
823
+ [2025-10-28 18:54:53] (step=0073300) Train Loss: nan, Train Steps/Sec: 1.18
824
+ [2025-10-28 18:56:17] (step=0073400) Train Loss: nan, Train Steps/Sec: 1.18
825
+ [2025-10-28 18:57:42] (step=0073500) Train Loss: nan, Train Steps/Sec: 1.18
826
+ [2025-10-28 18:59:07] (step=0073600) Train Loss: nan, Train Steps/Sec: 1.18
827
+ [2025-10-28 19:00:31] (step=0073700) Train Loss: nan, Train Steps/Sec: 1.18
828
+ [2025-10-28 19:01:55] (step=0073800) Train Loss: nan, Train Steps/Sec: 1.19
829
+ [2025-10-28 19:02:04] Beginning epoch 59...
830
+ [2025-10-28 19:03:25] (step=0073900) Train Loss: nan, Train Steps/Sec: 1.11
831
+ [2025-10-28 19:04:50] (step=0074000) Train Loss: nan, Train Steps/Sec: 1.18
832
+ [2025-10-28 19:06:14] (step=0074100) Train Loss: nan, Train Steps/Sec: 1.18
833
+ [2025-10-28 19:07:39] (step=0074200) Train Loss: nan, Train Steps/Sec: 1.18
834
+ [2025-10-28 19:09:04] (step=0074300) Train Loss: nan, Train Steps/Sec: 1.17
835
+ [2025-10-28 19:10:29] (step=0074400) Train Loss: nan, Train Steps/Sec: 1.18
836
+ [2025-10-28 19:11:53] (step=0074500) Train Loss: nan, Train Steps/Sec: 1.18
837
+ [2025-10-28 19:13:18] (step=0074600) Train Loss: nan, Train Steps/Sec: 1.18
838
+ [2025-10-28 19:14:42] (step=0074700) Train Loss: nan, Train Steps/Sec: 1.18
839
+ [2025-10-28 19:16:06] (step=0074800) Train Loss: nan, Train Steps/Sec: 1.18
840
+ [2025-10-28 19:17:31] (step=0074900) Train Loss: nan, Train Steps/Sec: 1.18
841
+ [2025-10-28 19:18:55] (step=0075000) Train Loss: nan, Train Steps/Sec: 1.18
842
+ [2025-10-28 19:19:49] Saved checkpoint to results/stage2/hfdata/lightningdit-xl-spatialpe-vit-g-bf16/checkpoints/0075000.pt
843
+ [2025-10-28 19:19:49] Generating EMA samples...
844
+ [2025-10-28 19:20:03] Generating EMA samples done.
845
+ [2025-10-28 19:20:54] Beginning epoch 60...
846
+ [2025-10-28 19:21:33] (step=0075100) Train Loss: nan, Train Steps/Sec: 0.63
847
+ [2025-10-28 19:22:59] (step=0075200) Train Loss: nan, Train Steps/Sec: 1.18
848
+ [2025-10-28 19:24:23] (step=0075300) Train Loss: nan, Train Steps/Sec: 1.18
849
+ [2025-10-28 19:25:47] (step=0075400) Train Loss: nan, Train Steps/Sec: 1.18
850
+ [2025-10-28 19:27:12] (step=0075500) Train Loss: nan, Train Steps/Sec: 1.18
851
+ [2025-10-28 19:28:36] (step=0075600) Train Loss: nan, Train Steps/Sec: 1.18
852
+ [2025-10-28 19:30:01] (step=0075700) Train Loss: nan, Train Steps/Sec: 1.18
853
+ [2025-10-28 19:31:25] (step=0075800) Train Loss: nan, Train Steps/Sec: 1.18
854
+ [2025-10-28 19:32:50] (step=0075900) Train Loss: nan, Train Steps/Sec: 1.18
855
+ [2025-10-28 19:34:15] (step=0076000) Train Loss: nan, Train Steps/Sec: 1.18
856
+ [2025-10-28 19:35:39] (step=0076100) Train Loss: nan, Train Steps/Sec: 1.18
857
+ [2025-10-28 19:37:04] (step=0076200) Train Loss: nan, Train Steps/Sec: 1.18
858
+ [2025-10-28 19:38:28] (step=0076300) Train Loss: nan, Train Steps/Sec: 1.18
859
+ [2025-10-28 19:38:38] Beginning epoch 61...
860
+ [2025-10-28 19:39:59] (step=0076400) Train Loss: nan, Train Steps/Sec: 1.10
861
+ [2025-10-28 19:41:24] (step=0076500) Train Loss: nan, Train Steps/Sec: 1.18
862
+ [2025-10-28 19:42:48] (step=0076600) Train Loss: nan, Train Steps/Sec: 1.18
863
+ [2025-10-28 19:44:13] (step=0076700) Train Loss: nan, Train Steps/Sec: 1.18
864
+ [2025-10-28 19:45:37] (step=0076800) Train Loss: nan, Train Steps/Sec: 1.18
865
+ [2025-10-28 19:47:02] (step=0076900) Train Loss: nan, Train Steps/Sec: 1.18
866
+ [2025-10-28 19:48:27] (step=0077000) Train Loss: nan, Train Steps/Sec: 1.18
867
+ [2025-10-28 19:49:51] (step=0077100) Train Loss: nan, Train Steps/Sec: 1.18
868
+ [2025-10-28 19:51:15] (step=0077200) Train Loss: nan, Train Steps/Sec: 1.18
869
+ [2025-10-28 19:52:40] (step=0077300) Train Loss: nan, Train Steps/Sec: 1.18
870
+ [2025-10-28 19:54:04] (step=0077400) Train Loss: nan, Train Steps/Sec: 1.18
871
+ [2025-10-28 19:55:29] (step=0077500) Train Loss: nan, Train Steps/Sec: 1.18
872
+ [2025-10-28 19:56:22] Beginning epoch 62...
873
+ [2025-10-28 19:56:59] (step=0077600) Train Loss: nan, Train Steps/Sec: 1.11
874
+ [2025-10-28 19:58:24] (step=0077700) Train Loss: nan, Train Steps/Sec: 1.18
875
+ [2025-10-28 19:59:49] (step=0077800) Train Loss: nan, Train Steps/Sec: 1.18
876
+ [2025-10-28 20:01:13] (step=0077900) Train Loss: nan, Train Steps/Sec: 1.18
877
+ [2025-10-28 20:02:38] (step=0078000) Train Loss: nan, Train Steps/Sec: 1.18
878
+ [2025-10-28 20:04:02] (step=0078100) Train Loss: nan, Train Steps/Sec: 1.18
879
+ [2025-10-28 20:05:27] (step=0078200) Train Loss: nan, Train Steps/Sec: 1.18
880
+ [2025-10-28 20:06:51] (step=0078300) Train Loss: nan, Train Steps/Sec: 1.18
881
+ [2025-10-28 20:08:16] (step=0078400) Train Loss: nan, Train Steps/Sec: 1.18
882
+ [2025-10-28 20:09:40] (step=0078500) Train Loss: nan, Train Steps/Sec: 1.18
883
+ [2025-10-28 20:11:05] (step=0078600) Train Loss: nan, Train Steps/Sec: 1.18
884
+ [2025-10-28 20:12:29] (step=0078700) Train Loss: nan, Train Steps/Sec: 1.18
885
+ [2025-10-28 20:13:54] (step=0078800) Train Loss: nan, Train Steps/Sec: 1.18
886
+ [2025-10-28 20:14:06] Beginning epoch 63...
887
+ [2025-10-28 20:15:25] (step=0078900) Train Loss: nan, Train Steps/Sec: 1.10
888
+ [2025-10-28 20:16:49] (step=0079000) Train Loss: nan, Train Steps/Sec: 1.18
889
+ [2025-10-28 20:18:13] (step=0079100) Train Loss: nan, Train Steps/Sec: 1.18
890
+ [2025-10-28 20:19:38] (step=0079200) Train Loss: nan, Train Steps/Sec: 1.18
891
+ [2025-10-28 20:21:03] (step=0079300) Train Loss: nan, Train Steps/Sec: 1.18
892
+ [2025-10-28 20:22:27] (step=0079400) Train Loss: nan, Train Steps/Sec: 1.18
893
+ [2025-10-28 20:23:52] (step=0079500) Train Loss: nan, Train Steps/Sec: 1.18
894
+ [2025-10-28 20:25:17] (step=0079600) Train Loss: nan, Train Steps/Sec: 1.18
895
+ [2025-10-28 20:26:41] (step=0079700) Train Loss: nan, Train Steps/Sec: 1.18
896
+ [2025-10-28 20:28:06] (step=0079800) Train Loss: nan, Train Steps/Sec: 1.18
897
+ [2025-10-28 20:29:30] (step=0079900) Train Loss: nan, Train Steps/Sec: 1.18
898
+ [2025-10-28 20:30:55] (step=0080000) Train Loss: nan, Train Steps/Sec: 1.18
899
+ [2025-10-28 20:31:49] Beginning epoch 64...
900
+ [2025-10-28 20:32:25] (step=0080100) Train Loss: nan, Train Steps/Sec: 1.11
901
+ [2025-10-28 20:33:49] (step=0080200) Train Loss: nan, Train Steps/Sec: 1.18
902
+ [2025-10-28 20:35:14] (step=0080300) Train Loss: nan, Train Steps/Sec: 1.18
903
+ [2025-10-28 20:36:39] (step=0080400) Train Loss: nan, Train Steps/Sec: 1.18
904
+ [2025-10-28 20:38:03] (step=0080500) Train Loss: nan, Train Steps/Sec: 1.18
905
+ [2025-10-28 20:39:28] (step=0080600) Train Loss: nan, Train Steps/Sec: 1.18
906
+ [2025-10-28 20:40:52] (step=0080700) Train Loss: nan, Train Steps/Sec: 1.18
907
+ [2025-10-28 20:42:17] (step=0080800) Train Loss: nan, Train Steps/Sec: 1.18
908
+ [2025-10-28 20:43:41] (step=0080900) Train Loss: nan, Train Steps/Sec: 1.18
909
+ [2025-10-28 20:45:06] (step=0081000) Train Loss: nan, Train Steps/Sec: 1.18
910
+ [2025-10-28 20:46:30] (step=0081100) Train Loss: nan, Train Steps/Sec: 1.18
911
+ [2025-10-28 20:47:55] (step=0081200) Train Loss: nan, Train Steps/Sec: 1.18
912
+ [2025-10-28 20:49:19] (step=0081300) Train Loss: nan, Train Steps/Sec: 1.18
913
+ [2025-10-28 20:49:33] Beginning epoch 65...
914
+ [2025-10-28 20:50:50] (step=0081400) Train Loss: nan, Train Steps/Sec: 1.11
915
+ [2025-10-28 20:52:14] (step=0081500) Train Loss: nan, Train Steps/Sec: 1.18
916
+ [2025-10-28 20:53:39] (step=0081600) Train Loss: nan, Train Steps/Sec: 1.18
917
+ [2025-10-28 20:55:03] (step=0081700) Train Loss: nan, Train Steps/Sec: 1.18
918
+ [2025-10-28 20:56:28] (step=0081800) Train Loss: nan, Train Steps/Sec: 1.18
919
+ [2025-10-28 20:57:52] (step=0081900) Train Loss: nan, Train Steps/Sec: 1.18
920
+ [2025-10-28 20:59:17] (step=0082000) Train Loss: nan, Train Steps/Sec: 1.18
921
+ [2025-10-28 21:00:42] (step=0082100) Train Loss: nan, Train Steps/Sec: 1.18
922
+ [2025-10-28 21:02:06] (step=0082200) Train Loss: nan, Train Steps/Sec: 1.18
923
+ [2025-10-28 21:03:31] (step=0082300) Train Loss: nan, Train Steps/Sec: 1.18
924
+ [2025-10-28 21:04:55] (step=0082400) Train Loss: nan, Train Steps/Sec: 1.18
925
+ [2025-10-28 21:06:20] (step=0082500) Train Loss: nan, Train Steps/Sec: 1.18
926
+ [2025-10-28 21:07:16] Beginning epoch 66...
927
+ [2025-10-28 21:07:50] (step=0082600) Train Loss: nan, Train Steps/Sec: 1.11
928
+ [2025-10-28 21:09:14] (step=0082700) Train Loss: nan, Train Steps/Sec: 1.18
929
+ [2025-10-28 21:10:39] (step=0082800) Train Loss: nan, Train Steps/Sec: 1.18
930
+ [2025-10-28 21:12:03] (step=0082900) Train Loss: nan, Train Steps/Sec: 1.18
931
+ [2025-10-28 21:13:28] (step=0083000) Train Loss: nan, Train Steps/Sec: 1.18
932
+ [2025-10-28 21:14:53] (step=0083100) Train Loss: nan, Train Steps/Sec: 1.18
933
+ [2025-10-28 21:16:17] (step=0083200) Train Loss: nan, Train Steps/Sec: 1.18
934
+ [2025-10-28 21:17:42] (step=0083300) Train Loss: nan, Train Steps/Sec: 1.18
935
+ [2025-10-28 21:19:06] (step=0083400) Train Loss: nan, Train Steps/Sec: 1.18
936
+ [2025-10-28 21:20:30] (step=0083500) Train Loss: nan, Train Steps/Sec: 1.18
937
+ [2025-10-28 21:21:55] (step=0083600) Train Loss: nan, Train Steps/Sec: 1.18
938
+ [2025-10-28 21:23:19] (step=0083700) Train Loss: nan, Train Steps/Sec: 1.18
939
+ [2025-10-28 21:24:44] (step=0083800) Train Loss: nan, Train Steps/Sec: 1.18
940
+ [2025-10-28 21:24:59] Beginning epoch 67...
941
+ [2025-10-28 21:26:15] (step=0083900) Train Loss: nan, Train Steps/Sec: 1.10
942
+ [2025-10-28 21:27:40] (step=0084000) Train Loss: nan, Train Steps/Sec: 1.18
943
+ [2025-10-28 21:29:04] (step=0084100) Train Loss: nan, Train Steps/Sec: 1.18
944
+ [2025-10-28 21:30:28] (step=0084200) Train Loss: nan, Train Steps/Sec: 1.18
945
+ [2025-10-28 21:31:53] (step=0084300) Train Loss: nan, Train Steps/Sec: 1.18
946
+ [2025-10-28 21:33:17] (step=0084400) Train Loss: nan, Train Steps/Sec: 1.18
947
+ [2025-10-28 21:34:42] (step=0084500) Train Loss: nan, Train Steps/Sec: 1.18
948
+ [2025-10-28 21:36:06] (step=0084600) Train Loss: nan, Train Steps/Sec: 1.18
949
+ [2025-10-28 21:37:31] (step=0084700) Train Loss: nan, Train Steps/Sec: 1.18
950
+ [2025-10-28 21:38:56] (step=0084800) Train Loss: nan, Train Steps/Sec: 1.18
951
+ [2025-10-28 21:40:20] (step=0084900) Train Loss: nan, Train Steps/Sec: 1.18
952
+ [2025-10-28 21:41:45] (step=0085000) Train Loss: nan, Train Steps/Sec: 1.18
953
+ [2025-10-28 21:42:43] Beginning epoch 68...
954
+ [2025-10-28 21:43:16] (step=0085100) Train Loss: nan, Train Steps/Sec: 1.09
955
+ [2025-10-28 21:44:41] (step=0085200) Train Loss: nan, Train Steps/Sec: 1.18
956
+ [2025-10-28 21:46:05] (step=0085300) Train Loss: nan, Train Steps/Sec: 1.18
957
+ [2025-10-28 21:47:30] (step=0085400) Train Loss: nan, Train Steps/Sec: 1.18
958
+ [2025-10-28 21:48:55] (step=0085500) Train Loss: nan, Train Steps/Sec: 1.18
959
+ [2025-10-28 21:50:19] (step=0085600) Train Loss: nan, Train Steps/Sec: 1.18
960
+ [2025-10-28 21:51:44] (step=0085700) Train Loss: nan, Train Steps/Sec: 1.18
961
+ [2025-10-28 21:53:08] (step=0085800) Train Loss: nan, Train Steps/Sec: 1.18
962
+ [2025-10-28 21:54:33] (step=0085900) Train Loss: nan, Train Steps/Sec: 1.18
963
+ [2025-10-28 21:55:57] (step=0086000) Train Loss: nan, Train Steps/Sec: 1.18
964
+ [2025-10-28 21:57:22] (step=0086100) Train Loss: nan, Train Steps/Sec: 1.18
965
+ [2025-10-28 21:58:46] (step=0086200) Train Loss: nan, Train Steps/Sec: 1.18
966
+ [2025-10-28 22:00:10] (step=0086300) Train Loss: nan, Train Steps/Sec: 1.18
967
+ [2025-10-28 22:00:27] Beginning epoch 69...