xingjianleng commited on
Commit
976646b
·
verified ·
1 Parent(s): 4ef9a4c

Upload folder using huggingface_hub

Browse files
stage2/lightningdit-xl-spatialpe-vit-l-bf16/checkpoints/0025000.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:493e5877a55955e2da2fad512b678e66ae3da6039ae8a32e9404d92bb2c69a44
3
+ size 19243018610
stage2/lightningdit-xl-spatialpe-vit-l-bf16/checkpoints/0050000.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:bf042f69250747054b82327074ca824b859072008d6b0f2431b5631a1a0ee999
3
+ size 19243018610
stage2/lightningdit-xl-spatialpe-vit-l-bf16/checkpoints/0075000.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:58b59ddc4911236997707d25c8aa053c8ae3ef774ceee01946c222683bda6c5e
3
+ size 19243018674
stage2/lightningdit-xl-spatialpe-vit-l-bf16/log.txt ADDED
@@ -0,0 +1,1000 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [2025-10-28 00:18:56] Experiment directory created at results/stage2/hfdata/lightningdit-xl-spatialpe-vit-l-bf16
2
+ [2025-10-28 00:19:01] Missing keys for loading vision encoder: []
3
+ [2025-10-28 00:19:01] Unexpected keys for loading vision encoder: []
4
+ [2025-10-28 00:19:17] Model Parameters: 1202.82M
5
+ [2025-10-28 00:19:22] Dataset contains 1,281,167 images (/scratch/xingjian.leng/data/train)
6
+ [2025-10-28 00:19:22] Gradient accumulation: steps=1, micro batch=128, per-GPU batch=128, global batch=1024
7
+ [2025-10-28 00:19:22] Precision mode: bf16
8
+ [2025-10-28 00:19:22] Training configured for 80 epochs, 1251 steps per epoch.
9
+ [2025-10-28 00:19:22] 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 00:19:22] Training for 80 epochs...
12
+ [2025-10-28 00:19:22] Beginning epoch 0...
13
+ [2025-10-28 00:46:43] Experiment directory created at results/stage2/hfdata/lightningdit-xl-spatialpe-vit-l-bf16
14
+ [2025-10-28 00:46:49] Missing keys for loading vision encoder: []
15
+ [2025-10-28 00:46:49] Unexpected keys for loading vision encoder: []
16
+ [2025-10-28 00:47:06] Model Parameters: 1202.82M
17
+ [2025-10-28 00:47:09] Dataset contains 1,281,167 images (/scratch/xingjian.leng/data/spatialpe-vit-l_hfdataset_precentercrop_True_train_bfloat16)
18
+ [2025-10-28 00:47:09] Gradient accumulation: steps=1, micro batch=128, per-GPU batch=128, global batch=1024
19
+ [2025-10-28 00:47:09] Precision mode: bf16
20
+ [2025-10-28 00:47:09] Training configured for 80 epochs, 1251 steps per epoch.
21
+ [2025-10-28 00:47:09] 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 00:47:09] Training for 80 epochs...
24
+ [2025-10-28 00:47:09] Beginning epoch 0...
25
+ [2025-10-28 00:47:18] Generating EMA samples...
26
+ [2025-10-28 00:47:47] Generating EMA samples done.
27
+ [2025-10-28 00:49:14] (step=0000100) Train Loss: 1.5614, Train Steps/Sec: 0.80
28
+ [2025-10-28 00:50:42] (step=0000200) Train Loss: 1.0399, Train Steps/Sec: 1.13
29
+ [2025-10-28 00:52:11] (step=0000300) Train Loss: 0.8722, Train Steps/Sec: 1.13
30
+ [2025-10-28 00:53:39] (step=0000400) Train Loss: 0.7924, Train Steps/Sec: 1.13
31
+ [2025-10-28 00:55:07] (step=0000500) Train Loss: 0.7486, Train Steps/Sec: 1.13
32
+ [2025-10-28 00:56:35] (step=0000600) Train Loss: 0.7179, Train Steps/Sec: 1.13
33
+ [2025-10-28 00:58:03] (step=0000700) Train Loss: 0.6948, Train Steps/Sec: 1.13
34
+ [2025-10-28 00:59:32] (step=0000800) Train Loss: 0.6755, Train Steps/Sec: 1.13
35
+ [2025-10-28 01:01:00] (step=0000900) Train Loss: 0.6596, Train Steps/Sec: 1.13
36
+ [2025-10-28 01:02:28] (step=0001000) Train Loss: 0.6482, Train Steps/Sec: 1.13
37
+ [2025-10-28 01:03:57] (step=0001100) Train Loss: 0.6359, Train Steps/Sec: 1.13
38
+ [2025-10-28 01:05:25] (step=0001200) Train Loss: 0.6283, Train Steps/Sec: 1.13
39
+ [2025-10-28 01:06:11] Beginning epoch 1...
40
+ [2025-10-28 01:06:56] (step=0001300) Train Loss: 0.6191, Train Steps/Sec: 1.09
41
+ [2025-10-28 01:08:25] (step=0001400) Train Loss: 0.6121, Train Steps/Sec: 1.13
42
+ [2025-10-28 01:09:53] (step=0001500) Train Loss: 0.6052, Train Steps/Sec: 1.13
43
+ [2025-10-28 01:11:21] (step=0001600) Train Loss: 0.6009, Train Steps/Sec: 1.13
44
+ [2025-10-28 01:12:49] (step=0001700) Train Loss: 0.5963, Train Steps/Sec: 1.13
45
+ [2025-10-28 01:14:18] (step=0001800) Train Loss: 0.5906, Train Steps/Sec: 1.12
46
+ [2025-10-28 01:15:46] (step=0001900) Train Loss: 0.5862, Train Steps/Sec: 1.13
47
+ [2025-10-28 01:17:15] (step=0002000) Train Loss: 0.5809, Train Steps/Sec: 1.13
48
+ [2025-10-28 01:18:43] (step=0002100) Train Loss: 0.5784, Train Steps/Sec: 1.13
49
+ [2025-10-28 01:20:11] (step=0002200) Train Loss: 0.5764, Train Steps/Sec: 1.13
50
+ [2025-10-28 01:21:39] (step=0002300) Train Loss: 0.5706, Train Steps/Sec: 1.13
51
+ [2025-10-28 01:23:07] (step=0002400) Train Loss: 0.5691, Train Steps/Sec: 1.13
52
+ [2025-10-28 01:24:36] (step=0002500) Train Loss: 0.5660, Train Steps/Sec: 1.13
53
+ [2025-10-28 01:24:38] Beginning epoch 2...
54
+ [2025-10-28 01:26:07] (step=0002600) Train Loss: 0.5638, Train Steps/Sec: 1.09
55
+ [2025-10-28 01:27:36] (step=0002700) Train Loss: 0.5596, Train Steps/Sec: 1.13
56
+ [2025-10-28 01:29:04] (step=0002800) Train Loss: 0.5581, Train Steps/Sec: 1.13
57
+ [2025-10-28 01:30:32] (step=0002900) Train Loss: 0.5557, Train Steps/Sec: 1.13
58
+ [2025-10-28 01:32:00] (step=0003000) Train Loss: 0.5530, Train Steps/Sec: 1.13
59
+ [2025-10-28 01:33:28] (step=0003100) Train Loss: 0.5527, Train Steps/Sec: 1.13
60
+ [2025-10-28 01:34:57] (step=0003200) Train Loss: 0.5509, Train Steps/Sec: 1.13
61
+ [2025-10-28 01:36:25] (step=0003300) Train Loss: 0.5487, Train Steps/Sec: 1.14
62
+ [2025-10-28 01:37:53] (step=0003400) Train Loss: 0.5481, Train Steps/Sec: 1.13
63
+ [2025-10-28 01:39:21] (step=0003500) Train Loss: 0.5462, Train Steps/Sec: 1.13
64
+ [2025-10-28 01:40:49] (step=0003600) Train Loss: 0.5448, Train Steps/Sec: 1.13
65
+ [2025-10-28 01:42:18] (step=0003700) Train Loss: 0.5432, Train Steps/Sec: 1.14
66
+ [2025-10-28 01:43:05] Beginning epoch 3...
67
+ [2025-10-28 01:43:48] (step=0003800) Train Loss: 0.5424, Train Steps/Sec: 1.10
68
+ [2025-10-28 01:45:17] (step=0003900) Train Loss: 0.5407, Train Steps/Sec: 1.13
69
+ [2025-10-28 01:46:45] (step=0004000) Train Loss: 0.5386, Train Steps/Sec: 1.13
70
+ [2025-10-28 01:48:13] (step=0004100) Train Loss: 0.5378, Train Steps/Sec: 1.13
71
+ [2025-10-28 01:49:41] (step=0004200) Train Loss: 0.5351, Train Steps/Sec: 1.13
72
+ [2025-10-28 01:51:10] (step=0004300) Train Loss: 0.5338, Train Steps/Sec: 1.13
73
+ [2025-10-28 01:52:38] (step=0004400) Train Loss: 0.5349, Train Steps/Sec: 1.13
74
+ [2025-10-28 01:54:06] (step=0004500) Train Loss: 0.5344, Train Steps/Sec: 1.13
75
+ [2025-10-28 01:55:34] (step=0004600) Train Loss: 0.5316, Train Steps/Sec: 1.13
76
+ [2025-10-28 01:57:03] (step=0004700) Train Loss: 0.5313, Train Steps/Sec: 1.13
77
+ [2025-10-28 01:58:31] (step=0004800) Train Loss: 0.5307, Train Steps/Sec: 1.13
78
+ [2025-10-28 01:59:59] (step=0004900) Train Loss: 0.5293, Train Steps/Sec: 1.13
79
+ [2025-10-28 02:01:27] (step=0005000) Train Loss: 0.5278, Train Steps/Sec: 1.13
80
+ [2025-10-28 02:01:32] Beginning epoch 4...
81
+ [2025-10-28 02:02:58] (step=0005100) Train Loss: 0.5278, Train Steps/Sec: 1.10
82
+ [2025-10-28 02:04:27] (step=0005200) Train Loss: 0.5252, Train Steps/Sec: 1.12
83
+ [2025-10-28 02:05:56] (step=0005300) Train Loss: 0.5249, Train Steps/Sec: 1.13
84
+ [2025-10-28 02:07:24] (step=0005400) Train Loss: 0.5259, Train Steps/Sec: 1.13
85
+ [2025-10-28 02:08:52] (step=0005500) Train Loss: 0.5241, Train Steps/Sec: 1.13
86
+ [2025-10-28 02:10:20] (step=0005600) Train Loss: 0.5228, Train Steps/Sec: 1.13
87
+ [2025-10-28 02:11:48] (step=0005700) Train Loss: 0.5226, Train Steps/Sec: 1.13
88
+ [2025-10-28 02:13:17] (step=0005800) Train Loss: 0.5228, Train Steps/Sec: 1.13
89
+ [2025-10-28 02:14:45] (step=0005900) Train Loss: 0.5212, Train Steps/Sec: 1.13
90
+ [2025-10-28 02:16:13] (step=0006000) Train Loss: 0.5211, Train Steps/Sec: 1.13
91
+ [2025-10-28 02:17:42] (step=0006100) Train Loss: 0.5198, Train Steps/Sec: 1.13
92
+ [2025-10-28 02:19:10] (step=0006200) Train Loss: 0.5180, Train Steps/Sec: 1.13
93
+ [2025-10-28 02:19:59] Beginning epoch 5...
94
+ [2025-10-28 02:20:41] (step=0006300) Train Loss: 0.5181, Train Steps/Sec: 1.10
95
+ [2025-10-28 02:22:09] (step=0006400) Train Loss: 0.5184, Train Steps/Sec: 1.13
96
+ [2025-10-28 02:23:37] (step=0006500) Train Loss: 0.5179, Train Steps/Sec: 1.13
97
+ [2025-10-28 02:25:06] (step=0006600) Train Loss: 0.5176, Train Steps/Sec: 1.13
98
+ [2025-10-28 02:26:34] (step=0006700) Train Loss: 0.5145, Train Steps/Sec: 1.13
99
+ [2025-10-28 02:28:02] (step=0006800) Train Loss: 0.5169, Train Steps/Sec: 1.13
100
+ [2025-10-28 02:29:31] (step=0006900) Train Loss: 0.5169, Train Steps/Sec: 1.13
101
+ [2025-10-28 02:30:59] (step=0007000) Train Loss: 0.5147, Train Steps/Sec: 1.13
102
+ [2025-10-28 02:32:27] (step=0007100) Train Loss: 0.5138, Train Steps/Sec: 1.13
103
+ [2025-10-28 02:33:55] (step=0007200) Train Loss: 0.5128, Train Steps/Sec: 1.13
104
+ [2025-10-28 02:35:24] (step=0007300) Train Loss: 0.5141, Train Steps/Sec: 1.13
105
+ [2025-10-28 02:36:52] (step=0007400) Train Loss: 0.5109, Train Steps/Sec: 1.13
106
+ [2025-10-28 02:38:20] (step=0007500) Train Loss: 0.5129, Train Steps/Sec: 1.13
107
+ [2025-10-28 02:38:26] Beginning epoch 6...
108
+ [2025-10-28 02:39:51] (step=0007600) Train Loss: 0.5113, Train Steps/Sec: 1.10
109
+ [2025-10-28 02:41:20] (step=0007700) Train Loss: 0.5124, Train Steps/Sec: 1.13
110
+ [2025-10-28 02:42:48] (step=0007800) Train Loss: 0.5094, Train Steps/Sec: 1.13
111
+ [2025-10-28 02:44:16] (step=0007900) Train Loss: 0.5098, Train Steps/Sec: 1.13
112
+ [2025-10-28 02:45:45] (step=0008000) Train Loss: 0.5111, Train Steps/Sec: 1.13
113
+ [2025-10-28 02:47:13] (step=0008100) Train Loss: 0.5100, Train Steps/Sec: 1.13
114
+ [2025-10-28 02:48:41] (step=0008200) Train Loss: 0.5099, Train Steps/Sec: 1.13
115
+ [2025-10-28 02:50:09] (step=0008300) Train Loss: 0.5087, Train Steps/Sec: 1.13
116
+ [2025-10-28 02:51:37] (step=0008400) Train Loss: 0.5083, Train Steps/Sec: 1.13
117
+ [2025-10-28 02:53:06] (step=0008500) Train Loss: 0.5075, Train Steps/Sec: 1.13
118
+ [2025-10-28 02:54:34] (step=0008600) Train Loss: 0.5060, Train Steps/Sec: 1.13
119
+ [2025-10-28 02:56:03] (step=0008700) Train Loss: 0.5069, Train Steps/Sec: 1.13
120
+ [2025-10-28 02:56:53] Beginning epoch 7...
121
+ [2025-10-28 02:57:34] (step=0008800) Train Loss: 0.5077, Train Steps/Sec: 1.10
122
+ [2025-10-28 02:59:02] (step=0008900) Train Loss: 0.5064, Train Steps/Sec: 1.13
123
+ [2025-10-28 03:00:30] (step=0009000) Train Loss: 0.5050, Train Steps/Sec: 1.13
124
+ [2025-10-28 03:01:58] (step=0009100) Train Loss: 0.5055, Train Steps/Sec: 1.13
125
+ [2025-10-28 03:03:26] (step=0009200) Train Loss: 0.5061, Train Steps/Sec: 1.13
126
+ [2025-10-28 03:04:55] (step=0009300) Train Loss: 0.5044, Train Steps/Sec: 1.13
127
+ [2025-10-28 03:06:24] (step=0009400) Train Loss: 0.5034, Train Steps/Sec: 1.13
128
+ [2025-10-28 03:07:52] (step=0009500) Train Loss: 0.5040, Train Steps/Sec: 1.13
129
+ [2025-10-28 03:09:20] (step=0009600) Train Loss: 0.5043, Train Steps/Sec: 1.13
130
+ [2025-10-28 03:10:48] (step=0009700) Train Loss: 0.5032, Train Steps/Sec: 1.13
131
+ [2025-10-28 03:12:16] (step=0009800) Train Loss: 0.5030, Train Steps/Sec: 1.13
132
+ [2025-10-28 03:13:44] (step=0009900) Train Loss: 0.5016, Train Steps/Sec: 1.13
133
+ [2025-10-28 03:15:13] (step=0010000) Train Loss: 0.5033, Train Steps/Sec: 1.13
134
+ [2025-10-28 03:15:20] Beginning epoch 8...
135
+ [2025-10-28 03:16:44] (step=0010100) Train Loss: 0.5023, Train Steps/Sec: 1.10
136
+ [2025-10-28 03:18:12] (step=0010200) Train Loss: 0.5012, Train Steps/Sec: 1.13
137
+ [2025-10-28 03:19:41] (step=0010300) Train Loss: 0.5021, Train Steps/Sec: 1.13
138
+ [2025-10-28 03:21:09] (step=0010400) Train Loss: 0.5017, Train Steps/Sec: 1.13
139
+ [2025-10-28 03:22:37] (step=0010500) Train Loss: 0.5004, Train Steps/Sec: 1.13
140
+ [2025-10-28 03:24:06] (step=0010600) Train Loss: 0.4992, Train Steps/Sec: 1.13
141
+ [2025-10-28 03:25:34] (step=0010700) Train Loss: 0.4996, Train Steps/Sec: 1.13
142
+ [2025-10-28 03:27:02] (step=0010800) Train Loss: 0.4990, Train Steps/Sec: 1.13
143
+ [2025-10-28 03:28:30] (step=0010900) Train Loss: 0.5015, Train Steps/Sec: 1.13
144
+ [2025-10-28 03:29:58] (step=0011000) Train Loss: 0.5013, Train Steps/Sec: 1.13
145
+ [2025-10-28 03:31:27] (step=0011100) Train Loss: 0.4980, Train Steps/Sec: 1.13
146
+ [2025-10-28 03:32:55] (step=0011200) Train Loss: 0.4980, Train Steps/Sec: 1.13
147
+ [2025-10-28 03:33:48] Beginning epoch 9...
148
+ [2025-10-28 03:34:26] (step=0011300) Train Loss: 0.4992, Train Steps/Sec: 1.10
149
+ [2025-10-28 03:35:54] (step=0011400) Train Loss: 0.4988, Train Steps/Sec: 1.13
150
+ [2025-10-28 03:37:23] (step=0011500) Train Loss: 0.4977, Train Steps/Sec: 1.13
151
+ [2025-10-28 03:38:51] (step=0011600) Train Loss: 0.4973, Train Steps/Sec: 1.13
152
+ [2025-10-28 03:40:19] (step=0011700) Train Loss: 0.4955, Train Steps/Sec: 1.13
153
+ [2025-10-28 03:41:47] (step=0011800) Train Loss: 0.4991, Train Steps/Sec: 1.13
154
+ [2025-10-28 03:43:15] (step=0011900) Train Loss: 0.4969, Train Steps/Sec: 1.13
155
+ [2025-10-28 03:44:45] (step=0012000) Train Loss: 0.4969, Train Steps/Sec: 1.12
156
+ [2025-10-28 03:46:13] (step=0012100) Train Loss: 0.4967, Train Steps/Sec: 1.13
157
+ [2025-10-28 03:47:41] (step=0012200) Train Loss: 0.4953, Train Steps/Sec: 1.13
158
+ [2025-10-28 03:49:09] (step=0012300) Train Loss: 0.4959, Train Steps/Sec: 1.13
159
+ [2025-10-28 03:50:38] (step=0012400) Train Loss: 0.4953, Train Steps/Sec: 1.13
160
+ [2025-10-28 03:52:06] (step=0012500) Train Loss: 0.4946, Train Steps/Sec: 1.13
161
+ [2025-10-28 03:52:15] Beginning epoch 10...
162
+ [2025-10-28 03:53:37] (step=0012600) Train Loss: 0.4942, Train Steps/Sec: 1.10
163
+ [2025-10-28 03:55:05] (step=0012700) Train Loss: 0.4962, Train Steps/Sec: 1.13
164
+ [2025-10-28 03:56:34] (step=0012800) Train Loss: 0.4946, Train Steps/Sec: 1.13
165
+ [2025-10-28 03:58:02] (step=0012900) Train Loss: 0.4924, Train Steps/Sec: 1.13
166
+ [2025-10-28 03:59:30] (step=0013000) Train Loss: 0.4945, Train Steps/Sec: 1.13
167
+ [2025-10-28 04:00:58] (step=0013100) Train Loss: 0.4941, Train Steps/Sec: 1.13
168
+ [2025-10-28 04:02:27] (step=0013200) Train Loss: 0.4945, Train Steps/Sec: 1.13
169
+ [2025-10-28 04:03:55] (step=0013300) Train Loss: 0.4938, Train Steps/Sec: 1.13
170
+ [2025-10-28 04:05:23] (step=0013400) Train Loss: 0.4944, Train Steps/Sec: 1.13
171
+ [2025-10-28 04:06:51] (step=0013500) Train Loss: 0.4931, Train Steps/Sec: 1.13
172
+ [2025-10-28 04:08:20] (step=0013600) Train Loss: 0.4940, Train Steps/Sec: 1.13
173
+ [2025-10-28 04:09:48] (step=0013700) Train Loss: 0.4931, Train Steps/Sec: 1.13
174
+ [2025-10-28 04:10:43] Beginning epoch 11...
175
+ [2025-10-28 04:11:20] (step=0013800) Train Loss: 0.4914, Train Steps/Sec: 1.09
176
+ [2025-10-28 04:12:48] (step=0013900) Train Loss: 0.4925, Train Steps/Sec: 1.13
177
+ [2025-10-28 04:14:16] (step=0014000) Train Loss: 0.4926, Train Steps/Sec: 1.13
178
+ [2025-10-28 04:15:44] (step=0014100) Train Loss: 0.4914, Train Steps/Sec: 1.13
179
+ [2025-10-28 04:17:13] (step=0014200) Train Loss: 0.4910, Train Steps/Sec: 1.13
180
+ [2025-10-28 04:18:41] (step=0014300) Train Loss: 0.4910, Train Steps/Sec: 1.13
181
+ [2025-10-28 04:20:09] (step=0014400) Train Loss: 0.4920, Train Steps/Sec: 1.13
182
+ [2025-10-28 04:21:38] (step=0014500) Train Loss: 0.4909, Train Steps/Sec: 1.13
183
+ [2025-10-28 04:23:06] (step=0014600) Train Loss: 0.4922, Train Steps/Sec: 1.13
184
+ [2025-10-28 04:24:34] (step=0014700) Train Loss: 0.4914, Train Steps/Sec: 1.13
185
+ [2025-10-28 04:26:02] (step=0014800) Train Loss: 0.4913, Train Steps/Sec: 1.13
186
+ [2025-10-28 04:27:31] (step=0014900) Train Loss: 0.4911, Train Steps/Sec: 1.13
187
+ [2025-10-28 04:28:59] (step=0015000) Train Loss: 0.4895, Train Steps/Sec: 1.13
188
+ [2025-10-28 04:29:10] Beginning epoch 12...
189
+ [2025-10-28 04:30:30] (step=0015100) Train Loss: 0.4903, Train Steps/Sec: 1.10
190
+ [2025-10-28 04:31:58] (step=0015200) Train Loss: 0.4894, Train Steps/Sec: 1.13
191
+ [2025-10-28 04:33:26] (step=0015300) Train Loss: 0.4917, Train Steps/Sec: 1.13
192
+ [2025-10-28 04:34:55] (step=0015400) Train Loss: 0.4906, Train Steps/Sec: 1.12
193
+ [2025-10-28 04:36:24] (step=0015500) Train Loss: 0.4903, Train Steps/Sec: 1.13
194
+ [2025-10-28 04:37:52] (step=0015600) Train Loss: 0.4895, Train Steps/Sec: 1.13
195
+ [2025-10-28 04:39:20] (step=0015700) Train Loss: 0.4902, Train Steps/Sec: 1.13
196
+ [2025-10-28 04:40:48] (step=0015800) Train Loss: 0.4880, Train Steps/Sec: 1.13
197
+ [2025-10-28 04:42:16] (step=0015900) Train Loss: 0.4896, Train Steps/Sec: 1.13
198
+ [2025-10-28 04:43:45] (step=0016000) Train Loss: 0.4891, Train Steps/Sec: 1.13
199
+ [2025-10-28 04:45:13] (step=0016100) Train Loss: 0.4903, Train Steps/Sec: 1.13
200
+ [2025-10-28 04:46:41] (step=0016200) Train Loss: 0.4878, Train Steps/Sec: 1.13
201
+ [2025-10-28 04:47:37] Beginning epoch 13...
202
+ [2025-10-28 04:48:12] (step=0016300) Train Loss: 0.4889, Train Steps/Sec: 1.10
203
+ [2025-10-28 04:49:40] (step=0016400) Train Loss: 0.4893, Train Steps/Sec: 1.13
204
+ [2025-10-28 04:51:09] (step=0016500) Train Loss: 0.4883, Train Steps/Sec: 1.13
205
+ [2025-10-28 04:52:37] (step=0016600) Train Loss: 0.4869, Train Steps/Sec: 1.13
206
+ [2025-10-28 04:54:05] (step=0016700) Train Loss: 0.4861, Train Steps/Sec: 1.13
207
+ [2025-10-28 04:55:33] (step=0016800) Train Loss: 0.4876, Train Steps/Sec: 1.13
208
+ [2025-10-28 04:57:01] (step=0016900) Train Loss: 0.4889, Train Steps/Sec: 1.13
209
+ [2025-10-28 04:58:30] (step=0017000) Train Loss: 0.4891, Train Steps/Sec: 1.13
210
+ [2025-10-28 04:59:59] (step=0017100) Train Loss: 0.4873, Train Steps/Sec: 1.12
211
+ [2025-10-28 05:01:27] (step=0017200) Train Loss: 0.4881, Train Steps/Sec: 1.13
212
+ [2025-10-28 05:02:55] (step=0017300) Train Loss: 0.4863, Train Steps/Sec: 1.13
213
+ [2025-10-28 05:04:23] (step=0017400) Train Loss: 0.4873, Train Steps/Sec: 1.13
214
+ [2025-10-28 05:05:51] (step=0017500) Train Loss: 0.4871, Train Steps/Sec: 1.13
215
+ [2025-10-28 05:06:04] Beginning epoch 14...
216
+ [2025-10-28 05:07:22] (step=0017600) Train Loss: 0.4854, Train Steps/Sec: 1.10
217
+ [2025-10-28 05:08:50] (step=0017700) Train Loss: 0.4870, Train Steps/Sec: 1.13
218
+ [2025-10-28 05:10:19] (step=0017800) Train Loss: 0.4860, Train Steps/Sec: 1.13
219
+ [2025-10-28 05:11:47] (step=0017900) Train Loss: 0.4858, Train Steps/Sec: 1.13
220
+ [2025-10-28 05:13:15] (step=0018000) Train Loss: 0.4866, Train Steps/Sec: 1.13
221
+ [2025-10-28 05:14:44] (step=0018100) Train Loss: 0.4855, Train Steps/Sec: 1.13
222
+ [2025-10-28 05:16:12] (step=0018200) Train Loss: 0.4853, Train Steps/Sec: 1.13
223
+ [2025-10-28 05:17:40] (step=0018300) Train Loss: 0.4866, Train Steps/Sec: 1.13
224
+ [2025-10-28 05:19:08] (step=0018400) Train Loss: 0.4867, Train Steps/Sec: 1.13
225
+ [2025-10-28 05:20:36] (step=0018500) Train Loss: 0.4851, Train Steps/Sec: 1.13
226
+ [2025-10-28 05:22:05] (step=0018600) Train Loss: 0.4847, Train Steps/Sec: 1.13
227
+ [2025-10-28 05:23:33] (step=0018700) Train Loss: 0.4845, Train Steps/Sec: 1.14
228
+ [2025-10-28 05:24:31] Beginning epoch 15...
229
+ [2025-10-28 05:25:04] (step=0018800) Train Loss: 0.4830, Train Steps/Sec: 1.10
230
+ [2025-10-28 05:26:32] (step=0018900) Train Loss: 0.4847, Train Steps/Sec: 1.13
231
+ [2025-10-28 05:28:00] (step=0019000) Train Loss: 0.4844, Train Steps/Sec: 1.13
232
+ [2025-10-28 05:29:28] (step=0019100) Train Loss: 0.4844, Train Steps/Sec: 1.13
233
+ [2025-10-28 05:30:57] (step=0019200) Train Loss: 0.4847, Train Steps/Sec: 1.13
234
+ [2025-10-28 05:32:25] (step=0019300) Train Loss: 0.4846, Train Steps/Sec: 1.13
235
+ [2025-10-28 05:33:53] (step=0019400) Train Loss: 0.4842, Train Steps/Sec: 1.14
236
+ [2025-10-28 05:35:21] (step=0019500) Train Loss: 0.4827, Train Steps/Sec: 1.13
237
+ [2025-10-28 05:36:50] (step=0019600) Train Loss: 0.4835, Train Steps/Sec: 1.13
238
+ [2025-10-28 05:38:18] (step=0019700) Train Loss: 0.4837, Train Steps/Sec: 1.13
239
+ [2025-10-28 05:39:46] (step=0019800) Train Loss: 0.4834, Train Steps/Sec: 1.13
240
+ [2025-10-28 05:41:14] (step=0019900) Train Loss: 0.4831, Train Steps/Sec: 1.13
241
+ [2025-10-28 05:42:42] (step=0020000) Train Loss: 0.4846, Train Steps/Sec: 1.13
242
+ [2025-10-28 05:42:57] Beginning epoch 16...
243
+ [2025-10-28 05:44:14] (step=0020100) Train Loss: 0.4828, Train Steps/Sec: 1.10
244
+ [2025-10-28 05:45:42] (step=0020200) Train Loss: 0.4840, Train Steps/Sec: 1.13
245
+ [2025-10-28 05:47:10] (step=0020300) Train Loss: 0.4854, Train Steps/Sec: 1.13
246
+ [2025-10-28 05:48:38] (step=0020400) Train Loss: 0.4845, Train Steps/Sec: 1.13
247
+ [2025-10-28 05:50:07] (step=0020500) Train Loss: 0.4837, Train Steps/Sec: 1.12
248
+ [2025-10-28 05:51:35] (step=0020600) Train Loss: 0.4812, Train Steps/Sec: 1.13
249
+ [2025-10-28 05:53:03] (step=0020700) Train Loss: 0.4827, Train Steps/Sec: 1.13
250
+ [2025-10-28 05:54:31] (step=0020800) Train Loss: 0.4818, Train Steps/Sec: 1.13
251
+ [2025-10-28 05:56:00] (step=0020900) Train Loss: 0.4824, Train Steps/Sec: 1.13
252
+ [2025-10-28 05:57:28] (step=0021000) Train Loss: 0.4823, Train Steps/Sec: 1.13
253
+ [2025-10-28 05:58:56] (step=0021100) Train Loss: 0.4818, Train Steps/Sec: 1.13
254
+ [2025-10-28 06:00:24] (step=0021200) Train Loss: 0.4812, Train Steps/Sec: 1.14
255
+ [2025-10-28 06:01:24] Beginning epoch 17...
256
+ [2025-10-28 06:01:56] (step=0021300) Train Loss: 0.4821, Train Steps/Sec: 1.09
257
+ [2025-10-28 06:03:24] (step=0021400) Train Loss: 0.4815, Train Steps/Sec: 1.13
258
+ [2025-10-28 06:04:52] (step=0021500) Train Loss: 0.4829, Train Steps/Sec: 1.13
259
+ [2025-10-28 06:06:20] (step=0021600) Train Loss: 0.4815, Train Steps/Sec: 1.13
260
+ [2025-10-28 06:07:48] (step=0021700) Train Loss: 0.4819, Train Steps/Sec: 1.13
261
+ [2025-10-28 06:09:16] (step=0021800) Train Loss: 0.4824, Train Steps/Sec: 1.13
262
+ [2025-10-28 06:10:44] (step=0021900) Train Loss: 0.4802, Train Steps/Sec: 1.13
263
+ [2025-10-28 06:12:13] (step=0022000) Train Loss: 0.4808, Train Steps/Sec: 1.13
264
+ [2025-10-28 06:13:41] (step=0022100) Train Loss: 0.4803, Train Steps/Sec: 1.13
265
+ [2025-10-28 06:15:09] (step=0022200) Train Loss: 0.4817, Train Steps/Sec: 1.13
266
+ [2025-10-28 06:16:38] (step=0022300) Train Loss: 0.4827, Train Steps/Sec: 1.13
267
+ [2025-10-28 06:18:06] (step=0022400) Train Loss: 0.4801, Train Steps/Sec: 1.13
268
+ [2025-10-28 06:19:34] (step=0022500) Train Loss: 0.4825, Train Steps/Sec: 1.13
269
+ [2025-10-28 06:19:50] Beginning epoch 18...
270
+ [2025-10-28 06:21:05] (step=0022600) Train Loss: 0.4821, Train Steps/Sec: 1.10
271
+ [2025-10-28 06:22:33] (step=0022700) Train Loss: 0.4795, Train Steps/Sec: 1.13
272
+ [2025-10-28 06:24:01] (step=0022800) Train Loss: 0.4804, Train Steps/Sec: 1.13
273
+ [2025-10-28 06:25:29] (step=0022900) Train Loss: 0.4813, Train Steps/Sec: 1.13
274
+ [2025-10-28 06:26:58] (step=0023000) Train Loss: 0.4806, Train Steps/Sec: 1.13
275
+ [2025-10-28 06:28:26] (step=0023100) Train Loss: 0.4801, Train Steps/Sec: 1.13
276
+ [2025-10-28 06:29:55] (step=0023200) Train Loss: 0.4811, Train Steps/Sec: 1.13
277
+ [2025-10-28 06:31:23] (step=0023300) Train Loss: 0.4804, Train Steps/Sec: 1.13
278
+ [2025-10-28 06:32:51] (step=0023400) Train Loss: 0.4792, Train Steps/Sec: 1.13
279
+ [2025-10-28 06:34:19] (step=0023500) Train Loss: 0.4787, Train Steps/Sec: 1.13
280
+ [2025-10-28 06:35:47] (step=0023600) Train Loss: 0.4805, Train Steps/Sec: 1.13
281
+ [2025-10-28 06:37:16] (step=0023700) Train Loss: 0.4780, Train Steps/Sec: 1.13
282
+ [2025-10-28 06:38:17] Beginning epoch 19...
283
+ [2025-10-28 06:38:47] (step=0023800) Train Loss: 0.4803, Train Steps/Sec: 1.10
284
+ [2025-10-28 06:40:16] (step=0023900) Train Loss: 0.4805, Train Steps/Sec: 1.13
285
+ [2025-10-28 06:41:44] (step=0024000) Train Loss: 0.4779, Train Steps/Sec: 1.13
286
+ [2025-10-28 06:43:12] (step=0024100) Train Loss: 0.4802, Train Steps/Sec: 1.13
287
+ [2025-10-28 06:44:40] (step=0024200) Train Loss: 0.4795, Train Steps/Sec: 1.13
288
+ [2025-10-28 06:46:08] (step=0024300) Train Loss: 0.4795, Train Steps/Sec: 1.13
289
+ [2025-10-28 06:47:36] (step=0024400) Train Loss: 0.4790, Train Steps/Sec: 1.13
290
+ [2025-10-28 06:49:05] (step=0024500) Train Loss: 0.4787, Train Steps/Sec: 1.13
291
+ [2025-10-28 06:50:33] (step=0024600) Train Loss: 0.4797, Train Steps/Sec: 1.13
292
+ [2025-10-28 06:52:01] (step=0024700) Train Loss: 0.4787, Train Steps/Sec: 1.13
293
+ [2025-10-28 06:53:29] (step=0024800) Train Loss: 0.4785, Train Steps/Sec: 1.13
294
+ [2025-10-28 06:54:58] (step=0024900) Train Loss: 0.4774, Train Steps/Sec: 1.13
295
+ [2025-10-28 06:56:26] (step=0025000) Train Loss: 0.4778, Train Steps/Sec: 1.13
296
+ [2025-10-28 06:57:23] Saved checkpoint to results/stage2/hfdata/lightningdit-xl-spatialpe-vit-l-bf16/checkpoints/0025000.pt
297
+ [2025-10-28 06:57:23] Generating EMA samples...
298
+ [2025-10-28 06:57:52] Generating EMA samples done.
299
+ [2025-10-28 06:58:09] Beginning epoch 20...
300
+ [2025-10-28 06:59:23] (step=0025100) Train Loss: 0.4796, Train Steps/Sec: 0.57
301
+ [2025-10-28 07:00:51] (step=0025200) Train Loss: 0.4769, Train Steps/Sec: 1.13
302
+ [2025-10-28 07:02:19] (step=0025300) Train Loss: 0.4798, Train Steps/Sec: 1.13
303
+ [2025-10-28 07:03:47] (step=0025400) Train Loss: 0.4780, Train Steps/Sec: 1.13
304
+ [2025-10-28 07:05:15] (step=0025500) Train Loss: 0.4792, Train Steps/Sec: 1.13
305
+ [2025-10-28 07:06:44] (step=0025600) Train Loss: 0.4774, Train Steps/Sec: 1.13
306
+ [2025-10-28 07:08:12] (step=0025700) Train Loss: 0.4764, Train Steps/Sec: 1.13
307
+ [2025-10-28 07:09:40] (step=0025800) Train Loss: 0.4786, Train Steps/Sec: 1.13
308
+ [2025-10-28 07:11:09] (step=0025900) Train Loss: 0.4774, Train Steps/Sec: 1.13
309
+ [2025-10-28 07:12:37] (step=0026000) Train Loss: 0.4789, Train Steps/Sec: 1.13
310
+ [2025-10-28 07:14:05] (step=0026100) Train Loss: 0.4773, Train Steps/Sec: 1.13
311
+ [2025-10-28 07:15:33] (step=0026200) Train Loss: 0.4775, Train Steps/Sec: 1.13
312
+ [2025-10-28 07:16:37] Beginning epoch 21...
313
+ [2025-10-28 07:17:05] (step=0026300) Train Loss: 0.4768, Train Steps/Sec: 1.10
314
+ [2025-10-28 07:18:33] (step=0026400) Train Loss: 0.4776, Train Steps/Sec: 1.13
315
+ [2025-10-28 07:20:02] (step=0026500) Train Loss: 0.4750, Train Steps/Sec: 1.13
316
+ [2025-10-28 07:21:30] (step=0026600) Train Loss: 0.4776, Train Steps/Sec: 1.13
317
+ [2025-10-28 07:22:58] (step=0026700) Train Loss: 0.4755, Train Steps/Sec: 1.13
318
+ [2025-10-28 07:24:26] (step=0026800) Train Loss: 0.4761, Train Steps/Sec: 1.13
319
+ [2025-10-28 07:25:54] (step=0026900) Train Loss: 0.4770, Train Steps/Sec: 1.13
320
+ [2025-10-28 07:27:22] (step=0027000) Train Loss: 0.4760, Train Steps/Sec: 1.13
321
+ [2025-10-28 07:28:51] (step=0027100) Train Loss: 0.4784, Train Steps/Sec: 1.13
322
+ [2025-10-28 07:30:19] (step=0027200) Train Loss: 0.4765, Train Steps/Sec: 1.13
323
+ [2025-10-28 07:31:47] (step=0027300) Train Loss: 0.4758, Train Steps/Sec: 1.13
324
+ [2025-10-28 07:33:15] (step=0027400) Train Loss: 0.4755, Train Steps/Sec: 1.13
325
+ [2025-10-28 07:34:44] (step=0027500) Train Loss: 0.4759, Train Steps/Sec: 1.13
326
+ [2025-10-28 07:35:04] Beginning epoch 22...
327
+ [2025-10-28 07:36:15] (step=0027600) Train Loss: 0.4741, Train Steps/Sec: 1.09
328
+ [2025-10-28 07:37:44] (step=0027700) Train Loss: 0.4758, Train Steps/Sec: 1.13
329
+ [2025-10-28 07:39:12] (step=0027800) Train Loss: 0.4738, Train Steps/Sec: 1.13
330
+ [2025-10-28 07:40:40] (step=0027900) Train Loss: 0.4755, Train Steps/Sec: 1.13
331
+ [2025-10-28 07:42:08] (step=0028000) Train Loss: 0.4759, Train Steps/Sec: 1.13
332
+ [2025-10-28 07:43:37] (step=0028100) Train Loss: 0.4764, Train Steps/Sec: 1.13
333
+ [2025-10-28 07:45:06] (step=0028200) Train Loss: 0.4762, Train Steps/Sec: 1.13
334
+ [2025-10-28 07:46:34] (step=0028300) Train Loss: 0.4745, Train Steps/Sec: 1.13
335
+ [2025-10-28 07:48:02] (step=0028400) Train Loss: 0.4753, Train Steps/Sec: 1.13
336
+ [2025-10-28 07:49:30] (step=0028500) Train Loss: 0.4752, Train Steps/Sec: 1.13
337
+ [2025-10-28 07:50:59] (step=0028600) Train Loss: 0.4759, Train Steps/Sec: 1.13
338
+ [2025-10-28 07:52:27] (step=0028700) Train Loss: 0.4769, Train Steps/Sec: 1.13
339
+ [2025-10-28 07:53:32] Beginning epoch 23...
340
+ [2025-10-28 07:53:58] (step=0028800) Train Loss: 0.4749, Train Steps/Sec: 1.10
341
+ [2025-10-28 07:55:26] (step=0028900) Train Loss: 0.4737, Train Steps/Sec: 1.13
342
+ [2025-10-28 07:56:55] (step=0029000) Train Loss: 0.4740, Train Steps/Sec: 1.13
343
+ [2025-10-28 07:58:23] (step=0029100) Train Loss: 0.4747, Train Steps/Sec: 1.13
344
+ [2025-10-28 07:59:51] (step=0029200) Train Loss: 0.4742, Train Steps/Sec: 1.13
345
+ [2025-10-28 08:01:19] (step=0029300) Train Loss: 0.4733, Train Steps/Sec: 1.13
346
+ [2025-10-28 08:02:48] (step=0029400) Train Loss: 0.4753, Train Steps/Sec: 1.13
347
+ [2025-10-28 08:04:16] (step=0029500) Train Loss: 0.4742, Train Steps/Sec: 1.13
348
+ [2025-10-28 08:05:44] (step=0029600) Train Loss: 0.4743, Train Steps/Sec: 1.13
349
+ [2025-10-28 08:07:12] (step=0029700) Train Loss: 0.4740, Train Steps/Sec: 1.13
350
+ [2025-10-28 08:08:41] (step=0029800) Train Loss: 0.4746, Train Steps/Sec: 1.13
351
+ [2025-10-28 08:10:09] (step=0029900) Train Loss: 0.4742, Train Steps/Sec: 1.13
352
+ [2025-10-28 08:11:37] (step=0030000) Train Loss: 0.4750, Train Steps/Sec: 1.13
353
+ [2025-10-28 08:11:59] Beginning epoch 24...
354
+ [2025-10-28 08:13:08] (step=0030100) Train Loss: 0.4741, Train Steps/Sec: 1.10
355
+ [2025-10-28 08:14:36] (step=0030200) Train Loss: 0.4749, Train Steps/Sec: 1.13
356
+ [2025-10-28 08:16:05] (step=0030300) Train Loss: 0.4728, Train Steps/Sec: 1.13
357
+ [2025-10-28 08:17:33] (step=0030400) Train Loss: 0.4731, Train Steps/Sec: 1.13
358
+ [2025-10-28 08:19:01] (step=0030500) Train Loss: 0.4750, Train Steps/Sec: 1.13
359
+ [2025-10-28 08:20:29] (step=0030600) Train Loss: 0.4757, Train Steps/Sec: 1.13
360
+ [2025-10-28 08:21:58] (step=0030700) Train Loss: 0.4746, Train Steps/Sec: 1.13
361
+ [2025-10-28 08:23:26] (step=0030800) Train Loss: 0.4724, Train Steps/Sec: 1.13
362
+ [2025-10-28 08:24:54] (step=0030900) Train Loss: 0.4746, Train Steps/Sec: 1.13
363
+ [2025-10-28 08:26:22] (step=0031000) Train Loss: 0.4736, Train Steps/Sec: 1.13
364
+ [2025-10-28 08:27:51] (step=0031100) Train Loss: 0.4724, Train Steps/Sec: 1.13
365
+ [2025-10-28 08:29:19] (step=0031200) Train Loss: 0.4733, Train Steps/Sec: 1.13
366
+ [2025-10-28 08:30:26] Beginning epoch 25...
367
+ [2025-10-28 08:30:50] (step=0031300) Train Loss: 0.4742, Train Steps/Sec: 1.10
368
+ [2025-10-28 08:32:18] (step=0031400) Train Loss: 0.4743, Train Steps/Sec: 1.13
369
+ [2025-10-28 08:33:47] (step=0031500) Train Loss: 0.4751, Train Steps/Sec: 1.13
370
+ [2025-10-28 08:35:15] (step=0031600) Train Loss: 0.4736, Train Steps/Sec: 1.13
371
+ [2025-10-28 08:36:43] (step=0031700) Train Loss: 0.4741, Train Steps/Sec: 1.13
372
+ [2025-10-28 08:38:11] (step=0031800) Train Loss: 0.4736, Train Steps/Sec: 1.13
373
+ [2025-10-28 08:39:39] (step=0031900) Train Loss: 0.4708, Train Steps/Sec: 1.13
374
+ [2025-10-28 08:41:08] (step=0032000) Train Loss: 0.4734, Train Steps/Sec: 1.13
375
+ [2025-10-28 08:42:36] (step=0032100) Train Loss: 0.4734, Train Steps/Sec: 1.13
376
+ [2025-10-28 08:44:04] (step=0032200) Train Loss: 0.4726, Train Steps/Sec: 1.13
377
+ [2025-10-28 08:45:32] (step=0032300) Train Loss: 0.4728, Train Steps/Sec: 1.13
378
+ [2025-10-28 08:47:01] (step=0032400) Train Loss: 0.4729, Train Steps/Sec: 1.13
379
+ [2025-10-28 08:48:29] (step=0032500) Train Loss: 0.4733, Train Steps/Sec: 1.13
380
+ [2025-10-28 08:48:52] Beginning epoch 26...
381
+ [2025-10-28 08:50:00] (step=0032600) Train Loss: 0.4730, Train Steps/Sec: 1.10
382
+ [2025-10-28 08:51:28] (step=0032700) Train Loss: 0.4714, Train Steps/Sec: 1.13
383
+ [2025-10-28 08:52:56] (step=0032800) Train Loss: 0.4736, Train Steps/Sec: 1.13
384
+ [2025-10-28 08:54:25] (step=0032900) Train Loss: 0.4725, Train Steps/Sec: 1.13
385
+ [2025-10-28 08:55:53] (step=0033000) Train Loss: 0.4710, Train Steps/Sec: 1.13
386
+ [2025-10-28 08:57:21] (step=0033100) Train Loss: 0.4736, Train Steps/Sec: 1.13
387
+ [2025-10-28 08:58:50] (step=0033200) Train Loss: 0.4747, Train Steps/Sec: 1.13
388
+ [2025-10-28 09:00:18] (step=0033300) Train Loss: 0.4734, Train Steps/Sec: 1.13
389
+ [2025-10-28 09:01:46] (step=0033400) Train Loss: 0.4716, Train Steps/Sec: 1.13
390
+ [2025-10-28 09:03:14] (step=0033500) Train Loss: 0.4718, Train Steps/Sec: 1.13
391
+ [2025-10-28 09:04:42] (step=0033600) Train Loss: 0.4713, Train Steps/Sec: 1.13
392
+ [2025-10-28 09:06:11] (step=0033700) Train Loss: 0.4726, Train Steps/Sec: 1.13
393
+ [2025-10-28 09:07:19] Beginning epoch 27...
394
+ [2025-10-28 09:07:42] (step=0033800) Train Loss: 0.4714, Train Steps/Sec: 1.10
395
+ [2025-10-28 09:09:10] (step=0033900) Train Loss: 0.4715, Train Steps/Sec: 1.13
396
+ [2025-10-28 09:10:38] (step=0034000) Train Loss: 0.4722, Train Steps/Sec: 1.13
397
+ [2025-10-28 09:12:07] (step=0034100) Train Loss: 0.4730, Train Steps/Sec: 1.13
398
+ [2025-10-28 09:13:35] (step=0034200) Train Loss: 0.4723, Train Steps/Sec: 1.13
399
+ [2025-10-28 09:15:03] (step=0034300) Train Loss: 0.4715, Train Steps/Sec: 1.13
400
+ [2025-10-28 09:16:31] (step=0034400) Train Loss: 0.4708, Train Steps/Sec: 1.13
401
+ [2025-10-28 09:17:59] (step=0034500) Train Loss: 0.4721, Train Steps/Sec: 1.14
402
+ [2025-10-28 09:19:27] (step=0034600) Train Loss: 0.4715, Train Steps/Sec: 1.13
403
+ [2025-10-28 09:20:55] (step=0034700) Train Loss: 0.4723, Train Steps/Sec: 1.13
404
+ [2025-10-28 09:22:24] (step=0034800) Train Loss: 0.4704, Train Steps/Sec: 1.13
405
+ [2025-10-28 09:23:52] (step=0034900) Train Loss: 0.4697, Train Steps/Sec: 1.13
406
+ [2025-10-28 09:25:20] (step=0035000) Train Loss: 0.4709, Train Steps/Sec: 1.13
407
+ [2025-10-28 09:25:45] Beginning epoch 28...
408
+ [2025-10-28 09:26:51] (step=0035100) Train Loss: 0.4712, Train Steps/Sec: 1.10
409
+ [2025-10-28 09:28:20] (step=0035200) Train Loss: 0.4720, Train Steps/Sec: 1.13
410
+ [2025-10-28 09:29:48] (step=0035300) Train Loss: 0.4712, Train Steps/Sec: 1.14
411
+ [2025-10-28 09:31:16] (step=0035400) Train Loss: 0.4710, Train Steps/Sec: 1.13
412
+ [2025-10-28 09:32:44] (step=0035500) Train Loss: 0.4717, Train Steps/Sec: 1.13
413
+ [2025-10-28 09:34:12] (step=0035600) Train Loss: 0.4713, Train Steps/Sec: 1.13
414
+ [2025-10-28 09:35:41] (step=0035700) Train Loss: 0.4703, Train Steps/Sec: 1.13
415
+ [2025-10-28 09:37:09] (step=0035800) Train Loss: 0.4718, Train Steps/Sec: 1.13
416
+ [2025-10-28 09:38:37] (step=0035900) Train Loss: 0.4731, Train Steps/Sec: 1.13
417
+ [2025-10-28 09:40:06] (step=0036000) Train Loss: 0.4704, Train Steps/Sec: 1.13
418
+ [2025-10-28 09:41:34] (step=0036100) Train Loss: 0.4707, Train Steps/Sec: 1.13
419
+ [2025-10-28 09:43:02] (step=0036200) Train Loss: 0.4689, Train Steps/Sec: 1.13
420
+ [2025-10-28 09:44:12] Beginning epoch 29...
421
+ [2025-10-28 09:44:33] (step=0036300) Train Loss: 0.4715, Train Steps/Sec: 1.10
422
+ [2025-10-28 09:46:01] (step=0036400) Train Loss: 0.4703, Train Steps/Sec: 1.13
423
+ [2025-10-28 09:47:29] (step=0036500) Train Loss: 0.4699, Train Steps/Sec: 1.13
424
+ [2025-10-28 09:48:58] (step=0036600) Train Loss: 0.4690, Train Steps/Sec: 1.13
425
+ [2025-10-28 09:50:26] (step=0036700) Train Loss: 0.4714, Train Steps/Sec: 1.13
426
+ [2025-10-28 09:51:54] (step=0036800) Train Loss: 0.4696, Train Steps/Sec: 1.14
427
+ [2025-10-28 09:53:22] (step=0036900) Train Loss: 0.4709, Train Steps/Sec: 1.14
428
+ [2025-10-28 09:54:50] (step=0037000) Train Loss: 0.4698, Train Steps/Sec: 1.14
429
+ [2025-10-28 09:56:18] (step=0037100) Train Loss: 0.4718, Train Steps/Sec: 1.13
430
+ [2025-10-28 09:57:47] (step=0037200) Train Loss: 0.4713, Train Steps/Sec: 1.13
431
+ [2025-10-28 09:59:15] (step=0037300) Train Loss: 0.4700, Train Steps/Sec: 1.14
432
+ [2025-10-28 10:00:43] (step=0037400) Train Loss: 0.4684, Train Steps/Sec: 1.13
433
+ [2025-10-28 10:02:11] (step=0037500) Train Loss: 0.4709, Train Steps/Sec: 1.13
434
+ [2025-10-28 10:02:38] Beginning epoch 30...
435
+ [2025-10-28 10:03:42] (step=0037600) Train Loss: 0.4706, Train Steps/Sec: 1.10
436
+ [2025-10-28 10:05:10] (step=0037700) Train Loss: 0.4697, Train Steps/Sec: 1.13
437
+ [2025-10-28 10:06:39] (step=0037800) Train Loss: 0.4693, Train Steps/Sec: 1.13
438
+ [2025-10-28 10:08:07] (step=0037900) Train Loss: 0.4685, Train Steps/Sec: 1.13
439
+ [2025-10-28 10:09:35] (step=0038000) Train Loss: 0.4700, Train Steps/Sec: 1.13
440
+ [2025-10-28 10:11:03] (step=0038100) Train Loss: 0.4677, Train Steps/Sec: 1.13
441
+ [2025-10-28 10:12:32] (step=0038200) Train Loss: 0.4709, Train Steps/Sec: 1.13
442
+ [2025-10-28 10:14:00] (step=0038300) Train Loss: 0.4698, Train Steps/Sec: 1.13
443
+ [2025-10-28 10:15:28] (step=0038400) Train Loss: 0.4704, Train Steps/Sec: 1.13
444
+ [2025-10-28 10:16:57] (step=0038500) Train Loss: 0.4676, Train Steps/Sec: 1.13
445
+ [2025-10-28 10:18:25] (step=0038600) Train Loss: 0.4697, Train Steps/Sec: 1.13
446
+ [2025-10-28 10:19:53] (step=0038700) Train Loss: 0.4693, Train Steps/Sec: 1.13
447
+ [2025-10-28 10:21:05] Beginning epoch 31...
448
+ [2025-10-28 10:21:24] (step=0038800) Train Loss: 0.4693, Train Steps/Sec: 1.10
449
+ [2025-10-28 10:22:52] (step=0038900) Train Loss: 0.4702, Train Steps/Sec: 1.13
450
+ [2025-10-28 10:24:20] (step=0039000) Train Loss: 0.4667, Train Steps/Sec: 1.14
451
+ [2025-10-28 10:25:49] (step=0039100) Train Loss: 0.4678, Train Steps/Sec: 1.13
452
+ [2025-10-28 10:27:17] (step=0039200) Train Loss: 0.4694, Train Steps/Sec: 1.13
453
+ [2025-10-28 10:28:45] (step=0039300) Train Loss: 0.4691, Train Steps/Sec: 1.14
454
+ [2025-10-28 10:30:13] (step=0039400) Train Loss: 0.4694, Train Steps/Sec: 1.13
455
+ [2025-10-28 10:31:42] (step=0039500) Train Loss: 0.4685, Train Steps/Sec: 1.13
456
+ [2025-10-28 10:33:10] (step=0039600) Train Loss: 0.4685, Train Steps/Sec: 1.13
457
+ [2025-10-28 10:34:38] (step=0039700) Train Loss: 0.4659, Train Steps/Sec: 1.13
458
+ [2025-10-28 10:36:06] (step=0039800) Train Loss: 0.4689, Train Steps/Sec: 1.13
459
+ [2025-10-28 10:37:34] (step=0039900) Train Loss: 0.4696, Train Steps/Sec: 1.13
460
+ [2025-10-28 10:39:03] (step=0040000) Train Loss: 0.4659, Train Steps/Sec: 1.13
461
+ [2025-10-28 10:39:31] Beginning epoch 32...
462
+ [2025-10-28 10:40:34] (step=0040100) Train Loss: 0.4684, Train Steps/Sec: 1.09
463
+ [2025-10-28 10:42:03] (step=0040200) Train Loss: 0.4691, Train Steps/Sec: 1.13
464
+ [2025-10-28 10:43:31] (step=0040300) Train Loss: 0.4665, Train Steps/Sec: 1.13
465
+ [2025-10-28 10:44:59] (step=0040400) Train Loss: 0.4685, Train Steps/Sec: 1.13
466
+ [2025-10-28 10:46:27] (step=0040500) Train Loss: 0.4689, Train Steps/Sec: 1.13
467
+ [2025-10-28 10:47:55] (step=0040600) Train Loss: 0.4682, Train Steps/Sec: 1.13
468
+ [2025-10-28 10:49:24] (step=0040700) Train Loss: 0.4689, Train Steps/Sec: 1.13
469
+ [2025-10-28 10:50:52] (step=0040800) Train Loss: 0.4675, Train Steps/Sec: 1.13
470
+ [2025-10-28 10:52:20] (step=0040900) Train Loss: 0.4691, Train Steps/Sec: 1.13
471
+ [2025-10-28 10:53:49] (step=0041000) Train Loss: 0.4688, Train Steps/Sec: 1.13
472
+ [2025-10-28 10:55:17] (step=0041100) Train Loss: 0.4679, Train Steps/Sec: 1.13
473
+ [2025-10-28 10:56:45] (step=0041200) Train Loss: 0.4678, Train Steps/Sec: 1.13
474
+ [2025-10-28 10:57:59] Beginning epoch 33...
475
+ [2025-10-28 10:58:16] (step=0041300) Train Loss: 0.4679, Train Steps/Sec: 1.10
476
+ [2025-10-28 10:59:44] (step=0041400) Train Loss: 0.4690, Train Steps/Sec: 1.13
477
+ [2025-10-28 11:01:12] (step=0041500) Train Loss: 0.4683, Train Steps/Sec: 1.13
478
+ [2025-10-28 11:02:40] (step=0041600) Train Loss: 0.4696, Train Steps/Sec: 1.13
479
+ [2025-10-28 11:04:09] (step=0041700) Train Loss: 0.4676, Train Steps/Sec: 1.12
480
+ [2025-10-28 11:05:38] (step=0041800) Train Loss: 0.4676, Train Steps/Sec: 1.13
481
+ [2025-10-28 11:07:06] (step=0041900) Train Loss: 0.4690, Train Steps/Sec: 1.14
482
+ [2025-10-28 11:08:34] (step=0042000) Train Loss: 0.4684, Train Steps/Sec: 1.14
483
+ [2025-10-28 11:10:02] (step=0042100) Train Loss: 0.4692, Train Steps/Sec: 1.13
484
+ [2025-10-28 11:11:30] (step=0042200) Train Loss: 0.4667, Train Steps/Sec: 1.13
485
+ [2025-10-28 11:12:58] (step=0042300) Train Loss: 0.4680, Train Steps/Sec: 1.13
486
+ [2025-10-28 11:14:26] (step=0042400) Train Loss: 0.4676, Train Steps/Sec: 1.13
487
+ [2025-10-28 11:15:55] (step=0042500) Train Loss: 0.4660, Train Steps/Sec: 1.13
488
+ [2025-10-28 11:16:25] Beginning epoch 34...
489
+ [2025-10-28 11:17:26] (step=0042600) Train Loss: 0.4667, Train Steps/Sec: 1.10
490
+ [2025-10-28 11:18:54] (step=0042700) Train Loss: 0.4677, Train Steps/Sec: 1.13
491
+ [2025-10-28 11:20:22] (step=0042800) Train Loss: 0.4670, Train Steps/Sec: 1.13
492
+ [2025-10-28 11:21:50] (step=0042900) Train Loss: 0.4671, Train Steps/Sec: 1.13
493
+ [2025-10-28 11:23:19] (step=0043000) Train Loss: 0.4662, Train Steps/Sec: 1.13
494
+ [2025-10-28 11:24:47] (step=0043100) Train Loss: 0.4677, Train Steps/Sec: 1.13
495
+ [2025-10-28 11:26:15] (step=0043200) Train Loss: 0.4649, Train Steps/Sec: 1.13
496
+ [2025-10-28 11:27:43] (step=0043300) Train Loss: 0.4659, Train Steps/Sec: 1.13
497
+ [2025-10-28 11:29:12] (step=0043400) Train Loss: 0.4673, Train Steps/Sec: 1.13
498
+ [2025-10-28 11:30:40] (step=0043500) Train Loss: 0.4678, Train Steps/Sec: 1.13
499
+ [2025-10-28 11:32:08] (step=0043600) Train Loss: 0.4687, Train Steps/Sec: 1.13
500
+ [2025-10-28 11:33:37] (step=0043700) Train Loss: 0.4673, Train Steps/Sec: 1.13
501
+ [2025-10-28 11:34:52] Beginning epoch 35...
502
+ [2025-10-28 11:35:08] (step=0043800) Train Loss: 0.4684, Train Steps/Sec: 1.10
503
+ [2025-10-28 11:36:36] (step=0043900) Train Loss: 0.4668, Train Steps/Sec: 1.13
504
+ [2025-10-28 11:38:04] (step=0044000) Train Loss: 0.4678, Train Steps/Sec: 1.13
505
+ [2025-10-28 11:39:32] (step=0044100) Train Loss: 0.4681, Train Steps/Sec: 1.13
506
+ [2025-10-28 11:41:01] (step=0044200) Train Loss: 0.4659, Train Steps/Sec: 1.13
507
+ [2025-10-28 11:42:29] (step=0044300) Train Loss: 0.4655, Train Steps/Sec: 1.13
508
+ [2025-10-28 11:43:57] (step=0044400) Train Loss: 0.4658, Train Steps/Sec: 1.13
509
+ [2025-10-28 11:45:26] (step=0044500) Train Loss: 0.4658, Train Steps/Sec: 1.13
510
+ [2025-10-28 11:46:54] (step=0044600) Train Loss: 0.4656, Train Steps/Sec: 1.13
511
+ [2025-10-28 11:48:22] (step=0044700) Train Loss: 0.4660, Train Steps/Sec: 1.13
512
+ [2025-10-28 11:49:50] (step=0044800) Train Loss: 0.4661, Train Steps/Sec: 1.14
513
+ [2025-10-28 11:51:18] (step=0044900) Train Loss: 0.4656, Train Steps/Sec: 1.13
514
+ [2025-10-28 11:52:46] (step=0045000) Train Loss: 0.4661, Train Steps/Sec: 1.13
515
+ [2025-10-28 11:53:19] Beginning epoch 36...
516
+ [2025-10-28 11:54:18] (step=0045100) Train Loss: 0.4675, Train Steps/Sec: 1.09
517
+ [2025-10-28 11:55:46] (step=0045200) Train Loss: 0.4650, Train Steps/Sec: 1.13
518
+ [2025-10-28 11:57:14] (step=0045300) Train Loss: 0.4645, Train Steps/Sec: 1.13
519
+ [2025-10-28 11:58:42] (step=0045400) Train Loss: 0.4669, Train Steps/Sec: 1.13
520
+ [2025-10-28 12:00:10] (step=0045500) Train Loss: 0.4678, Train Steps/Sec: 1.13
521
+ [2025-10-28 12:01:39] (step=0045600) Train Loss: 0.4647, Train Steps/Sec: 1.13
522
+ [2025-10-28 12:03:07] (step=0045700) Train Loss: 0.4654, Train Steps/Sec: 1.13
523
+ [2025-10-28 12:04:35] (step=0045800) Train Loss: 0.4662, Train Steps/Sec: 1.13
524
+ [2025-10-28 12:06:04] (step=0045900) Train Loss: 0.4666, Train Steps/Sec: 1.13
525
+ [2025-10-28 12:07:32] (step=0046000) Train Loss: 0.4653, Train Steps/Sec: 1.13
526
+ [2025-10-28 12:09:00] (step=0046100) Train Loss: 0.4652, Train Steps/Sec: 1.13
527
+ [2025-10-28 12:10:28] (step=0046200) Train Loss: 0.4653, Train Steps/Sec: 1.13
528
+ [2025-10-28 12:11:45] Beginning epoch 37...
529
+ [2025-10-28 12:11:59] (step=0046300) Train Loss: 0.4647, Train Steps/Sec: 1.10
530
+ [2025-10-28 12:13:28] (step=0046400) Train Loss: 0.4658, Train Steps/Sec: 1.13
531
+ [2025-10-28 12:14:56] (step=0046500) Train Loss: 0.4660, Train Steps/Sec: 1.13
532
+ [2025-10-28 12:16:24] (step=0046600) Train Loss: 0.4658, Train Steps/Sec: 1.13
533
+ [2025-10-28 12:17:52] (step=0046700) Train Loss: 0.4654, Train Steps/Sec: 1.13
534
+ [2025-10-28 12:19:21] (step=0046800) Train Loss: 0.4670, Train Steps/Sec: 1.13
535
+ [2025-10-28 12:20:49] (step=0046900) Train Loss: 0.4659, Train Steps/Sec: 1.13
536
+ [2025-10-28 12:22:17] (step=0047000) Train Loss: 0.4653, Train Steps/Sec: 1.13
537
+ [2025-10-28 12:23:45] (step=0047100) Train Loss: 0.4648, Train Steps/Sec: 1.14
538
+ [2025-10-28 12:25:13] (step=0047200) Train Loss: 0.4640, Train Steps/Sec: 1.13
539
+ [2025-10-28 12:26:42] (step=0047300) Train Loss: 0.4656, Train Steps/Sec: 1.14
540
+ [2025-10-28 12:28:10] (step=0047400) Train Loss: 0.4640, Train Steps/Sec: 1.13
541
+ [2025-10-28 12:29:38] (step=0047500) Train Loss: 0.4624, Train Steps/Sec: 1.13
542
+ [2025-10-28 12:30:12] Beginning epoch 38...
543
+ [2025-10-28 12:31:10] (step=0047600) Train Loss: 0.4665, Train Steps/Sec: 1.09
544
+ [2025-10-28 12:32:38] (step=0047700) Train Loss: 0.4657, Train Steps/Sec: 1.13
545
+ [2025-10-28 12:34:06] (step=0047800) Train Loss: 0.4648, Train Steps/Sec: 1.13
546
+ [2025-10-28 12:35:34] (step=0047900) Train Loss: 0.4655, Train Steps/Sec: 1.13
547
+ [2025-10-28 12:37:03] (step=0048000) Train Loss: 0.4644, Train Steps/Sec: 1.13
548
+ [2025-10-28 12:38:31] (step=0048100) Train Loss: 0.4664, Train Steps/Sec: 1.13
549
+ [2025-10-28 12:39:59] (step=0048200) Train Loss: 0.4648, Train Steps/Sec: 1.13
550
+ [2025-10-28 12:41:27] (step=0048300) Train Loss: 0.4657, Train Steps/Sec: 1.13
551
+ [2025-10-28 12:42:55] (step=0048400) Train Loss: 0.4653, Train Steps/Sec: 1.13
552
+ [2025-10-28 12:44:24] (step=0048500) Train Loss: 0.4664, Train Steps/Sec: 1.13
553
+ [2025-10-28 12:45:52] (step=0048600) Train Loss: 0.4650, Train Steps/Sec: 1.13
554
+ [2025-10-28 12:47:20] (step=0048700) Train Loss: 0.4664, Train Steps/Sec: 1.13
555
+ [2025-10-28 12:48:39] Beginning epoch 39...
556
+ [2025-10-28 12:48:51] (step=0048800) Train Loss: 0.4651, Train Steps/Sec: 1.10
557
+ [2025-10-28 12:50:20] (step=0048900) Train Loss: 0.4646, Train Steps/Sec: 1.13
558
+ [2025-10-28 12:51:48] (step=0049000) Train Loss: 0.4632, Train Steps/Sec: 1.13
559
+ [2025-10-28 12:53:16] (step=0049100) Train Loss: 0.4649, Train Steps/Sec: 1.13
560
+ [2025-10-28 12:54:44] (step=0049200) Train Loss: 0.4661, Train Steps/Sec: 1.13
561
+ [2025-10-28 12:56:13] (step=0049300) Train Loss: 0.4644, Train Steps/Sec: 1.13
562
+ [2025-10-28 12:57:41] (step=0049400) Train Loss: 0.4653, Train Steps/Sec: 1.13
563
+ [2025-10-28 12:59:10] (step=0049500) Train Loss: 0.4644, Train Steps/Sec: 1.13
564
+ [2025-10-28 13:00:38] (step=0049600) Train Loss: 0.4645, Train Steps/Sec: 1.13
565
+ [2025-10-28 13:02:06] (step=0049700) Train Loss: 0.4649, Train Steps/Sec: 1.13
566
+ [2025-10-28 13:03:34] (step=0049800) Train Loss: 0.4648, Train Steps/Sec: 1.13
567
+ [2025-10-28 13:05:02] (step=0049900) Train Loss: 0.4651, Train Steps/Sec: 1.13
568
+ [2025-10-28 13:06:30] (step=0050000) Train Loss: 0.4640, Train Steps/Sec: 1.13
569
+ [2025-10-28 13:07:23] Saved checkpoint to results/stage2/hfdata/lightningdit-xl-spatialpe-vit-l-bf16/checkpoints/0050000.pt
570
+ [2025-10-28 13:07:23] Generating EMA samples...
571
+ [2025-10-28 13:07:51] Generating EMA samples done.
572
+ [2025-10-28 13:08:26] Beginning epoch 40...
573
+ [2025-10-28 13:09:22] (step=0050100) Train Loss: 0.4652, Train Steps/Sec: 0.58
574
+ [2025-10-28 13:10:50] (step=0050200) Train Loss: 0.4648, Train Steps/Sec: 1.12
575
+ [2025-10-28 13:12:19] (step=0050300) Train Loss: 0.4645, Train Steps/Sec: 1.13
576
+ [2025-10-28 13:13:47] (step=0050400) Train Loss: 0.4641, Train Steps/Sec: 1.13
577
+ [2025-10-28 13:15:15] (step=0050500) Train Loss: 0.4643, Train Steps/Sec: 1.13
578
+ [2025-10-28 13:16:43] (step=0050600) Train Loss: 0.4649, Train Steps/Sec: 1.13
579
+ [2025-10-28 13:18:11] (step=0050700) Train Loss: 0.4638, Train Steps/Sec: 1.13
580
+ [2025-10-28 13:19:40] (step=0050800) Train Loss: 0.4635, Train Steps/Sec: 1.13
581
+ [2025-10-28 13:21:08] (step=0050900) Train Loss: 0.4622, Train Steps/Sec: 1.13
582
+ [2025-10-28 13:22:36] (step=0051000) Train Loss: 0.4641, Train Steps/Sec: 1.13
583
+ [2025-10-28 13:24:05] (step=0051100) Train Loss: 0.4645, Train Steps/Sec: 1.13
584
+ [2025-10-28 13:25:33] (step=0051200) Train Loss: 0.4648, Train Steps/Sec: 1.13
585
+ [2025-10-28 13:26:54] Beginning epoch 41...
586
+ [2025-10-28 13:27:04] (step=0051300) Train Loss: 0.4659, Train Steps/Sec: 1.10
587
+ [2025-10-28 13:28:32] (step=0051400) Train Loss: 0.4652, Train Steps/Sec: 1.13
588
+ [2025-10-28 13:30:00] (step=0051500) Train Loss: 0.4634, Train Steps/Sec: 1.13
589
+ [2025-10-28 13:31:29] (step=0051600) Train Loss: 0.4627, Train Steps/Sec: 1.13
590
+ [2025-10-28 13:32:57] (step=0051700) Train Loss: 0.4642, Train Steps/Sec: 1.13
591
+ [2025-10-28 13:34:25] (step=0051800) Train Loss: 0.4652, Train Steps/Sec: 1.13
592
+ [2025-10-28 13:35:54] (step=0051900) Train Loss: 0.4650, Train Steps/Sec: 1.13
593
+ [2025-10-28 13:37:22] (step=0052000) Train Loss: 0.4644, Train Steps/Sec: 1.13
594
+ [2025-10-28 13:38:50] (step=0052100) Train Loss: 0.4627, Train Steps/Sec: 1.13
595
+ [2025-10-28 13:40:18] (step=0052200) Train Loss: 0.4643, Train Steps/Sec: 1.14
596
+ [2025-10-28 13:41:46] (step=0052300) Train Loss: 0.4647, Train Steps/Sec: 1.14
597
+ [2025-10-28 13:43:15] (step=0052400) Train Loss: 0.4631, Train Steps/Sec: 1.13
598
+ [2025-10-28 13:44:43] (step=0052500) Train Loss: 0.4648, Train Steps/Sec: 1.13
599
+ [2025-10-28 13:45:20] Beginning epoch 42...
600
+ [2025-10-28 13:46:14] (step=0052600) Train Loss: 0.4636, Train Steps/Sec: 1.10
601
+ [2025-10-28 13:47:43] (step=0052700) Train Loss: 0.4638, Train Steps/Sec: 1.13
602
+ [2025-10-28 13:49:11] (step=0052800) Train Loss: 0.4655, Train Steps/Sec: 1.13
603
+ [2025-10-28 13:50:39] (step=0052900) Train Loss: 0.4617, Train Steps/Sec: 1.13
604
+ [2025-10-28 13:52:07] (step=0053000) Train Loss: 0.4628, Train Steps/Sec: 1.13
605
+ [2025-10-28 13:53:35] (step=0053100) Train Loss: 0.4627, Train Steps/Sec: 1.14
606
+ [2025-10-28 13:55:03] (step=0053200) Train Loss: 0.4645, Train Steps/Sec: 1.13
607
+ [2025-10-28 13:56:32] (step=0053300) Train Loss: 0.4622, Train Steps/Sec: 1.13
608
+ [2025-10-28 13:58:00] (step=0053400) Train Loss: 0.4623, Train Steps/Sec: 1.13
609
+ [2025-10-28 13:59:28] (step=0053500) Train Loss: 0.4634, Train Steps/Sec: 1.13
610
+ [2025-10-28 14:00:57] (step=0053600) Train Loss: 0.4634, Train Steps/Sec: 1.13
611
+ [2025-10-28 14:02:25] (step=0053700) Train Loss: 0.4645, Train Steps/Sec: 1.13
612
+ [2025-10-28 14:03:47] Beginning epoch 43...
613
+ [2025-10-28 14:03:56] (step=0053800) Train Loss: 0.4626, Train Steps/Sec: 1.10
614
+ [2025-10-28 14:05:24] (step=0053900) Train Loss: 0.4637, Train Steps/Sec: 1.13
615
+ [2025-10-28 14:06:52] (step=0054000) Train Loss: 0.4647, Train Steps/Sec: 1.13
616
+ [2025-10-28 14:08:20] (step=0054100) Train Loss: 0.4641, Train Steps/Sec: 1.13
617
+ [2025-10-28 14:09:48] (step=0054200) Train Loss: 0.4619, Train Steps/Sec: 1.13
618
+ [2025-10-28 14:11:16] (step=0054300) Train Loss: 0.4640, Train Steps/Sec: 1.13
619
+ [2025-10-28 14:12:45] (step=0054400) Train Loss: 0.4649, Train Steps/Sec: 1.13
620
+ [2025-10-28 14:14:13] (step=0054500) Train Loss: 0.4625, Train Steps/Sec: 1.13
621
+ [2025-10-28 14:15:41] (step=0054600) Train Loss: 0.4630, Train Steps/Sec: 1.13
622
+ [2025-10-28 14:17:10] (step=0054700) Train Loss: 0.4634, Train Steps/Sec: 1.14
623
+ [2025-10-28 14:18:38] (step=0054800) Train Loss: 0.4634, Train Steps/Sec: 1.13
624
+ [2025-10-28 14:20:06] (step=0054900) Train Loss: 0.4621, Train Steps/Sec: 1.13
625
+ [2025-10-28 14:21:34] (step=0055000) Train Loss: 0.4619, Train Steps/Sec: 1.13
626
+ [2025-10-28 14:22:13] Beginning epoch 44...
627
+ [2025-10-28 14:23:05] (step=0055100) Train Loss: 0.4630, Train Steps/Sec: 1.10
628
+ [2025-10-28 14:24:33] (step=0055200) Train Loss: 0.4632, Train Steps/Sec: 1.13
629
+ [2025-10-28 14:26:02] (step=0055300) Train Loss: 0.4628, Train Steps/Sec: 1.13
630
+ [2025-10-28 14:27:30] (step=0055400) Train Loss: 0.4638, Train Steps/Sec: 1.14
631
+ [2025-10-28 14:28:58] (step=0055500) Train Loss: 0.4634, Train Steps/Sec: 1.14
632
+ [2025-10-28 14:30:27] (step=0055600) Train Loss: 0.4634, Train Steps/Sec: 1.13
633
+ [2025-10-28 14:31:55] (step=0055700) Train Loss: 0.4627, Train Steps/Sec: 1.13
634
+ [2025-10-28 14:33:23] (step=0055800) Train Loss: 0.4612, Train Steps/Sec: 1.13
635
+ [2025-10-28 14:34:51] (step=0055900) Train Loss: 0.4625, Train Steps/Sec: 1.13
636
+ [2025-10-28 14:36:19] (step=0056000) Train Loss: 0.4638, Train Steps/Sec: 1.13
637
+ [2025-10-28 14:37:48] (step=0056100) Train Loss: 0.4617, Train Steps/Sec: 1.13
638
+ [2025-10-28 14:39:16] (step=0056200) Train Loss: 0.4618, Train Steps/Sec: 1.13
639
+ [2025-10-28 14:40:40] Beginning epoch 45...
640
+ [2025-10-28 14:40:47] (step=0056300) Train Loss: 0.4637, Train Steps/Sec: 1.10
641
+ [2025-10-28 14:42:15] (step=0056400) Train Loss: 0.4615, Train Steps/Sec: 1.13
642
+ [2025-10-28 14:43:44] (step=0056500) Train Loss: 0.4612, Train Steps/Sec: 1.13
643
+ [2025-10-28 14:45:12] (step=0056600) Train Loss: 0.4633, Train Steps/Sec: 1.13
644
+ [2025-10-28 14:46:40] (step=0056700) Train Loss: 0.4623, Train Steps/Sec: 1.13
645
+ [2025-10-28 14:48:08] (step=0056800) Train Loss: 0.4614, Train Steps/Sec: 1.13
646
+ [2025-10-28 14:49:36] (step=0056900) Train Loss: 0.4643, Train Steps/Sec: 1.13
647
+ [2025-10-28 14:51:05] (step=0057000) Train Loss: 0.4635, Train Steps/Sec: 1.13
648
+ [2025-10-28 14:52:33] (step=0057100) Train Loss: 0.4629, Train Steps/Sec: 1.13
649
+ [2025-10-28 14:54:02] (step=0057200) Train Loss: 0.4626, Train Steps/Sec: 1.13
650
+ [2025-10-28 14:55:30] (step=0057300) Train Loss: 0.4604, Train Steps/Sec: 1.14
651
+ [2025-10-28 14:56:58] (step=0057400) Train Loss: 0.4610, Train Steps/Sec: 1.13
652
+ [2025-10-28 14:58:26] (step=0057500) Train Loss: 0.4629, Train Steps/Sec: 1.14
653
+ [2025-10-28 14:59:07] Beginning epoch 46...
654
+ [2025-10-28 14:59:57] (step=0057600) Train Loss: 0.4623, Train Steps/Sec: 1.10
655
+ [2025-10-28 15:01:25] (step=0057700) Train Loss: 0.4606, Train Steps/Sec: 1.14
656
+ [2025-10-28 15:02:54] (step=0057800) Train Loss: 0.4624, Train Steps/Sec: 1.13
657
+ [2025-10-28 15:04:22] (step=0057900) Train Loss: 0.4641, Train Steps/Sec: 1.13
658
+ [2025-10-28 15:05:50] (step=0058000) Train Loss: 0.4632, Train Steps/Sec: 1.13
659
+ [2025-10-28 15:07:18] (step=0058100) Train Loss: 0.4620, Train Steps/Sec: 1.14
660
+ [2025-10-28 15:08:46] (step=0058200) Train Loss: 0.4619, Train Steps/Sec: 1.13
661
+ [2025-10-28 15:10:15] (step=0058300) Train Loss: 0.4605, Train Steps/Sec: 1.13
662
+ [2025-10-28 15:11:43] (step=0058400) Train Loss: 0.4591, Train Steps/Sec: 1.13
663
+ [2025-10-28 15:13:11] (step=0058500) Train Loss: 0.4624, Train Steps/Sec: 1.13
664
+ [2025-10-28 15:14:39] (step=0058600) Train Loss: 0.4620, Train Steps/Sec: 1.13
665
+ [2025-10-28 15:16:08] (step=0058700) Train Loss: 0.4613, Train Steps/Sec: 1.13
666
+ [2025-10-28 15:17:34] Beginning epoch 47...
667
+ [2025-10-28 15:17:39] (step=0058800) Train Loss: 0.4618, Train Steps/Sec: 1.10
668
+ [2025-10-28 15:19:07] (step=0058900) Train Loss: 0.4602, Train Steps/Sec: 1.13
669
+ [2025-10-28 15:20:35] (step=0059000) Train Loss: 0.4606, Train Steps/Sec: 1.13
670
+ [2025-10-28 15:22:03] (step=0059100) Train Loss: 0.4603, Train Steps/Sec: 1.13
671
+ [2025-10-28 15:23:31] (step=0059200) Train Loss: 0.4607, Train Steps/Sec: 1.13
672
+ [2025-10-28 15:25:00] (step=0059300) Train Loss: 0.4629, Train Steps/Sec: 1.13
673
+ [2025-10-28 15:26:28] (step=0059400) Train Loss: 0.4634, Train Steps/Sec: 1.13
674
+ [2025-10-28 15:27:57] (step=0059500) Train Loss: 0.4610, Train Steps/Sec: 1.12
675
+ [2025-10-28 15:29:25] (step=0059600) Train Loss: 0.4618, Train Steps/Sec: 1.13
676
+ [2025-10-28 15:30:53] (step=0059700) Train Loss: 0.4614, Train Steps/Sec: 1.13
677
+ [2025-10-28 15:32:22] (step=0059800) Train Loss: 0.4618, Train Steps/Sec: 1.13
678
+ [2025-10-28 15:33:50] (step=0059900) Train Loss: 0.4624, Train Steps/Sec: 1.13
679
+ [2025-10-28 15:35:18] (step=0060000) Train Loss: 0.4615, Train Steps/Sec: 1.13
680
+ [2025-10-28 15:36:01] Beginning epoch 48...
681
+ [2025-10-28 15:36:49] (step=0060100) Train Loss: 0.4629, Train Steps/Sec: 1.09
682
+ [2025-10-28 15:38:18] (step=0060200) Train Loss: 0.4622, Train Steps/Sec: 1.13
683
+ [2025-10-28 15:39:46] (step=0060300) Train Loss: 0.4617, Train Steps/Sec: 1.13
684
+ [2025-10-28 15:41:15] (step=0060400) Train Loss: 0.4610, Train Steps/Sec: 1.13
685
+ [2025-10-28 15:42:43] (step=0060500) Train Loss: 0.4608, Train Steps/Sec: 1.13
686
+ [2025-10-28 15:44:11] (step=0060600) Train Loss: 0.4628, Train Steps/Sec: 1.13
687
+ [2025-10-28 15:45:39] (step=0060700) Train Loss: 0.4605, Train Steps/Sec: 1.13
688
+ [2025-10-28 15:47:07] (step=0060800) Train Loss: 0.4612, Train Steps/Sec: 1.13
689
+ [2025-10-28 15:48:35] (step=0060900) Train Loss: 0.4600, Train Steps/Sec: 1.13
690
+ [2025-10-28 15:50:04] (step=0061000) Train Loss: 0.4614, Train Steps/Sec: 1.13
691
+ [2025-10-28 15:51:32] (step=0061100) Train Loss: 0.4598, Train Steps/Sec: 1.13
692
+ [2025-10-28 15:53:00] (step=0061200) Train Loss: 0.4612, Train Steps/Sec: 1.13
693
+ [2025-10-28 15:54:28] Beginning epoch 49...
694
+ [2025-10-28 15:54:31] (step=0061300) Train Loss: 0.4616, Train Steps/Sec: 1.10
695
+ [2025-10-28 15:56:00] (step=0061400) Train Loss: 0.4607, Train Steps/Sec: 1.13
696
+ [2025-10-28 15:57:28] (step=0061500) Train Loss: 0.4601, Train Steps/Sec: 1.13
697
+ [2025-10-28 15:58:56] (step=0061600) Train Loss: 0.4615, Train Steps/Sec: 1.13
698
+ [2025-10-28 16:00:24] (step=0061700) Train Loss: 0.4602, Train Steps/Sec: 1.13
699
+ [2025-10-28 16:01:53] (step=0061800) Train Loss: 0.4606, Train Steps/Sec: 1.13
700
+ [2025-10-28 16:03:21] (step=0061900) Train Loss: 0.4600, Train Steps/Sec: 1.13
701
+ [2025-10-28 16:04:49] (step=0062000) Train Loss: 0.4612, Train Steps/Sec: 1.13
702
+ [2025-10-28 16:06:18] (step=0062100) Train Loss: 0.4615, Train Steps/Sec: 1.13
703
+ [2025-10-28 16:07:46] (step=0062200) Train Loss: 0.4603, Train Steps/Sec: 1.13
704
+ [2025-10-28 16:09:14] (step=0062300) Train Loss: 0.4627, Train Steps/Sec: 1.13
705
+ [2025-10-28 16:10:42] (step=0062400) Train Loss: 0.4610, Train Steps/Sec: 1.13
706
+ [2025-10-28 16:12:11] (step=0062500) Train Loss: 0.4601, Train Steps/Sec: 1.13
707
+ [2025-10-28 16:12:55] Beginning epoch 50...
708
+ [2025-10-28 16:13:42] (step=0062600) Train Loss: 0.4608, Train Steps/Sec: 1.10
709
+ [2025-10-28 16:15:10] (step=0062700) Train Loss: 0.4609, Train Steps/Sec: 1.13
710
+ [2025-10-28 16:16:38] (step=0062800) Train Loss: 0.4613, Train Steps/Sec: 1.13
711
+ [2025-10-28 16:18:07] (step=0062900) Train Loss: 0.4602, Train Steps/Sec: 1.13
712
+ [2025-10-28 16:19:35] (step=0063000) Train Loss: 0.4603, Train Steps/Sec: 1.13
713
+ [2025-10-28 16:21:03] (step=0063100) Train Loss: 0.4600, Train Steps/Sec: 1.13
714
+ [2025-10-28 16:22:31] (step=0063200) Train Loss: 0.4594, Train Steps/Sec: 1.13
715
+ [2025-10-28 16:24:00] (step=0063300) Train Loss: 0.4609, Train Steps/Sec: 1.13
716
+ [2025-10-28 16:25:28] (step=0063400) Train Loss: 0.4611, Train Steps/Sec: 1.13
717
+ [2025-10-28 16:26:56] (step=0063500) Train Loss: 0.4590, Train Steps/Sec: 1.13
718
+ [2025-10-28 16:28:24] (step=0063600) Train Loss: 0.4598, Train Steps/Sec: 1.13
719
+ [2025-10-28 16:29:53] (step=0063700) Train Loss: 0.4605, Train Steps/Sec: 1.13
720
+ [2025-10-28 16:31:21] (step=0063800) Train Loss: 0.4601, Train Steps/Sec: 1.13
721
+ [2025-10-28 16:31:23] Beginning epoch 51...
722
+ [2025-10-28 16:32:52] (step=0063900) Train Loss: 0.4581, Train Steps/Sec: 1.10
723
+ [2025-10-28 16:34:20] (step=0064000) Train Loss: 0.4610, Train Steps/Sec: 1.13
724
+ [2025-10-28 16:35:48] (step=0064100) Train Loss: 0.4602, Train Steps/Sec: 1.13
725
+ [2025-10-28 16:37:17] (step=0064200) Train Loss: 0.4610, Train Steps/Sec: 1.13
726
+ [2025-10-28 16:38:45] (step=0064300) Train Loss: 0.4611, Train Steps/Sec: 1.13
727
+ [2025-10-28 16:40:13] (step=0064400) Train Loss: 0.4589, Train Steps/Sec: 1.13
728
+ [2025-10-28 16:41:41] (step=0064500) Train Loss: 0.4595, Train Steps/Sec: 1.13
729
+ [2025-10-28 16:43:10] (step=0064600) Train Loss: 0.4608, Train Steps/Sec: 1.13
730
+ [2025-10-28 16:44:38] (step=0064700) Train Loss: 0.4600, Train Steps/Sec: 1.13
731
+ [2025-10-28 16:46:07] (step=0064800) Train Loss: 0.4605, Train Steps/Sec: 1.13
732
+ [2025-10-28 16:47:35] (step=0064900) Train Loss: 0.4609, Train Steps/Sec: 1.13
733
+ [2025-10-28 16:49:03] (step=0065000) Train Loss: 0.4608, Train Steps/Sec: 1.13
734
+ [2025-10-28 16:49:49] Beginning epoch 52...
735
+ [2025-10-28 16:50:34] (step=0065100) Train Loss: 0.4604, Train Steps/Sec: 1.10
736
+ [2025-10-28 16:52:02] (step=0065200) Train Loss: 0.4611, Train Steps/Sec: 1.13
737
+ [2025-10-28 16:53:30] (step=0065300) Train Loss: 0.4598, Train Steps/Sec: 1.13
738
+ [2025-10-28 16:54:58] (step=0065400) Train Loss: 0.4604, Train Steps/Sec: 1.13
739
+ [2025-10-28 16:56:27] (step=0065500) Train Loss: 0.4600, Train Steps/Sec: 1.12
740
+ [2025-10-28 16:57:55] (step=0065600) Train Loss: 0.4593, Train Steps/Sec: 1.13
741
+ [2025-10-28 16:59:24] (step=0065700) Train Loss: 0.4594, Train Steps/Sec: 1.13
742
+ [2025-10-28 17:00:52] (step=0065800) Train Loss: 0.4605, Train Steps/Sec: 1.13
743
+ [2025-10-28 17:02:20] (step=0065900) Train Loss: 0.4607, Train Steps/Sec: 1.13
744
+ [2025-10-28 17:03:48] (step=0066000) Train Loss: 0.4596, Train Steps/Sec: 1.13
745
+ [2025-10-28 17:05:16] (step=0066100) Train Loss: 0.4602, Train Steps/Sec: 1.13
746
+ [2025-10-28 17:06:44] (step=0066200) Train Loss: 0.4592, Train Steps/Sec: 1.13
747
+ [2025-10-28 17:08:13] (step=0066300) Train Loss: 0.4595, Train Steps/Sec: 1.13
748
+ [2025-10-28 17:08:16] Beginning epoch 53...
749
+ [2025-10-28 17:09:44] (step=0066400) Train Loss: 0.4612, Train Steps/Sec: 1.10
750
+ [2025-10-28 17:11:12] (step=0066500) Train Loss: 0.4590, Train Steps/Sec: 1.13
751
+ [2025-10-28 17:12:41] (step=0066600) Train Loss: 0.4604, Train Steps/Sec: 1.13
752
+ [2025-10-28 17:14:09] (step=0066700) Train Loss: 0.4587, Train Steps/Sec: 1.13
753
+ [2025-10-28 17:15:37] (step=0066800) Train Loss: 0.4596, Train Steps/Sec: 1.13
754
+ [2025-10-28 17:17:05] (step=0066900) Train Loss: 0.4596, Train Steps/Sec: 1.13
755
+ [2025-10-28 17:18:33] (step=0067000) Train Loss: 0.4594, Train Steps/Sec: 1.13
756
+ [2025-10-28 17:20:01] (step=0067100) Train Loss: 0.4606, Train Steps/Sec: 1.13
757
+ [2025-10-28 17:21:30] (step=0067200) Train Loss: 0.4588, Train Steps/Sec: 1.13
758
+ [2025-10-28 17:22:58] (step=0067300) Train Loss: 0.4618, Train Steps/Sec: 1.13
759
+ [2025-10-28 17:24:26] (step=0067400) Train Loss: 0.4592, Train Steps/Sec: 1.13
760
+ [2025-10-28 17:25:55] (step=0067500) Train Loss: 0.4596, Train Steps/Sec: 1.13
761
+ [2025-10-28 17:26:43] Beginning epoch 54...
762
+ [2025-10-28 17:27:26] (step=0067600) Train Loss: 0.4593, Train Steps/Sec: 1.10
763
+ [2025-10-28 17:28:54] (step=0067700) Train Loss: 0.4606, Train Steps/Sec: 1.13
764
+ [2025-10-28 17:30:22] (step=0067800) Train Loss: 0.4585, Train Steps/Sec: 1.13
765
+ [2025-10-28 17:31:50] (step=0067900) Train Loss: 0.4589, Train Steps/Sec: 1.13
766
+ [2025-10-28 17:33:19] (step=0068000) Train Loss: 0.4585, Train Steps/Sec: 1.13
767
+ [2025-10-28 17:34:47] (step=0068100) Train Loss: 0.4606, Train Steps/Sec: 1.13
768
+ [2025-10-28 17:36:16] (step=0068200) Train Loss: 0.4592, Train Steps/Sec: 1.13
769
+ [2025-10-28 17:37:44] (step=0068300) Train Loss: 0.4589, Train Steps/Sec: 1.13
770
+ [2025-10-28 17:39:12] (step=0068400) Train Loss: 0.4600, Train Steps/Sec: 1.13
771
+ [2025-10-28 17:40:40] (step=0068500) Train Loss: 0.4596, Train Steps/Sec: 1.13
772
+ [2025-10-28 17:42:08] (step=0068600) Train Loss: 0.4589, Train Steps/Sec: 1.13
773
+ [2025-10-28 17:43:36] (step=0068700) Train Loss: 0.4594, Train Steps/Sec: 1.13
774
+ [2025-10-28 17:45:05] (step=0068800) Train Loss: 0.4585, Train Steps/Sec: 1.13
775
+ [2025-10-28 17:45:09] Beginning epoch 55...
776
+ [2025-10-28 17:46:36] (step=0068900) Train Loss: 0.4588, Train Steps/Sec: 1.09
777
+ [2025-10-28 17:48:05] (step=0069000) Train Loss: 0.4587, Train Steps/Sec: 1.13
778
+ [2025-10-28 17:49:33] (step=0069100) Train Loss: 0.4583, Train Steps/Sec: 1.13
779
+ [2025-10-28 17:51:01] (step=0069200) Train Loss: 0.4609, Train Steps/Sec: 1.13
780
+ [2025-10-28 17:52:29] (step=0069300) Train Loss: 0.4611, Train Steps/Sec: 1.13
781
+ [2025-10-28 17:53:57] (step=0069400) Train Loss: 0.4584, Train Steps/Sec: 1.13
782
+ [2025-10-28 17:55:26] (step=0069500) Train Loss: 0.4599, Train Steps/Sec: 1.13
783
+ [2025-10-28 17:56:54] (step=0069600) Train Loss: 0.4575, Train Steps/Sec: 1.13
784
+ [2025-10-28 17:58:22] (step=0069700) Train Loss: 0.4601, Train Steps/Sec: 1.13
785
+ [2025-10-28 17:59:51] (step=0069800) Train Loss: 0.4588, Train Steps/Sec: 1.13
786
+ [2025-10-28 18:01:19] (step=0069900) Train Loss: 0.4590, Train Steps/Sec: 1.13
787
+ [2025-10-28 18:02:47] (step=0070000) Train Loss: 0.4584, Train Steps/Sec: 1.13
788
+ [2025-10-28 18:03:37] Beginning epoch 56...
789
+ [2025-10-28 18:04:18] (step=0070100) Train Loss: 0.4603, Train Steps/Sec: 1.10
790
+ [2025-10-28 18:05:46] (step=0070200) Train Loss: 0.4590, Train Steps/Sec: 1.13
791
+ [2025-10-28 18:07:14] (step=0070300) Train Loss: 0.4590, Train Steps/Sec: 1.13
792
+ [2025-10-28 18:08:42] (step=0070400) Train Loss: 0.4586, Train Steps/Sec: 1.13
793
+ [2025-10-28 18:10:11] (step=0070500) Train Loss: 0.4592, Train Steps/Sec: 1.13
794
+ [2025-10-28 18:11:39] (step=0070600) Train Loss: 0.4596, Train Steps/Sec: 1.13
795
+ [2025-10-28 18:13:08] (step=0070700) Train Loss: 0.4593, Train Steps/Sec: 1.13
796
+ [2025-10-28 18:14:36] (step=0070800) Train Loss: 0.4574, Train Steps/Sec: 1.13
797
+ [2025-10-28 18:16:04] (step=0070900) Train Loss: 0.4607, Train Steps/Sec: 1.13
798
+ [2025-10-28 18:17:32] (step=0071000) Train Loss: 0.4585, Train Steps/Sec: 1.13
799
+ [2025-10-28 18:19:00] (step=0071100) Train Loss: 0.4579, Train Steps/Sec: 1.13
800
+ [2025-10-28 18:20:28] (step=0071200) Train Loss: 0.4585, Train Steps/Sec: 1.13
801
+ [2025-10-28 18:21:57] (step=0071300) Train Loss: 0.4592, Train Steps/Sec: 1.13
802
+ [2025-10-28 18:22:03] Beginning epoch 57...
803
+ [2025-10-28 18:23:28] (step=0071400) Train Loss: 0.4600, Train Steps/Sec: 1.09
804
+ [2025-10-28 18:24:56] (step=0071500) Train Loss: 0.4580, Train Steps/Sec: 1.13
805
+ [2025-10-28 18:26:25] (step=0071600) Train Loss: 0.4579, Train Steps/Sec: 1.13
806
+ [2025-10-28 18:27:53] (step=0071700) Train Loss: 0.4599, Train Steps/Sec: 1.13
807
+ [2025-10-28 18:29:21] (step=0071800) Train Loss: 0.4589, Train Steps/Sec: 1.13
808
+ [2025-10-28 18:30:49] (step=0071900) Train Loss: 0.4571, Train Steps/Sec: 1.13
809
+ [2025-10-28 18:32:17] (step=0072000) Train Loss: 0.4582, Train Steps/Sec: 1.13
810
+ [2025-10-28 18:33:45] (step=0072100) Train Loss: 0.4599, Train Steps/Sec: 1.13
811
+ [2025-10-28 18:35:14] (step=0072200) Train Loss: 0.4581, Train Steps/Sec: 1.13
812
+ [2025-10-28 18:36:42] (step=0072300) Train Loss: 0.4581, Train Steps/Sec: 1.13
813
+ [2025-10-28 18:38:10] (step=0072400) Train Loss: 0.4564, Train Steps/Sec: 1.13
814
+ [2025-10-28 18:39:38] (step=0072500) Train Loss: 0.4573, Train Steps/Sec: 1.13
815
+ [2025-10-28 18:40:30] Beginning epoch 58...
816
+ [2025-10-28 18:41:10] (step=0072600) Train Loss: 0.4564, Train Steps/Sec: 1.10
817
+ [2025-10-28 18:42:38] (step=0072700) Train Loss: 0.4592, Train Steps/Sec: 1.13
818
+ [2025-10-28 18:44:06] (step=0072800) Train Loss: 0.4584, Train Steps/Sec: 1.13
819
+ [2025-10-28 18:45:34] (step=0072900) Train Loss: 0.4591, Train Steps/Sec: 1.14
820
+ [2025-10-28 18:47:02] (step=0073000) Train Loss: 0.4575, Train Steps/Sec: 1.14
821
+ [2025-10-28 18:48:31] (step=0073100) Train Loss: 0.4598, Train Steps/Sec: 1.13
822
+ [2025-10-28 18:49:59] (step=0073200) Train Loss: 0.4602, Train Steps/Sec: 1.13
823
+ [2025-10-28 18:51:27] (step=0073300) Train Loss: 0.4582, Train Steps/Sec: 1.14
824
+ [2025-10-28 18:52:55] (step=0073400) Train Loss: 0.4580, Train Steps/Sec: 1.13
825
+ [2025-10-28 18:54:24] (step=0073500) Train Loss: 0.4597, Train Steps/Sec: 1.13
826
+ [2025-10-28 18:55:52] (step=0073600) Train Loss: 0.4561, Train Steps/Sec: 1.13
827
+ [2025-10-28 18:57:20] (step=0073700) Train Loss: 0.4586, Train Steps/Sec: 1.13
828
+ [2025-10-28 18:58:48] (step=0073800) Train Loss: 0.4591, Train Steps/Sec: 1.13
829
+ [2025-10-28 18:58:56] Beginning epoch 59...
830
+ [2025-10-28 19:00:19] (step=0073900) Train Loss: 0.4580, Train Steps/Sec: 1.10
831
+ [2025-10-28 19:01:48] (step=0074000) Train Loss: 0.4572, Train Steps/Sec: 1.13
832
+ [2025-10-28 19:03:16] (step=0074100) Train Loss: 0.4582, Train Steps/Sec: 1.13
833
+ [2025-10-28 19:04:44] (step=0074200) Train Loss: 0.4587, Train Steps/Sec: 1.13
834
+ [2025-10-28 19:06:12] (step=0074300) Train Loss: 0.4582, Train Steps/Sec: 1.13
835
+ [2025-10-28 19:07:41] (step=0074400) Train Loss: 0.4573, Train Steps/Sec: 1.13
836
+ [2025-10-28 19:09:09] (step=0074500) Train Loss: 0.4578, Train Steps/Sec: 1.13
837
+ [2025-10-28 19:10:37] (step=0074600) Train Loss: 0.4592, Train Steps/Sec: 1.13
838
+ [2025-10-28 19:12:05] (step=0074700) Train Loss: 0.4574, Train Steps/Sec: 1.13
839
+ [2025-10-28 19:13:33] (step=0074800) Train Loss: 0.4583, Train Steps/Sec: 1.13
840
+ [2025-10-28 19:15:02] (step=0074900) Train Loss: 0.4585, Train Steps/Sec: 1.13
841
+ [2025-10-28 19:16:30] (step=0075000) Train Loss: 0.4558, Train Steps/Sec: 1.13
842
+ [2025-10-28 19:17:24] Saved checkpoint to results/stage2/hfdata/lightningdit-xl-spatialpe-vit-l-bf16/checkpoints/0075000.pt
843
+ [2025-10-28 19:17:24] Generating EMA samples...
844
+ [2025-10-28 19:17:52] Generating EMA samples done.
845
+ [2025-10-28 19:18:45] Beginning epoch 60...
846
+ [2025-10-28 19:19:23] (step=0075100) Train Loss: 0.4581, Train Steps/Sec: 0.58
847
+ [2025-10-28 19:20:51] (step=0075200) Train Loss: 0.4581, Train Steps/Sec: 1.14
848
+ [2025-10-28 19:22:19] (step=0075300) Train Loss: 0.4569, Train Steps/Sec: 1.13
849
+ [2025-10-28 19:23:47] (step=0075400) Train Loss: 0.4580, Train Steps/Sec: 1.13
850
+ [2025-10-28 19:25:15] (step=0075500) Train Loss: 0.4563, Train Steps/Sec: 1.13
851
+ [2025-10-28 19:26:43] (step=0075600) Train Loss: 0.4574, Train Steps/Sec: 1.13
852
+ [2025-10-28 19:28:12] (step=0075700) Train Loss: 0.4582, Train Steps/Sec: 1.13
853
+ [2025-10-28 19:29:40] (step=0075800) Train Loss: 0.4559, Train Steps/Sec: 1.13
854
+ [2025-10-28 19:31:08] (step=0075900) Train Loss: 0.4573, Train Steps/Sec: 1.13
855
+ [2025-10-28 19:32:37] (step=0076000) Train Loss: 0.4586, Train Steps/Sec: 1.13
856
+ [2025-10-28 19:34:05] (step=0076100) Train Loss: 0.4576, Train Steps/Sec: 1.13
857
+ [2025-10-28 19:35:33] (step=0076200) Train Loss: 0.4570, Train Steps/Sec: 1.13
858
+ [2025-10-28 19:37:01] (step=0076300) Train Loss: 0.4575, Train Steps/Sec: 1.13
859
+ [2025-10-28 19:37:11] Beginning epoch 61...
860
+ [2025-10-28 19:38:32] (step=0076400) Train Loss: 0.4573, Train Steps/Sec: 1.10
861
+ [2025-10-28 19:40:01] (step=0076500) Train Loss: 0.4558, Train Steps/Sec: 1.13
862
+ [2025-10-28 19:41:29] (step=0076600) Train Loss: 0.4564, Train Steps/Sec: 1.13
863
+ [2025-10-28 19:42:58] (step=0076700) Train Loss: 0.4584, Train Steps/Sec: 1.13
864
+ [2025-10-28 19:44:26] (step=0076800) Train Loss: 0.4560, Train Steps/Sec: 1.13
865
+ [2025-10-28 19:45:54] (step=0076900) Train Loss: 0.4579, Train Steps/Sec: 1.13
866
+ [2025-10-28 19:47:22] (step=0077000) Train Loss: 0.4559, Train Steps/Sec: 1.13
867
+ [2025-10-28 19:48:50] (step=0077100) Train Loss: 0.4584, Train Steps/Sec: 1.13
868
+ [2025-10-28 19:50:19] (step=0077200) Train Loss: 0.4575, Train Steps/Sec: 1.13
869
+ [2025-10-28 19:51:47] (step=0077300) Train Loss: 0.4572, Train Steps/Sec: 1.13
870
+ [2025-10-28 19:53:15] (step=0077400) Train Loss: 0.4580, Train Steps/Sec: 1.13
871
+ [2025-10-28 19:54:43] (step=0077500) Train Loss: 0.4558, Train Steps/Sec: 1.13
872
+ [2025-10-28 19:55:39] Beginning epoch 62...
873
+ [2025-10-28 19:56:15] (step=0077600) Train Loss: 0.4573, Train Steps/Sec: 1.10
874
+ [2025-10-28 19:57:43] (step=0077700) Train Loss: 0.4579, Train Steps/Sec: 1.13
875
+ [2025-10-28 19:59:11] (step=0077800) Train Loss: 0.4557, Train Steps/Sec: 1.13
876
+ [2025-10-28 20:00:39] (step=0077900) Train Loss: 0.4563, Train Steps/Sec: 1.13
877
+ [2025-10-28 20:02:07] (step=0078000) Train Loss: 0.4583, Train Steps/Sec: 1.13
878
+ [2025-10-28 20:03:35] (step=0078100) Train Loss: 0.4577, Train Steps/Sec: 1.13
879
+ [2025-10-28 20:05:04] (step=0078200) Train Loss: 0.4561, Train Steps/Sec: 1.13
880
+ [2025-10-28 20:06:32] (step=0078300) Train Loss: 0.4556, Train Steps/Sec: 1.13
881
+ [2025-10-28 20:08:01] (step=0078400) Train Loss: 0.4577, Train Steps/Sec: 1.13
882
+ [2025-10-28 20:09:29] (step=0078500) Train Loss: 0.4576, Train Steps/Sec: 1.13
883
+ [2025-10-28 20:10:57] (step=0078600) Train Loss: 0.4565, Train Steps/Sec: 1.13
884
+ [2025-10-28 20:12:25] (step=0078700) Train Loss: 0.4591, Train Steps/Sec: 1.13
885
+ [2025-10-28 20:13:53] (step=0078800) Train Loss: 0.4576, Train Steps/Sec: 1.13
886
+ [2025-10-28 20:14:05] Beginning epoch 63...
887
+ [2025-10-28 20:15:24] (step=0078900) Train Loss: 0.4558, Train Steps/Sec: 1.10
888
+ [2025-10-28 20:16:53] (step=0079000) Train Loss: 0.4582, Train Steps/Sec: 1.13
889
+ [2025-10-28 20:18:21] (step=0079100) Train Loss: 0.4562, Train Steps/Sec: 1.13
890
+ [2025-10-28 20:19:50] (step=0079200) Train Loss: 0.4561, Train Steps/Sec: 1.13
891
+ [2025-10-28 20:21:18] (step=0079300) Train Loss: 0.4573, Train Steps/Sec: 1.13
892
+ [2025-10-28 20:22:46] (step=0079400) Train Loss: 0.4581, Train Steps/Sec: 1.13
893
+ [2025-10-28 20:24:14] (step=0079500) Train Loss: 0.4566, Train Steps/Sec: 1.13
894
+ [2025-10-28 20:25:43] (step=0079600) Train Loss: 0.4574, Train Steps/Sec: 1.13
895
+ [2025-10-28 20:27:11] (step=0079700) Train Loss: 0.4579, Train Steps/Sec: 1.13
896
+ [2025-10-28 20:28:39] (step=0079800) Train Loss: 0.4560, Train Steps/Sec: 1.13
897
+ [2025-10-28 20:30:07] (step=0079900) Train Loss: 0.4563, Train Steps/Sec: 1.13
898
+ [2025-10-28 20:31:36] (step=0080000) Train Loss: 0.4564, Train Steps/Sec: 1.13
899
+ [2025-10-28 20:32:33] Beginning epoch 64...
900
+ [2025-10-28 20:33:07] (step=0080100) Train Loss: 0.4578, Train Steps/Sec: 1.10
901
+ [2025-10-28 20:34:35] (step=0080200) Train Loss: 0.4564, Train Steps/Sec: 1.13
902
+ [2025-10-28 20:36:03] (step=0080300) Train Loss: 0.4575, Train Steps/Sec: 1.13
903
+ [2025-10-28 20:37:32] (step=0080400) Train Loss: 0.4559, Train Steps/Sec: 1.13
904
+ [2025-10-28 20:39:00] (step=0080500) Train Loss: 0.4565, Train Steps/Sec: 1.13
905
+ [2025-10-28 20:40:28] (step=0080600) Train Loss: 0.4577, Train Steps/Sec: 1.13
906
+ [2025-10-28 20:41:56] (step=0080700) Train Loss: 0.4550, Train Steps/Sec: 1.13
907
+ [2025-10-28 20:43:25] (step=0080800) Train Loss: 0.4580, Train Steps/Sec: 1.13
908
+ [2025-10-28 20:44:53] (step=0080900) Train Loss: 0.4557, Train Steps/Sec: 1.13
909
+ [2025-10-28 20:46:21] (step=0081000) Train Loss: 0.4563, Train Steps/Sec: 1.13
910
+ [2025-10-28 20:47:49] (step=0081100) Train Loss: 0.4582, Train Steps/Sec: 1.13
911
+ [2025-10-28 20:49:17] (step=0081200) Train Loss: 0.4579, Train Steps/Sec: 1.13
912
+ [2025-10-28 20:50:46] (step=0081300) Train Loss: 0.4555, Train Steps/Sec: 1.13
913
+ [2025-10-28 20:50:59] Beginning epoch 65...
914
+ [2025-10-28 20:52:17] (step=0081400) Train Loss: 0.4563, Train Steps/Sec: 1.10
915
+ [2025-10-28 20:53:45] (step=0081500) Train Loss: 0.4556, Train Steps/Sec: 1.13
916
+ [2025-10-28 20:55:14] (step=0081600) Train Loss: 0.4562, Train Steps/Sec: 1.12
917
+ [2025-10-28 20:56:42] (step=0081700) Train Loss: 0.4563, Train Steps/Sec: 1.13
918
+ [2025-10-28 20:58:10] (step=0081800) Train Loss: 0.4563, Train Steps/Sec: 1.13
919
+ [2025-10-28 20:59:38] (step=0081900) Train Loss: 0.4562, Train Steps/Sec: 1.13
920
+ [2025-10-28 21:01:06] (step=0082000) Train Loss: 0.4563, Train Steps/Sec: 1.13
921
+ [2025-10-28 21:02:35] (step=0082100) Train Loss: 0.4574, Train Steps/Sec: 1.13
922
+ [2025-10-28 21:04:03] (step=0082200) Train Loss: 0.4565, Train Steps/Sec: 1.13
923
+ [2025-10-28 21:05:31] (step=0082300) Train Loss: 0.4559, Train Steps/Sec: 1.13
924
+ [2025-10-28 21:06:59] (step=0082400) Train Loss: 0.4571, Train Steps/Sec: 1.13
925
+ [2025-10-28 21:08:28] (step=0082500) Train Loss: 0.4559, Train Steps/Sec: 1.13
926
+ [2025-10-28 21:09:26] Beginning epoch 66...
927
+ [2025-10-28 21:09:59] (step=0082600) Train Loss: 0.4569, Train Steps/Sec: 1.10
928
+ [2025-10-28 21:11:27] (step=0082700) Train Loss: 0.4569, Train Steps/Sec: 1.13
929
+ [2025-10-28 21:12:55] (step=0082800) Train Loss: 0.4561, Train Steps/Sec: 1.13
930
+ [2025-10-28 21:14:24] (step=0082900) Train Loss: 0.4562, Train Steps/Sec: 1.13
931
+ [2025-10-28 21:15:52] (step=0083000) Train Loss: 0.4560, Train Steps/Sec: 1.13
932
+ [2025-10-28 21:17:20] (step=0083100) Train Loss: 0.4563, Train Steps/Sec: 1.14
933
+ [2025-10-28 21:18:48] (step=0083200) Train Loss: 0.4588, Train Steps/Sec: 1.13
934
+ [2025-10-28 21:20:17] (step=0083300) Train Loss: 0.4562, Train Steps/Sec: 1.13
935
+ [2025-10-28 21:21:45] (step=0083400) Train Loss: 0.4560, Train Steps/Sec: 1.13
936
+ [2025-10-28 21:23:13] (step=0083500) Train Loss: 0.4559, Train Steps/Sec: 1.13
937
+ [2025-10-28 21:24:41] (step=0083600) Train Loss: 0.4565, Train Steps/Sec: 1.13
938
+ [2025-10-28 21:26:10] (step=0083700) Train Loss: 0.4558, Train Steps/Sec: 1.13
939
+ [2025-10-28 21:27:38] (step=0083800) Train Loss: 0.4571, Train Steps/Sec: 1.13
940
+ [2025-10-28 21:27:53] Beginning epoch 67...
941
+ [2025-10-28 21:29:09] (step=0083900) Train Loss: 0.4567, Train Steps/Sec: 1.10
942
+ [2025-10-28 21:30:37] (step=0084000) Train Loss: 0.4561, Train Steps/Sec: 1.13
943
+ [2025-10-28 21:32:05] (step=0084100) Train Loss: 0.4565, Train Steps/Sec: 1.13
944
+ [2025-10-28 21:33:34] (step=0084200) Train Loss: 0.4548, Train Steps/Sec: 1.12
945
+ [2025-10-28 21:35:02] (step=0084300) Train Loss: 0.4581, Train Steps/Sec: 1.13
946
+ [2025-10-28 21:36:30] (step=0084400) Train Loss: 0.4555, Train Steps/Sec: 1.13
947
+ [2025-10-28 21:37:59] (step=0084500) Train Loss: 0.4544, Train Steps/Sec: 1.13
948
+ [2025-10-28 21:39:27] (step=0084600) Train Loss: 0.4572, Train Steps/Sec: 1.13
949
+ [2025-10-28 21:40:55] (step=0084700) Train Loss: 0.4553, Train Steps/Sec: 1.13
950
+ [2025-10-28 21:42:23] (step=0084800) Train Loss: 0.4566, Train Steps/Sec: 1.13
951
+ [2025-10-28 21:43:51] (step=0084900) Train Loss: 0.4564, Train Steps/Sec: 1.13
952
+ [2025-10-28 21:45:20] (step=0085000) Train Loss: 0.4569, Train Steps/Sec: 1.13
953
+ [2025-10-28 21:46:21] Beginning epoch 68...
954
+ [2025-10-28 21:46:51] (step=0085100) Train Loss: 0.4557, Train Steps/Sec: 1.10
955
+ [2025-10-28 21:48:19] (step=0085200) Train Loss: 0.4547, Train Steps/Sec: 1.13
956
+ [2025-10-28 21:49:47] (step=0085300) Train Loss: 0.4555, Train Steps/Sec: 1.13
957
+ [2025-10-28 21:51:16] (step=0085400) Train Loss: 0.4562, Train Steps/Sec: 1.13
958
+ [2025-10-28 21:52:44] (step=0085500) Train Loss: 0.4577, Train Steps/Sec: 1.13
959
+ [2025-10-28 21:54:12] (step=0085600) Train Loss: 0.4562, Train Steps/Sec: 1.14
960
+ [2025-10-28 21:55:40] (step=0085700) Train Loss: 0.4566, Train Steps/Sec: 1.13
961
+ [2025-10-28 21:57:08] (step=0085800) Train Loss: 0.4575, Train Steps/Sec: 1.13
962
+ [2025-10-28 21:58:37] (step=0085900) Train Loss: 0.4550, Train Steps/Sec: 1.13
963
+ [2025-10-28 22:00:05] (step=0086000) Train Loss: 0.4561, Train Steps/Sec: 1.13
964
+ [2025-10-28 22:01:33] (step=0086100) Train Loss: 0.4561, Train Steps/Sec: 1.13
965
+ [2025-10-28 22:03:01] (step=0086200) Train Loss: 0.4536, Train Steps/Sec: 1.13
966
+ [2025-10-28 22:04:29] (step=0086300) Train Loss: 0.4554, Train Steps/Sec: 1.13
967
+ [2025-10-28 22:04:47] Beginning epoch 69...
968
+ [2025-10-28 22:06:01] (step=0086400) Train Loss: 0.4566, Train Steps/Sec: 1.10
969
+ [2025-10-28 22:07:29] (step=0086500) Train Loss: 0.4561, Train Steps/Sec: 1.13
970
+ [2025-10-28 22:08:57] (step=0086600) Train Loss: 0.4540, Train Steps/Sec: 1.13
971
+ [2025-10-28 22:10:26] (step=0086700) Train Loss: 0.4557, Train Steps/Sec: 1.12
972
+ [2025-10-28 22:11:54] (step=0086800) Train Loss: 0.4569, Train Steps/Sec: 1.13
973
+ [2025-10-28 22:13:22] (step=0086900) Train Loss: 0.4550, Train Steps/Sec: 1.13
974
+ [2025-10-28 22:14:50] (step=0087000) Train Loss: 0.4550, Train Steps/Sec: 1.13
975
+ [2025-10-28 22:16:19] (step=0087100) Train Loss: 0.4555, Train Steps/Sec: 1.13
976
+ [2025-10-28 22:17:47] (step=0087200) Train Loss: 0.4563, Train Steps/Sec: 1.13
977
+ [2025-10-28 22:19:15] (step=0087300) Train Loss: 0.4560, Train Steps/Sec: 1.13
978
+ [2025-10-28 22:20:43] (step=0087400) Train Loss: 0.4547, Train Steps/Sec: 1.13
979
+ [2025-10-28 22:22:11] (step=0087500) Train Loss: 0.4558, Train Steps/Sec: 1.13
980
+ [2025-10-28 22:23:14] Beginning epoch 70...
981
+ [2025-10-28 22:23:43] (step=0087600) Train Loss: 0.4562, Train Steps/Sec: 1.10
982
+ [2025-10-28 22:25:11] (step=0087700) Train Loss: 0.4552, Train Steps/Sec: 1.13
983
+ [2025-10-28 22:26:39] (step=0087800) Train Loss: 0.4553, Train Steps/Sec: 1.13
984
+ [2025-10-28 22:28:07] (step=0087900) Train Loss: 0.4551, Train Steps/Sec: 1.13
985
+ [2025-10-28 22:29:35] (step=0088000) Train Loss: 0.4534, Train Steps/Sec: 1.14
986
+ [2025-10-28 22:31:03] (step=0088100) Train Loss: 0.4549, Train Steps/Sec: 1.13
987
+ [2025-10-28 22:32:31] (step=0088200) Train Loss: 0.4555, Train Steps/Sec: 1.14
988
+ [2025-10-28 22:34:00] (step=0088300) Train Loss: 0.4566, Train Steps/Sec: 1.14
989
+ [2025-10-28 22:35:28] (step=0088400) Train Loss: 0.4547, Train Steps/Sec: 1.13
990
+ [2025-10-28 22:36:57] (step=0088500) Train Loss: 0.4551, Train Steps/Sec: 1.13
991
+ [2025-10-28 22:38:25] (step=0088600) Train Loss: 0.4554, Train Steps/Sec: 1.14
992
+ [2025-10-28 22:39:53] (step=0088700) Train Loss: 0.4562, Train Steps/Sec: 1.13
993
+ [2025-10-28 22:41:21] (step=0088800) Train Loss: 0.4558, Train Steps/Sec: 1.13
994
+ [2025-10-28 22:41:40] Beginning epoch 71...
995
+ [2025-10-28 22:42:52] (step=0088900) Train Loss: 0.4566, Train Steps/Sec: 1.10
996
+ [2025-10-28 22:44:20] (step=0089000) Train Loss: 0.4554, Train Steps/Sec: 1.13
997
+ [2025-10-28 22:45:48] (step=0089100) Train Loss: 0.4555, Train Steps/Sec: 1.13
998
+ [2025-10-28 22:47:17] (step=0089200) Train Loss: 0.4546, Train Steps/Sec: 1.13
999
+ [2025-10-28 22:48:45] (step=0089300) Train Loss: 0.4562, Train Steps/Sec: 1.13
1000
+ [2025-10-28 22:50:13] (step=0089400) Train Loss: 0.4541, Train Steps/Sec: 1.13