Hugging Face's logo

ilessio-aiflowlab
/
DEF-rtfdnet

Image Segmentation
PyTorch
ONNX
Safetensors
robotics
anima
rgb-thermal
semantic-segmentation
segformer
defense
robot-flow-labs
Model card Files
xet
 Community
ilessio-aiflowlab commited on
Commit
2d4d4ff
·
verified ·
1 Parent(s): b66cac9

Upload logs/train_fmb_20260404_1832.log with huggingface_hub

Browse files
Files changed (1) hide show
  1. logs/train_fmb_20260404_1832.log +179 -0
logs/train_fmb_20260404_1832.log ADDED
@@ -0,0 +1,179 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ 2026-04-04 18:32:49 [INFO] Loaded 664 pretrained weights into both streams. Missing backbone keys: 0, Unexpected: 0
2
+ 2026-04-04 18:32:51 [INFO] [MODEL] mit_b2 | 50.4M params | 14 classes
3
+ 2026-04-04 18:32:51 [INFO] RGBTDataset [data/ade_fmb/training]: 1220 samples (skipped 0 without annotation)
4
+ 2026-04-04 18:32:51 [INFO] RGBTDataset [data/ade_fmb/validation]: 280 samples (skipped 0 without annotation)
5
+ 2026-04-04 18:32:51 [INFO] [DATA] fmb | train=1220 val=280 | crop=(512, 512)
6
+ 2026-04-04 18:32:51 [INFO] [BATCH] Config batch_size=4
7
+ 2026-04-04 18:32:51 [INFO] [CONFIG] configs/fmb_b2.toml
8
+ 2026-04-04 18:32:51 [INFO] [GPU] NVIDIA L4 (22563MB)
9
+ 2026-04-04 18:32:51 [INFO] [TRAIN] 300 epochs, lr=3.00e-05, optimizer=adamw
10
+ 2026-04-04 18:32:51 [INFO] [CKPT] save every 10 epochs, keep best 2
11
+ 2026-04-04 18:37:19 [INFO] [TRAIN] Epoch 0 | loss=6.0595 | lr=1.00e-05 | 4.6 samples/sec | 267.6s
12
+ 2026-04-04 18:41:38 [INFO] [TRAIN] Epoch 1 | loss=3.2261 | lr=1.00e-05 | 4.7 samples/sec | 259.8s
13
+ 2026-04-04 18:45:59 [INFO] [TRAIN] Epoch 2 | loss=2.3690 | lr=1.00e-05 | 4.7 samples/sec | 260.3s
14
+ 2026-04-04 18:50:19 [INFO] [TRAIN] Epoch 3 | loss=1.8940 | lr=1.00e-05 | 4.7 samples/sec | 260.1s
15
+ 2026-04-04 18:54:39 [INFO] [TRAIN] Epoch 4 | loss=1.5675 | lr=1.00e-05 | 4.7 samples/sec | 259.6s
16
+ /mnt/forge-data/modules/04_wave8/DEF-rtfdnet/src/def_rtfdnet/train.py:171: RuntimeWarning: invalid value encountered in divide
17
+ iou = np.where(union > 0, intersection / union, 0.0)
18
+ 2026-04-04 18:55:42 [INFO] [VAL] loss=1.3965 | mIoU=0.3247 | acc=0.8775
19
+ 2026-04-04 18:55:44 [INFO] [BEST] mIoU=0.3247 at epoch 4
20
+ 2026-04-04 19:00:04 [INFO] [TRAIN] Epoch 5 | loss=1.3846 | lr=1.20e-05 | 4.7 samples/sec | 260.9s
21
+ 2026-04-04 19:04:25 [INFO] [TRAIN] Epoch 6 | loss=1.3084 | lr=1.40e-05 | 4.7 samples/sec | 260.3s
22
+ 2026-04-04 19:08:45 [INFO] [TRAIN] Epoch 7 | loss=1.2041 | lr=1.60e-05 | 4.7 samples/sec | 260.7s
23
+ 2026-04-04 19:13:06 [INFO] [TRAIN] Epoch 8 | loss=1.1008 | lr=1.80e-05 | 4.7 samples/sec | 260.9s
24
+ 2026-04-04 19:17:26 [INFO] [TRAIN] Epoch 9 | loss=1.0539 | lr=2.00e-05 | 4.7 samples/sec | 259.8s
25
+ 2026-04-04 19:18:29 [INFO] [VAL] loss=1.1006 | mIoU=0.4662 | acc=0.8948
26
+ 2026-04-04 19:18:30 [INFO] [BEST] mIoU=0.4662 at epoch 9
27
+ 2026-04-04 19:22:51 [INFO] [TRAIN] Epoch 10 | loss=1.0235 | lr=2.20e-05 | 4.7 samples/sec | 260.3s
28
+ 2026-04-04 19:27:11 [INFO] [TRAIN] Epoch 11 | loss=0.9764 | lr=2.40e-05 | 4.7 samples/sec | 260.3s
29
+ 2026-04-04 19:31:31 [INFO] [TRAIN] Epoch 12 | loss=0.9201 | lr=2.60e-05 | 4.7 samples/sec | 260.2s
30
+ 2026-04-04 19:35:51 [INFO] [TRAIN] Epoch 13 | loss=0.8912 | lr=2.80e-05 | 4.7 samples/sec | 260.1s
31
+ 2026-04-04 19:40:12 [INFO] [TRAIN] Epoch 14 | loss=0.8803 | lr=3.00e-05 | 4.7 samples/sec | 260.1s
32
+ 2026-04-04 19:41:12 [INFO] [VAL] loss=0.9619 | mIoU=0.5775 | acc=0.9154
33
+ 2026-04-04 19:41:14 [INFO] [BEST] mIoU=0.5775 at epoch 14
34
+ 2026-04-04 19:45:35 [INFO] [TRAIN] Epoch 15 | loss=0.8395 | lr=3.00e-05 | 4.7 samples/sec | 260.7s
35
+ 2026-04-04 19:49:56 [INFO] [TRAIN] Epoch 16 | loss=0.8192 | lr=3.00e-05 | 4.7 samples/sec | 260.6s
36
+ 2026-04-04 19:54:16 [INFO] [TRAIN] Epoch 17 | loss=0.7806 | lr=3.00e-05 | 4.7 samples/sec | 260.3s
37
+ 2026-04-04 19:58:35 [INFO] [TRAIN] Epoch 18 | loss=0.7504 | lr=3.00e-05 | 4.7 samples/sec | 258.9s
38
+ 2026-04-04 20:02:54 [INFO] [TRAIN] Epoch 19 | loss=0.7273 | lr=3.00e-05 | 4.7 samples/sec | 259.3s
39
+ 2026-04-04 20:03:54 [INFO] [VAL] loss=0.7973 | mIoU=0.6211 | acc=0.9288
40
+ 2026-04-04 20:03:56 [INFO] [BEST] mIoU=0.6211 at epoch 19
41
+ 2026-04-04 20:08:15 [INFO] [TRAIN] Epoch 20 | loss=0.7362 | lr=3.00e-05 | 4.7 samples/sec | 259.6s
42
+ 2026-04-04 20:12:35 [INFO] [TRAIN] Epoch 21 | loss=0.7138 | lr=3.00e-05 | 4.7 samples/sec | 259.4s
43
+ 2026-04-04 20:16:53 [INFO] [TRAIN] Epoch 22 | loss=0.6845 | lr=2.99e-05 | 4.7 samples/sec | 258.6s
44
+ 2026-04-04 20:21:11 [INFO] [TRAIN] Epoch 23 | loss=0.6761 | lr=2.99e-05 | 4.7 samples/sec | 257.8s
45
+ 2026-04-04 20:23:52 [INFO] [TRAIN] Epoch 24 | loss=0.6773 | lr=2.99e-05 | 7.6 samples/sec | 161.3s
46
+ 2026-04-04 20:24:49 [INFO] [VAL] loss=0.8198 | mIoU=0.6302 | acc=0.9252
47
+ 2026-04-04 20:24:50 [INFO] [BEST] mIoU=0.6302 at epoch 24
48
+ 2026-04-04 20:27:32 [INFO] [TRAIN] Epoch 25 | loss=0.6597 | lr=2.99e-05 | 7.6 samples/sec | 161.4s
49
+ 2026-04-04 20:30:14 [INFO] [TRAIN] Epoch 26 | loss=0.6423 | lr=2.99e-05 | 7.5 samples/sec | 162.0s
50
+ 2026-04-04 20:32:55 [INFO] [TRAIN] Epoch 27 | loss=0.6632 | lr=2.98e-05 | 7.6 samples/sec | 161.2s
51
+ 2026-04-04 20:35:37 [INFO] [TRAIN] Epoch 28 | loss=0.6378 | lr=2.98e-05 | 7.5 samples/sec | 161.8s
52
+ 2026-04-04 20:38:18 [INFO] [TRAIN] Epoch 29 | loss=0.6361 | lr=2.98e-05 | 7.6 samples/sec | 161.2s
53
+ 2026-04-04 20:39:14 [INFO] [VAL] loss=0.7975 | mIoU=0.6556 | acc=0.9258
54
+ 2026-04-04 20:39:15 [INFO] [BEST] mIoU=0.6556 at epoch 29
55
+ 2026-04-04 20:41:57 [INFO] [TRAIN] Epoch 30 | loss=0.6257 | lr=2.98e-05 | 7.6 samples/sec | 161.3s
56
+ 2026-04-04 20:44:38 [INFO] [TRAIN] Epoch 31 | loss=0.6272 | lr=2.97e-05 | 7.6 samples/sec | 161.6s
57
+ 2026-04-04 20:47:19 [INFO] [TRAIN] Epoch 32 | loss=0.5938 | lr=2.97e-05 | 7.6 samples/sec | 161.0s
58
+ 2026-04-04 20:50:01 [INFO] [TRAIN] Epoch 33 | loss=0.5919 | lr=2.97e-05 | 7.6 samples/sec | 161.5s
59
+ 2026-04-04 20:52:43 [INFO] [TRAIN] Epoch 34 | loss=0.5856 | lr=2.96e-05 | 7.5 samples/sec | 161.9s
60
+ 2026-04-04 20:53:39 [INFO] [VAL] loss=0.7684 | mIoU=0.6574 | acc=0.9294
61
+ 2026-04-04 20:53:40 [INFO] [BEST] mIoU=0.6574 at epoch 34
62
+ 2026-04-04 20:56:21 [INFO] [TRAIN] Epoch 35 | loss=0.5966 | lr=2.96e-05 | 7.6 samples/sec | 160.8s
63
+ 2026-04-04 20:59:02 [INFO] [TRAIN] Epoch 36 | loss=0.5757 | lr=2.96e-05 | 7.6 samples/sec | 160.6s
64
+ 2026-04-04 21:01:43 [INFO] [TRAIN] Epoch 37 | loss=0.5838 | lr=2.95e-05 | 7.6 samples/sec | 160.9s
65
+ 2026-04-04 21:04:23 [INFO] [TRAIN] Epoch 38 | loss=0.5904 | lr=2.95e-05 | 7.6 samples/sec | 160.4s
66
+ 2026-04-04 21:07:04 [INFO] [TRAIN] Epoch 39 | loss=0.5661 | lr=2.94e-05 | 7.6 samples/sec | 161.2s
67
+ 2026-04-04 21:08:00 [INFO] [VAL] loss=0.8079 | mIoU=0.6442 | acc=0.9268
68
+ 2026-04-04 21:10:43 [INFO] [TRAIN] Epoch 40 | loss=0.5711 | lr=2.94e-05 | 7.6 samples/sec | 161.2s
69
+ 2026-04-04 21:13:24 [INFO] [TRAIN] Epoch 41 | loss=0.5579 | lr=2.93e-05 | 7.6 samples/sec | 161.0s
70
+ 2026-04-04 21:16:05 [INFO] [TRAIN] Epoch 42 | loss=0.5544 | lr=2.93e-05 | 7.6 samples/sec | 161.5s
71
+ 2026-04-04 21:18:46 [INFO] [TRAIN] Epoch 43 | loss=0.5581 | lr=2.92e-05 | 7.6 samples/sec | 161.0s
72
+ 2026-04-04 21:21:27 [INFO] [TRAIN] Epoch 44 | loss=0.5548 | lr=2.92e-05 | 7.6 samples/sec | 161.3s
73
+ 2026-04-04 21:22:24 [INFO] [VAL] loss=0.7947 | mIoU=0.6656 | acc=0.9308
74
+ 2026-04-04 21:22:26 [INFO] [BEST] mIoU=0.6656 at epoch 44
75
+ 2026-04-04 21:25:08 [INFO] [TRAIN] Epoch 45 | loss=0.5465 | lr=2.91e-05 | 7.5 samples/sec | 161.7s
76
+ 2026-04-04 21:27:49 [INFO] [TRAIN] Epoch 46 | loss=0.5391 | lr=2.91e-05 | 7.6 samples/sec | 161.0s
77
+ 2026-04-04 21:30:30 [INFO] [TRAIN] Epoch 47 | loss=0.5429 | lr=2.90e-05 | 7.6 samples/sec | 161.5s
78
+ 2026-04-04 21:33:11 [INFO] [TRAIN] Epoch 48 | loss=0.5500 | lr=2.90e-05 | 7.6 samples/sec | 160.7s
79
+ 2026-04-04 21:35:52 [INFO] [TRAIN] Epoch 49 | loss=0.5280 | lr=2.89e-05 | 7.6 samples/sec | 160.8s
80
+ 2026-04-04 21:36:48 [INFO] [VAL] loss=0.7909 | mIoU=0.6788 | acc=0.9331
81
+ 2026-04-04 21:36:50 [INFO] [BEST] mIoU=0.6788 at epoch 49
82
+ 2026-04-04 21:39:32 [INFO] [TRAIN] Epoch 50 | loss=0.5178 | lr=2.88e-05 | 7.6 samples/sec | 161.5s
83
+ 2026-04-04 21:42:13 [INFO] [TRAIN] Epoch 51 | loss=0.5293 | lr=2.88e-05 | 7.6 samples/sec | 161.6s
84
+ 2026-04-04 21:44:55 [INFO] [TRAIN] Epoch 52 | loss=0.5166 | lr=2.87e-05 | 7.6 samples/sec | 161.6s
85
+ 2026-04-04 21:47:38 [INFO] [TRAIN] Epoch 53 | loss=0.5312 | lr=2.86e-05 | 7.5 samples/sec | 163.1s
86
+ 2026-04-04 21:50:20 [INFO] [TRAIN] Epoch 54 | loss=0.5235 | lr=2.86e-05 | 7.5 samples/sec | 162.5s
87
+ 2026-04-04 21:51:16 [INFO] [VAL] loss=0.8111 | mIoU=0.6444 | acc=0.9284
88
+ 2026-04-04 21:53:58 [INFO] [TRAIN] Epoch 55 | loss=0.5136 | lr=2.85e-05 | 7.5 samples/sec | 161.6s
89
+ 2026-04-04 21:56:19 [INFO] [TRAIN] Epoch 56 | loss=0.5205 | lr=2.84e-05 | 8.7 samples/sec | 140.7s
90
+ 2026-04-04 21:58:32 [INFO] [TRAIN] Epoch 57 | loss=0.4960 | lr=2.83e-05 | 9.2 samples/sec | 132.8s
91
+ 2026-04-04 22:00:45 [INFO] [TRAIN] Epoch 58 | loss=0.5055 | lr=2.83e-05 | 9.2 samples/sec | 133.3s
92
+ 2026-04-04 22:02:58 [INFO] [TRAIN] Epoch 59 | loss=0.5092 | lr=2.82e-05 | 9.1 samples/sec | 133.4s
93
+ 2026-04-04 22:03:55 [INFO] [VAL] loss=0.8483 | mIoU=0.6193 | acc=0.9260
94
+ 2026-04-04 22:06:12 [INFO] [TRAIN] Epoch 60 | loss=0.5122 | lr=2.81e-05 | 9.1 samples/sec | 134.6s
95
+ 2026-04-04 22:08:25 [INFO] [TRAIN] Epoch 61 | loss=0.4946 | lr=2.80e-05 | 9.2 samples/sec | 132.8s
96
+ 2026-04-04 22:10:38 [INFO] [TRAIN] Epoch 62 | loss=0.4831 | lr=2.79e-05 | 9.2 samples/sec | 132.9s
97
+ 2026-04-04 22:12:52 [INFO] [TRAIN] Epoch 63 | loss=0.4924 | lr=2.79e-05 | 9.1 samples/sec | 133.6s
98
+ 2026-04-04 22:15:04 [INFO] [TRAIN] Epoch 64 | loss=0.4985 | lr=2.78e-05 | 9.2 samples/sec | 132.6s
99
+ 2026-04-04 22:15:59 [INFO] [VAL] loss=0.8041 | mIoU=0.6453 | acc=0.9280
100
+ 2026-04-04 22:18:13 [INFO] [TRAIN] Epoch 65 | loss=0.5020 | lr=2.77e-05 | 9.1 samples/sec | 133.5s
101
+ 2026-04-04 22:20:28 [INFO] [TRAIN] Epoch 66 | loss=0.4884 | lr=2.76e-05 | 9.0 samples/sec | 134.8s
102
+ 2026-04-04 22:22:40 [INFO] [TRAIN] Epoch 67 | loss=0.4913 | lr=2.75e-05 | 9.2 samples/sec | 132.9s
103
+ 2026-04-04 22:24:53 [INFO] [TRAIN] Epoch 68 | loss=0.4850 | lr=2.74e-05 | 9.2 samples/sec | 133.0s
104
+ 2026-04-04 22:27:07 [INFO] [TRAIN] Epoch 69 | loss=0.4905 | lr=2.73e-05 | 9.1 samples/sec | 133.4s
105
+ 2026-04-04 22:28:05 [INFO] [VAL] loss=0.8051 | mIoU=0.6106 | acc=0.9282
106
+ 2026-04-04 22:30:21 [INFO] [TRAIN] Epoch 70 | loss=0.4815 | lr=2.72e-05 | 9.2 samples/sec | 132.9s
107
+ 2026-04-04 22:32:35 [INFO] [TRAIN] Epoch 71 | loss=0.4903 | lr=2.71e-05 | 9.1 samples/sec | 133.8s
108
+ 2026-04-04 22:34:48 [INFO] [TRAIN] Epoch 72 | loss=0.4813 | lr=2.70e-05 | 9.2 samples/sec | 133.1s
109
+ 2026-04-04 22:37:01 [INFO] [TRAIN] Epoch 73 | loss=0.4697 | lr=2.69e-05 | 9.1 samples/sec | 133.4s
110
+ 2026-04-04 22:39:16 [INFO] [TRAIN] Epoch 74 | loss=0.4949 | lr=2.68e-05 | 9.1 samples/sec | 134.7s
111
+ 2026-04-04 22:40:13 [INFO] [VAL] loss=0.8234 | mIoU=0.6844 | acc=0.9313
112
+ 2026-04-04 22:40:15 [INFO] [BEST] mIoU=0.6844 at epoch 74
113
+ 2026-04-04 22:42:31 [INFO] [TRAIN] Epoch 75 | loss=0.4797 | lr=2.67e-05 | 8.9 samples/sec | 136.4s
114
+ 2026-04-04 22:44:45 [INFO] [TRAIN] Epoch 76 | loss=0.4681 | lr=2.66e-05 | 9.1 samples/sec | 133.5s
115
+ 2026-04-04 22:47:00 [INFO] [TRAIN] Epoch 77 | loss=0.4923 | lr=2.65e-05 | 9.0 samples/sec | 135.5s
116
+ 2026-04-04 22:49:14 [INFO] [TRAIN] Epoch 78 | loss=0.4705 | lr=2.64e-05 | 9.1 samples/sec | 133.3s
117
+ 2026-04-04 22:51:27 [INFO] [TRAIN] Epoch 79 | loss=0.4769 | lr=2.63e-05 | 9.2 samples/sec | 133.1s
118
+ 2026-04-04 22:52:22 [INFO] [VAL] loss=0.8079 | mIoU=0.6507 | acc=0.9292
119
+ 2026-04-04 22:54:37 [INFO] [TRAIN] Epoch 80 | loss=0.4814 | lr=2.62e-05 | 9.2 samples/sec | 132.3s
120
+ 2026-04-04 22:56:51 [INFO] [TRAIN] Epoch 81 | loss=0.4582 | lr=2.61e-05 | 9.1 samples/sec | 133.7s
121
+ 2026-04-04 22:59:05 [INFO] [TRAIN] Epoch 82 | loss=0.4699 | lr=2.60e-05 | 9.1 samples/sec | 134.0s
122
+ 2026-04-04 23:01:18 [INFO] [TRAIN] Epoch 83 | loss=0.4636 | lr=2.59e-05 | 9.2 samples/sec | 132.9s
123
+ 2026-04-04 23:03:31 [INFO] [TRAIN] Epoch 84 | loss=0.4515 | lr=2.58e-05 | 9.1 samples/sec | 133.5s
124
+ 2026-04-04 23:04:28 [INFO] [VAL] loss=0.8526 | mIoU=0.6214 | acc=0.9267
125
+ 2026-04-04 23:06:41 [INFO] [TRAIN] Epoch 85 | loss=0.4706 | lr=2.56e-05 | 9.2 samples/sec | 132.8s
126
+ 2026-04-04 23:08:53 [INFO] [TRAIN] Epoch 86 | loss=0.4428 | lr=2.55e-05 | 9.2 samples/sec | 132.0s
127
+ 2026-04-04 23:11:05 [INFO] [TRAIN] Epoch 87 | loss=0.4620 | lr=2.54e-05 | 9.2 samples/sec | 132.5s
128
+ 2026-04-04 23:13:19 [INFO] [TRAIN] Epoch 88 | loss=0.4562 | lr=2.53e-05 | 9.2 samples/sec | 133.3s
129
+ 2026-04-04 23:15:31 [INFO] [TRAIN] Epoch 89 | loss=0.4595 | lr=2.52e-05 | 9.2 samples/sec | 132.2s
130
+ 2026-04-04 23:16:26 [INFO] [VAL] loss=0.8104 | mIoU=0.6536 | acc=0.9288
131
+ 2026-04-04 23:18:43 [INFO] [TRAIN] Epoch 90 | loss=0.4554 | lr=2.50e-05 | 9.1 samples/sec | 134.2s
132
+ 2026-04-04 23:20:56 [INFO] [TRAIN] Epoch 91 | loss=0.4503 | lr=2.49e-05 | 9.2 samples/sec | 133.0s
133
+ 2026-04-04 23:23:09 [INFO] [TRAIN] Epoch 92 | loss=0.4561 | lr=2.48e-05 | 9.2 samples/sec | 133.2s
134
+ 2026-04-04 23:25:22 [INFO] [TRAIN] Epoch 93 | loss=0.4507 | lr=2.47e-05 | 9.2 samples/sec | 132.6s
135
+ 2026-04-04 23:27:34 [INFO] [TRAIN] Epoch 94 | loss=0.4437 | lr=2.45e-05 | 9.2 samples/sec | 132.1s
136
+ 2026-04-04 23:28:29 [INFO] [VAL] loss=0.8477 | mIoU=0.6374 | acc=0.9277
137
+ 2026-04-04 23:30:43 [INFO] [TRAIN] Epoch 95 | loss=0.4550 | lr=2.44e-05 | 9.1 samples/sec | 133.6s
138
+ 2026-04-04 23:32:56 [INFO] [TRAIN] Epoch 96 | loss=0.4517 | lr=2.43e-05 | 9.2 samples/sec | 132.9s
139
+ 2026-04-04 23:35:08 [INFO] [TRAIN] Epoch 97 | loss=0.4451 | lr=2.41e-05 | 9.2 samples/sec | 132.1s
140
+ 2026-04-04 23:37:21 [INFO] [TRAIN] Epoch 98 | loss=0.4392 | lr=2.40e-05 | 9.1 samples/sec | 133.3s
141
+ 2026-04-04 23:39:33 [INFO] [TRAIN] Epoch 99 | loss=0.4545 | lr=2.39e-05 | 9.2 samples/sec | 132.4s
142
+ 2026-04-04 23:40:28 [INFO] [VAL] loss=0.8378 | mIoU=0.6043 | acc=0.9304
143
+ 2026-04-04 23:42:44 [INFO] [TRAIN] Epoch 100 | loss=0.4364 | lr=2.37e-05 | 9.1 samples/sec | 133.8s
144
+ 2026-04-04 23:44:57 [INFO] [TRAIN] Epoch 101 | loss=0.4435 | lr=2.36e-05 | 9.2 samples/sec | 132.6s
145
+ 2026-04-04 23:47:08 [INFO] [TRAIN] Epoch 102 | loss=0.4373 | lr=2.35e-05 | 9.3 samples/sec | 131.4s
146
+ 2026-04-04 23:49:21 [INFO] [TRAIN] Epoch 103 | loss=0.4407 | lr=2.33e-05 | 9.2 samples/sec | 132.8s
147
+ 2026-04-04 23:51:34 [INFO] [TRAIN] Epoch 104 | loss=0.4442 | lr=2.32e-05 | 9.2 samples/sec | 132.7s
148
+ 2026-04-04 23:52:28 [INFO] [VAL] loss=0.8360 | mIoU=0.6138 | acc=0.9297
149
+ 2026-04-04 23:54:40 [INFO] [TRAIN] Epoch 105 | loss=0.4386 | lr=2.31e-05 | 9.2 samples/sec | 132.1s
150
+ 2026-04-04 23:56:53 [INFO] [TRAIN] Epoch 106 | loss=0.4301 | lr=2.29e-05 | 9.2 samples/sec | 132.4s
151
+ 2026-04-04 23:59:06 [INFO] [TRAIN] Epoch 107 | loss=0.4327 | lr=2.28e-05 | 9.2 samples/sec | 133.1s
152
+ 2026-04-05 00:01:16 [INFO] [TRAIN] Epoch 108 | loss=0.4292 | lr=2.26e-05 | 9.4 samples/sec | 130.5s
153
+ 2026-04-05 00:03:27 [INFO] [TRAIN] Epoch 109 | loss=0.4344 | lr=2.25e-05 | 9.3 samples/sec | 130.6s
154
+ 2026-04-05 00:04:22 [INFO] [VAL] loss=0.8193 | mIoU=0.6508 | acc=0.9294
155
+ 2026-04-05 00:06:35 [INFO] [TRAIN] Epoch 110 | loss=0.4313 | lr=2.24e-05 | 9.3 samples/sec | 131.0s
156
+ 2026-04-05 00:08:46 [INFO] [TRAIN] Epoch 111 | loss=0.4247 | lr=2.22e-05 | 9.3 samples/sec | 131.0s
157
+ 2026-04-05 00:10:57 [INFO] [TRAIN] Epoch 112 | loss=0.4312 | lr=2.21e-05 | 9.3 samples/sec | 130.6s
158
+ 2026-04-05 00:13:08 [INFO] [TRAIN] Epoch 113 | loss=0.4262 | lr=2.19e-05 | 9.3 samples/sec | 131.3s
159
+ 2026-04-05 00:15:18 [INFO] [TRAIN] Epoch 114 | loss=0.4246 | lr=2.18e-05 | 9.4 samples/sec | 130.3s
160
+ 2026-04-05 00:16:13 [INFO] [VAL] loss=0.8361 | mIoU=0.6430 | acc=0.9292
161
+ 2026-04-05 00:18:24 [INFO] [TRAIN] Epoch 115 | loss=0.4275 | lr=2.16e-05 | 9.3 samples/sec | 130.6s
162
+ 2026-04-05 00:20:34 [INFO] [TRAIN] Epoch 116 | loss=0.4301 | lr=2.15e-05 | 9.4 samples/sec | 130.4s
163
+ 2026-04-05 00:22:45 [INFO] [TRAIN] Epoch 117 | loss=0.4283 | lr=2.13e-05 | 9.3 samples/sec | 130.6s
164
+ 2026-04-05 00:24:56 [INFO] [TRAIN] Epoch 118 | loss=0.4230 | lr=2.12e-05 | 9.3 samples/sec | 130.9s
165
+ 2026-04-05 00:27:06 [INFO] [TRAIN] Epoch 119 | loss=0.4314 | lr=2.10e-05 | 9.4 samples/sec | 130.3s
166
+ 2026-04-05 00:28:00 [INFO] [VAL] loss=0.8535 | mIoU=0.6514 | acc=0.9305
167
+ 2026-04-05 00:30:12 [INFO] [TRAIN] Epoch 120 | loss=0.4223 | lr=2.09e-05 | 9.4 samples/sec | 130.1s
168
+ 2026-04-05 00:32:22 [INFO] [TRAIN] Epoch 121 | loss=0.4258 | lr=2.07e-05 | 9.4 samples/sec | 130.0s
169
+ 2026-04-05 00:34:33 [INFO] [TRAIN] Epoch 122 | loss=0.4318 | lr=2.06e-05 | 9.3 samples/sec | 131.1s
170
+ 2026-04-05 00:36:43 [INFO] [TRAIN] Epoch 123 | loss=0.4261 | lr=2.04e-05 | 9.4 samples/sec | 130.2s
171
+ 2026-04-05 00:38:53 [INFO] [TRAIN] Epoch 124 | loss=0.4234 | lr=2.03e-05 | 9.4 samples/sec | 129.8s
172
+ 2026-04-05 00:39:47 [INFO] [VAL] loss=0.8700 | mIoU=0.5975 | acc=0.9289
173
+ 2026-04-05 00:41:58 [INFO] [TRAIN] Epoch 125 | loss=0.4286 | lr=2.01e-05 | 9.4 samples/sec | 130.3s
174
+ 2026-04-05 00:44:07 [INFO] [TRAIN] Epoch 126 | loss=0.4117 | lr=1.99e-05 | 9.4 samples/sec | 129.7s
175
+ 2026-04-05 00:46:18 [INFO] [TRAIN] Epoch 127 | loss=0.4245 | lr=1.98e-05 | 9.4 samples/sec | 130.4s
176
+ 2026-04-05 00:48:31 [INFO] [TRAIN] Epoch 128 | loss=0.4150 | lr=1.96e-05 | 9.2 samples/sec | 133.1s
177
+ 2026-04-05 00:50:44 [INFO] [TRAIN] Epoch 129 | loss=0.4180 | lr=1.95e-05 | 9.2 samples/sec | 132.8s
178
+ 2026-04-05 00:51:39 [INFO] [VAL] loss=0.8497 | mIoU=0.6176 | acc=0.9307
179
+ 2026-04-05 00:53:54 [INFO] [TRAIN] Epoch 130 | loss=0.4133 | lr=1.93e-05 | 9.1 samples/sec | 133.4s