Hugging Face's logo

heromiya
/
segformer-b0-finetuned-segments-sidewalk-2

Image Segmentation
Transformers
TensorBoard
Safetensors
segformer
vision
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
heromiya commited on
Commit
d9a6a8e
·
verified ·
1 Parent(s): 281d715

End of training

Browse files
Files changed (8) hide show
  1. README.md +151 -0
  2. config.json +144 -0
  3. model.safetensors +3 -0
  4. preprocessor_config.json +23 -0
  5. runs/Jan20_06-21-09_jupyter-admin01/events.out.tfevents.1737354101.jupyter-admin01.177.0 +3 -0
  6. runs/Jan20_06-21-09_jupyter-admin01/events.out.tfevents.1737355214.jupyter-admin01.177.1 +3 -0
  7. runs/Jan20_06-45-05_jupyter-admin01/events.out.tfevents.1737355516.jupyter-admin01.177.2 +3 -0
  8. training_args.bin +3 -0
README.md ADDED
@@ -0,0 +1,151 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: transformers
3
+ base_model: hogehoge
4
+ tags:
5
+ - vision
6
+ - image-segmentation
7
+ - generated_from_trainer
8
+ model-index:
9
+ - name: segformer-b0-finetuned-segments-sidewalk-2
10
+ results: []
11
+ ---
12
+
13
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
14
+ should probably proofread and complete it, then remove this comment. -->
15
+
16
+ # segformer-b0-finetuned-segments-sidewalk-2
17
+
18
+ This model is a fine-tuned version of [hogehoge](https://huggingface.co/hogehoge) on the segments/sidewalk-semantic dataset.
19
+ It achieves the following results on the evaluation set:
20
+ - Loss: 0.9393
21
+ - Mean Iou: 0.0027
22
+ - Mean Accuracy: 0.0525
23
+ - Overall Accuracy: 0.0214
24
+ - Accuracy Unlabeled: nan
25
+ - Accuracy Flat-road: 0.0284
26
+ - Accuracy Flat-sidewalk: 0.1051
27
+ - Accuracy Flat-crosswalk: 0.0
28
+ - Accuracy Flat-cyclinglane: 0.0131
29
+ - Accuracy Flat-parkingdriveway: nan
30
+ - Accuracy Flat-railtrack: 0.0
31
+ - Accuracy Flat-curb: 0.0
32
+ - Accuracy Human-person: 0.0
33
+ - Accuracy Human-rider: 0.0
34
+ - Accuracy Vehicle-car: 0.3571
35
+ - Accuracy Vehicle-truck: 0.0
36
+ - Accuracy Vehicle-bus: nan
37
+ - Accuracy Vehicle-tramtrain: 0.0
38
+ - Accuracy Vehicle-motorcycle: 0.0
39
+ - Accuracy Vehicle-bicycle: 0.0
40
+ - Accuracy Vehicle-caravan: 0.0
41
+ - Accuracy Vehicle-cartrailer: 0.0
42
+ - Accuracy Construction-building: 0.9472
43
+ - Accuracy Construction-door: 0.0
44
+ - Accuracy Construction-wall: 0.0000
45
+ - Accuracy Construction-fenceguardrail: 0.0
46
+ - Accuracy Construction-bridge: nan
47
+ - Accuracy Construction-tunnel: 0.0
48
+ - Accuracy Construction-stairs: 0.0
49
+ - Accuracy Object-pole: 0.0
50
+ - Accuracy Object-trafficsign: 0.0
51
+ - Accuracy Object-trafficlight: 0.0
52
+ - Accuracy Nature-vegetation: 0.1241
53
+ - Accuracy Nature-terrain: 0.0000
54
+ - Accuracy Sky: 0.0
55
+ - Accuracy Void-ground: 0.0
56
+ - Accuracy Void-dynamic: 0.0
57
+ - Accuracy Void-static: 0.0
58
+ - Accuracy Void-unclear: nan
59
+ - Iou Unlabeled: nan
60
+ - Iou Flat-road: 0.0257
61
+ - Iou Flat-sidewalk: 0.0033
62
+ - Iou Flat-crosswalk: 0.0
63
+ - Iou Flat-cyclinglane: 0.0056
64
+ - Iou Flat-parkingdriveway: 0.0
65
+ - Iou Flat-railtrack: 0.0
66
+ - Iou Flat-curb: 0.0
67
+ - Iou Human-person: 0.0
68
+ - Iou Human-rider: 0.0
69
+ - Iou Vehicle-car: 0.0041
70
+ - Iou Vehicle-truck: 0.0
71
+ - Iou Vehicle-bus: nan
72
+ - Iou Vehicle-tramtrain: 0.0
73
+ - Iou Vehicle-motorcycle: 0.0
74
+ - Iou Vehicle-bicycle: 0.0
75
+ - Iou Vehicle-caravan: 0.0
76
+ - Iou Vehicle-cartrailer: 0.0
77
+ - Iou Construction-building: 0.0185
78
+ - Iou Construction-door: 0.0
79
+ - Iou Construction-wall: 0.0000
80
+ - Iou Construction-fenceguardrail: 0.0
81
+ - Iou Construction-bridge: nan
82
+ - Iou Construction-tunnel: 0.0
83
+ - Iou Construction-stairs: 0.0
84
+ - Iou Object-pole: 0.0
85
+ - Iou Object-trafficsign: 0.0
86
+ - Iou Object-trafficlight: 0.0
87
+ - Iou Nature-vegetation: 0.0263
88
+ - Iou Nature-terrain: 0.0000
89
+ - Iou Sky: 0.0
90
+ - Iou Void-ground: 0.0
91
+ - Iou Void-dynamic: 0.0
92
+ - Iou Void-static: 0.0
93
+ - Iou Void-unclear: nan
94
+
95
+ ## Model description
96
+
97
+ More information needed
98
+
99
+ ## Intended uses & limitations
100
+
101
+ More information needed
102
+
103
+ ## Training and evaluation data
104
+
105
+ More information needed
106
+
107
+ ## Training procedure
108
+
109
+ ### Training hyperparameters
110
+
111
+ The following hyperparameters were used during training:
112
+ - learning_rate: 6e-05
113
+ - train_batch_size: 2
114
+ - eval_batch_size: 2
115
+ - seed: 42
116
+ - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
117
+ - lr_scheduler_type: linear
118
+ - num_epochs: 1
119
+
120
+ ### Training results
121
+
122
+ | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Unlabeled | Accuracy Flat-road | Accuracy Flat-sidewalk | Accuracy Flat-crosswalk | Accuracy Flat-cyclinglane | Accuracy Flat-parkingdriveway | Accuracy Flat-railtrack | Accuracy Flat-curb | Accuracy Human-person | Accuracy Human-rider | Accuracy Vehicle-car | Accuracy Vehicle-truck | Accuracy Vehicle-bus | Accuracy Vehicle-tramtrain | Accuracy Vehicle-motorcycle | Accuracy Vehicle-bicycle | Accuracy Vehicle-caravan | Accuracy Vehicle-cartrailer | Accuracy Construction-building | Accuracy Construction-door | Accuracy Construction-wall | Accuracy Construction-fenceguardrail | Accuracy Construction-bridge | Accuracy Construction-tunnel | Accuracy Construction-stairs | Accuracy Object-pole | Accuracy Object-trafficsign | Accuracy Object-trafficlight | Accuracy Nature-vegetation | Accuracy Nature-terrain | Accuracy Sky | Accuracy Void-ground | Accuracy Void-dynamic | Accuracy Void-static | Accuracy Void-unclear | Iou Unlabeled | Iou Flat-road | Iou Flat-sidewalk | Iou Flat-crosswalk | Iou Flat-cyclinglane | Iou Flat-parkingdriveway | Iou Flat-railtrack | Iou Flat-curb | Iou Human-person | Iou Human-rider | Iou Vehicle-car | Iou Vehicle-truck | Iou Vehicle-bus | Iou Vehicle-tramtrain | Iou Vehicle-motorcycle | Iou Vehicle-bicycle | Iou Vehicle-caravan | Iou Vehicle-cartrailer | Iou Construction-building | Iou Construction-door | Iou Construction-wall | Iou Construction-fenceguardrail | Iou Construction-bridge | Iou Construction-tunnel | Iou Construction-stairs | Iou Object-pole | Iou Object-trafficsign | Iou Object-trafficlight | Iou Nature-vegetation | Iou Nature-terrain | Iou Sky | Iou Void-ground | Iou Void-dynamic | Iou Void-static | Iou Void-unclear |
123
+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:------------------:|:----------------------:|:-----------------------:|:-------------------------:|:-----------------------------:|:-----------------------:|:------------------:|:---------------------:|:--------------------:|:--------------------:|:----------------------:|:--------------------:|:--------------------------:|:---------------------------:|:------------------------:|:------------------------:|:---------------------------:|:------------------------------:|:--------------------------:|:--------------------------:|:------------------------------------:|:----------------------------:|:----------------------------:|:----------------------------:|:--------------------:|:---------------------------:|:----------------------------:|:--------------------------:|:-----------------------:|:------------:|:--------------------:|:---------------------:|:--------------------:|:---------------------:|:-------------:|:-------------:|:-----------------:|:------------------:|:--------------------:|:------------------------:|:------------------:|:-------------:|:----------------:|:---------------:|:---------------:|:-----------------:|:---------------:|:---------------------:|:----------------------:|:-------------------:|:-------------------:|:----------------------:|:-------------------------:|:---------------------:|:---------------------:|:-------------------------------:|:-----------------------:|:-----------------------:|:-----------------------:|:---------------:|:----------------------:|:-----------------------:|:---------------------:|:------------------:|:-------:|:---------------:|:----------------:|:---------------:|:----------------:|
124
+ | 1.7078 | 0.05 | 20 | 1.4727 | 0.0050 | 0.0648 | 0.0413 | nan | 0.0453 | 0.1637 | 0.0 | 0.0094 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.4761 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.8487 | 0.0 | 0.0000 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4009 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0407 | 0.0050 | 0.0 | 0.0046 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0043 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0198 | 0.0 | 0.0000 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0808 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan |
125
+ | 1.5621 | 0.1 | 40 | 1.2747 | 0.0039 | 0.0588 | 0.0334 | nan | 0.0395 | 0.1797 | 0.0 | 0.0037 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.3333 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9304 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2783 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0359 | 0.0054 | 0.0 | 0.0018 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0037 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0190 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0562 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan |
126
+ | 1.3203 | 0.15 | 60 | 1.2383 | 0.0046 | 0.0604 | 0.0393 | nan | 0.0453 | 0.1395 | 0.0 | 0.0080 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.3332 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9205 | 0.0 | 0.0000 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.3648 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0405 | 0.0044 | 0.0 | 0.0037 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0036 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0184 | 0.0 | 0.0000 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0731 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan |
127
+ | 1.2475 | 0.2 | 80 | 1.2265 | 0.0026 | 0.0549 | 0.0195 | nan | 0.0259 | 0.2398 | 0.0 | 0.0245 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.3967 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9003 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0595 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0237 | 0.0071 | 0.0 | 0.0109 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0043 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0207 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0134 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan |
128
+ | 1.5941 | 0.25 | 100 | 1.2210 | 0.0065 | 0.0632 | 0.0573 | nan | 0.0776 | 0.0279 | 0.0 | 0.0228 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.3200 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9444 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5040 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0680 | 0.0009 | 0.0 | 0.0098 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0038 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0186 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1008 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan |
129
+ | 0.9769 | 0.3 | 120 | 1.1445 | 0.0019 | 0.0531 | 0.0157 | nan | 0.0198 | 0.2436 | 0.0 | 0.0066 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.3249 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9607 | 0.0 | 0.0000 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0379 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0183 | 0.0071 | 0.0 | 0.0035 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0041 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0176 | 0.0 | 0.0000 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0087 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan |
130
+ | 1.2438 | 0.35 | 140 | 1.1050 | 0.0035 | 0.0583 | 0.0309 | nan | 0.0385 | 0.1843 | 0.0 | 0.0019 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.3802 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9115 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2319 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0347 | 0.0057 | 0.0 | 0.0010 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0044 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0194 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0441 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan |
131
+ | 2.0597 | 0.4 | 160 | 1.0509 | 0.0033 | 0.0572 | 0.0251 | nan | 0.0259 | 0.1654 | 0.0 | 0.0167 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.3968 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9070 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2050 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0236 | 0.0049 | 0.0 | 0.0075 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0043 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0197 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0421 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan |
132
+ | 1.2601 | 0.45 | 180 | 1.0366 | 0.0028 | 0.0544 | 0.0215 | nan | 0.0196 | 0.1423 | 0.0 | 0.0116 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.2936 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9778 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1861 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0180 | 0.0043 | 0.0 | 0.0052 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0039 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0189 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0377 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan |
133
+ | 1.4819 | 0.5 | 200 | 1.0306 | 0.0035 | 0.0544 | 0.0286 | nan | 0.0339 | 0.1112 | 0.0 | 0.0174 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.3395 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.8977 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2318 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0306 | 0.0035 | 0.0 | 0.0074 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0042 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0187 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0453 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan |
134
+ | 1.2691 | 0.55 | 220 | 1.0464 | 0.0034 | 0.0517 | 0.0315 | nan | 0.0573 | 0.0692 | 0.0 | 0.0141 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.3368 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9610 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1127 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0505 | 0.0023 | 0.0 | 0.0061 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0042 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0173 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0241 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan |
135
+ | 1.4964 | 0.6 | 240 | 0.9766 | 0.0022 | 0.0511 | 0.0149 | nan | 0.0170 | 0.1352 | 0.0 | 0.0352 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.3674 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9244 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0531 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0157 | 0.0041 | 0.0 | 0.0141 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0043 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0194 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0114 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan |
136
+ | 1.0495 | 0.65 | 260 | 0.9955 | 0.0029 | 0.0517 | 0.0220 | nan | 0.0205 | 0.1308 | 0.0 | 0.0165 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.3268 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.8596 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1960 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0188 | 0.0040 | 0.0 | 0.0070 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0039 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0186 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0385 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan |
137
+ | 1.01 | 0.7 | 280 | 0.9897 | 0.0027 | 0.0495 | 0.0237 | nan | 0.0425 | 0.0761 | 0.0 | 0.0124 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.3474 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9409 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0663 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0378 | 0.0024 | 0.0 | 0.0055 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0040 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0189 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0143 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan |
138
+ | 1.2455 | 0.75 | 300 | 0.9772 | 0.0027 | 0.0493 | 0.0229 | nan | 0.0365 | 0.0776 | 0.0 | 0.0194 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.2942 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9603 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0919 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0328 | 0.0025 | 0.0 | 0.0083 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0038 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0183 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0192 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan |
139
+ | 1.0037 | 0.8 | 320 | 0.9762 | 0.0033 | 0.0537 | 0.0256 | nan | 0.0277 | 0.0919 | 0.0 | 0.0161 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.2931 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9624 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2196 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0253 | 0.0029 | 0.0 | 0.0068 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0038 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0182 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0440 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan |
140
+ | 1.4191 | 0.85 | 340 | 0.9478 | 0.0028 | 0.0528 | 0.0219 | nan | 0.0246 | 0.1163 | 0.0 | 0.0140 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.3095 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9573 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1625 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0223 | 0.0036 | 0.0 | 0.0060 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0039 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0185 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0338 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan |
141
+ | 0.8844 | 0.9 | 360 | 0.9406 | 0.0029 | 0.0541 | 0.0223 | nan | 0.0246 | 0.1224 | 0.0 | 0.0151 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.3412 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9532 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1673 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0223 | 0.0038 | 0.0 | 0.0064 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0041 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0184 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0352 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan |
142
+ | 1.053 | 0.95 | 380 | 0.9542 | 0.0030 | 0.0527 | 0.0246 | nan | 0.0349 | 0.0897 | 0.0 | 0.0152 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.3554 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9432 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1426 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0312 | 0.0029 | 0.0 | 0.0065 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0042 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0189 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0295 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan |
143
+ | 2.2768 | 1.0 | 400 | 0.9393 | 0.0027 | 0.0525 | 0.0214 | nan | 0.0284 | 0.1051 | 0.0 | 0.0131 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.3571 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9472 | 0.0 | 0.0000 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1241 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan | nan | 0.0257 | 0.0033 | 0.0 | 0.0056 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0041 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0185 | 0.0 | 0.0000 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0263 | 0.0000 | 0.0 | 0.0 | 0.0 | 0.0 | nan |
144
+
145
+
146
+ ### Framework versions
147
+
148
+ - Transformers 4.48.0
149
+ - Pytorch 2.1.1+cu118
150
+ - Datasets 3.2.0
151
+ - Tokenizers 0.21.0
config.json ADDED
@@ -0,0 +1,144 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "_name_or_path": "nvidia/mit-b0",
3
+ "architectures": [
4
+ "SegformerForSemanticSegmentation"
5
+ ],
6
+ "attention_probs_dropout_prob": 0.0,
7
+ "classifier_dropout_prob": 0.1,
8
+ "decoder_hidden_size": 256,
9
+ "depths": [
10
+ 2,
11
+ 2,
12
+ 2,
13
+ 2
14
+ ],
15
+ "downsampling_rates": [
16
+ 1,
17
+ 4,
18
+ 8,
19
+ 16
20
+ ],
21
+ "drop_path_rate": 0.1,
22
+ "hidden_act": "gelu",
23
+ "hidden_dropout_prob": 0.0,
24
+ "hidden_sizes": [
25
+ 32,
26
+ 64,
27
+ 160,
28
+ 256
29
+ ],
30
+ "id2label": {
31
+ "0": "unlabeled",
32
+ "1": "flat-road",
33
+ "2": "flat-sidewalk",
34
+ "3": "flat-crosswalk",
35
+ "4": "flat-cyclinglane",
36
+ "5": "flat-parkingdriveway",
37
+ "6": "flat-railtrack",
38
+ "7": "flat-curb",
39
+ "8": "human-person",
40
+ "9": "human-rider",
41
+ "10": "vehicle-car",
42
+ "11": "vehicle-truck",
43
+ "12": "vehicle-bus",
44
+ "13": "vehicle-tramtrain",
45
+ "14": "vehicle-motorcycle",
46
+ "15": "vehicle-bicycle",
47
+ "16": "vehicle-caravan",
48
+ "17": "vehicle-cartrailer",
49
+ "18": "construction-building",
50
+ "19": "construction-door",
51
+ "20": "construction-wall",
52
+ "21": "construction-fenceguardrail",
53
+ "22": "construction-bridge",
54
+ "23": "construction-tunnel",
55
+ "24": "construction-stairs",
56
+ "25": "object-pole",
57
+ "26": "object-trafficsign",
58
+ "27": "object-trafficlight",
59
+ "28": "nature-vegetation",
60
+ "29": "nature-terrain",
61
+ "30": "sky",
62
+ "31": "void-ground",
63
+ "32": "void-dynamic",
64
+ "33": "void-static",
65
+ "34": "void-unclear"
66
+ },
67
+ "image_size": 224,
68
+ "initializer_range": 0.02,
69
+ "label2id": {
70
+ "construction-bridge": 22,
71
+ "construction-building": 18,
72
+ "construction-door": 19,
73
+ "construction-fenceguardrail": 21,
74
+ "construction-stairs": 24,
75
+ "construction-tunnel": 23,
76
+ "construction-wall": 20,
77
+ "flat-crosswalk": 3,
78
+ "flat-curb": 7,
79
+ "flat-cyclinglane": 4,
80
+ "flat-parkingdriveway": 5,
81
+ "flat-railtrack": 6,
82
+ "flat-road": 1,
83
+ "flat-sidewalk": 2,
84
+ "human-person": 8,
85
+ "human-rider": 9,
86
+ "nature-terrain": 29,
87
+ "nature-vegetation": 28,
88
+ "object-pole": 25,
89
+ "object-trafficlight": 27,
90
+ "object-trafficsign": 26,
91
+ "sky": 30,
92
+ "unlabeled": 0,
93
+ "vehicle-bicycle": 15,
94
+ "vehicle-bus": 12,
95
+ "vehicle-car": 10,
96
+ "vehicle-caravan": 16,
97
+ "vehicle-cartrailer": 17,
98
+ "vehicle-motorcycle": 14,
99
+ "vehicle-tramtrain": 13,
100
+ "vehicle-truck": 11,
101
+ "void-dynamic": 32,
102
+ "void-ground": 31,
103
+ "void-static": 33,
104
+ "void-unclear": 34
105
+ },
106
+ "layer_norm_eps": 1e-06,
107
+ "mlp_ratios": [
108
+ 4,
109
+ 4,
110
+ 4,
111
+ 4
112
+ ],
113
+ "model_type": "segformer",
114
+ "num_attention_heads": [
115
+ 1,
116
+ 2,
117
+ 5,
118
+ 8
119
+ ],
120
+ "num_channels": 3,
121
+ "num_encoder_blocks": 4,
122
+ "patch_sizes": [
123
+ 7,
124
+ 3,
125
+ 3,
126
+ 3
127
+ ],
128
+ "reshape_last_stage": true,
129
+ "semantic_loss_ignore_index": 255,
130
+ "sr_ratios": [
131
+ 8,
132
+ 4,
133
+ 2,
134
+ 1
135
+ ],
136
+ "strides": [
137
+ 4,
138
+ 2,
139
+ 2,
140
+ 2
141
+ ],
142
+ "torch_dtype": "float32",
143
+ "transformers_version": "4.48.0"
144
+ }
model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:176f0c6707f35a57b40bb891e5931cd37af2f24a64e7e21494eef480754c35a9
3
+ size 14918708
preprocessor_config.json ADDED
@@ -0,0 +1,23 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "do_normalize": true,
3
+ "do_reduce_labels": false,
4
+ "do_rescale": true,
5
+ "do_resize": true,
6
+ "image_mean": [
7
+ 0.485,
8
+ 0.456,
9
+ 0.406
10
+ ],
11
+ "image_processor_type": "SegformerFeatureExtractor",
12
+ "image_std": [
13
+ 0.229,
14
+ 0.224,
15
+ 0.225
16
+ ],
17
+ "resample": 2,
18
+ "rescale_factor": 0.00392156862745098,
19
+ "size": {
20
+ "height": 512,
21
+ "width": 512
22
+ }
23
+ }
runs/Jan20_06-21-09_jupyter-admin01/events.out.tfevents.1737354101.jupyter-admin01.177.0 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d3d3169cbc27f97293b89ebbdc7a4819d724c6c84ac5cb56140d26d6a44eb5d8
3
+ size 11604
runs/Jan20_06-21-09_jupyter-admin01/events.out.tfevents.1737355214.jupyter-admin01.177.1 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:5f33d73dffc3177c9a9fb616200c8adc7a224c3f56d3932ea00cde943150f7ca
3
+ size 47848
runs/Jan20_06-45-05_jupyter-admin01/events.out.tfevents.1737355516.jupyter-admin01.177.2 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:657875b8af6f3f462f795bdbb1471e27dfbd359dcad04588d10f84f708f4b362
3
+ size 191182
training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:181cebe210cd87415ab77ae759f029cfa5a0b64865fab706581f051a5138231c
3
+ size 5432