Hugging Face's logo

sungile
/
custom-object-test7

Image Segmentation
Transformers
Safetensors
segformer
vision
Generated from Trainer
Inference Endpoints
Model card Files Community
sungile commited on
Commit
953122c
·
verified ·
1 Parent(s): 55faff4

End of training

Browse files
Files changed (4) hide show
  1. README.md +59 -15
  2. config.json +1 -1
  3. model.safetensors +1 -1
  4. training_args.bin +1 -1
README.md CHANGED
@@ -18,15 +18,15 @@ should probably proofread and complete it, then remove this comment. -->
18
 
19
  This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the sungile/custom-object-masking5 dataset.
20
  It achieves the following results on the evaluation set:
21
- - Loss: 0.0051
22
- - Mean Iou: 0.0
23
- - Mean Accuracy: nan
24
- - Overall Accuracy: nan
25
  - Accuracy Unknown: nan
26
- - Accuracy Background: nan
27
  - Accuracy Object: nan
28
  - Iou Unknown: 0.0
29
- - Iou Background: nan
30
  - Iou Object: nan
31
 
32
  ## Model description
@@ -52,20 +52,64 @@ The following hyperparameters were used during training:
52
  - seed: 42
53
  - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
54
  - lr_scheduler_type: linear
55
- - num_epochs: 2
56
 
57
  ### Training results
58
 
59
  | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Unknown | Accuracy Background | Accuracy Object | Iou Unknown | Iou Background | Iou Object |
60
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:----------------:|:-------------------:|:---------------:|:-----------:|:--------------:|:----------:|
61
- | 0.012 | 0.25 | 20 | 0.0095 | 0.0 | nan | nan | nan | nan | nan | 0.0 | nan | nan |
62
- | 0.0105 | 0.5 | 40 | 0.0080 | 0.0 | nan | nan | nan | nan | nan | 0.0 | nan | nan |
63
- | 0.0075 | 0.75 | 60 | 0.0075 | 0.0 | nan | nan | nan | nan | nan | 0.0 | nan | nan |
64
- | 0.0068 | 1.0 | 80 | 0.0059 | 0.0 | nan | nan | nan | nan | nan | 0.0 | nan | nan |
65
- | 0.0064 | 1.25 | 100 | 0.0057 | 0.0 | nan | nan | nan | nan | nan | 0.0 | nan | nan |
66
- | 0.0057 | 1.5 | 120 | 0.0054 | 0.0 | nan | nan | nan | nan | nan | 0.0 | nan | nan |
67
- | 0.0053 | 1.75 | 140 | 0.0052 | 0.0 | nan | nan | nan | nan | nan | 0.0 | nan | nan |
68
- | 0.0055 | 2.0 | 160 | 0.0051 | 0.0 | nan | nan | nan | nan | nan | 0.0 | nan | nan |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
69
 
70
 
71
  ### Framework versions
 
18
 
19
  This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the sungile/custom-object-masking5 dataset.
20
  It achieves the following results on the evaluation set:
21
+ - Loss: 0.1507
22
+ - Mean Iou: 0.3557
23
+ - Mean Accuracy: 0.7113
24
+ - Overall Accuracy: 0.7113
25
  - Accuracy Unknown: nan
26
+ - Accuracy Background: 0.7113
27
  - Accuracy Object: nan
28
  - Iou Unknown: 0.0
29
+ - Iou Background: 0.7113
30
  - Iou Object: nan
31
 
32
  ## Model description
 
52
  - seed: 42
53
  - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
54
  - lr_scheduler_type: linear
55
+ - num_epochs: 13
56
 
57
  ### Training results
58
 
59
  | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Unknown | Accuracy Background | Accuracy Object | Iou Unknown | Iou Background | Iou Object |
60
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:----------------:|:-------------------:|:---------------:|:-----------:|:--------------:|:----------:|
61
+ | 0.7249 | 0.25 | 20 | 0.9434 | 0.2871 | 0.8614 | 0.8614 | nan | 0.8614 | nan | 0.0 | 0.8614 | 0.0 |
62
+ | 0.7121 | 0.5 | 40 | 0.6610 | 0.3810 | 0.7620 | 0.7620 | nan | 0.7620 | nan | 0.0 | 0.7620 | nan |
63
+ | 0.4732 | 0.75 | 60 | 0.5195 | 0.3888 | 0.7775 | 0.7775 | nan | 0.7775 | nan | 0.0 | 0.7775 | nan |
64
+ | 0.5129 | 1.0 | 80 | 0.4134 | 0.2955 | 0.5910 | 0.5910 | nan | 0.5910 | nan | 0.0 | 0.5910 | nan |
65
+ | 0.4451 | 1.25 | 100 | 0.3473 | 0.2485 | 0.4971 | 0.4971 | nan | 0.4971 | nan | 0.0 | 0.4971 | nan |
66
+ | 0.4109 | 1.5 | 120 | 0.3279 | 0.2516 | 0.5033 | 0.5033 | nan | 0.5033 | nan | 0.0 | 0.5033 | nan |
67
+ | 0.3659 | 1.75 | 140 | 0.3014 | 0.2695 | 0.5391 | 0.5391 | nan | 0.5391 | nan | 0.0 | 0.5391 | nan |
68
+ | 0.2206 | 2.0 | 160 | 0.2773 | 0.2581 | 0.5163 | 0.5163 | nan | 0.5163 | nan | 0.0 | 0.5163 | nan |
69
+ | 0.2452 | 2.25 | 180 | 0.2575 | 0.2982 | 0.5964 | 0.5964 | nan | 0.5964 | nan | 0.0 | 0.5964 | nan |
70
+ | 0.2496 | 2.5 | 200 | 0.2523 | 0.3345 | 0.6690 | 0.6690 | nan | 0.6690 | nan | 0.0 | 0.6690 | nan |
71
+ | 0.1633 | 2.75 | 220 | 0.3160 | 0.4074 | 0.8149 | 0.8149 | nan | 0.8149 | nan | 0.0 | 0.8149 | nan |
72
+ | 0.1426 | 3.0 | 240 | 0.2242 | 0.3451 | 0.6903 | 0.6903 | nan | 0.6903 | nan | 0.0 | 0.6903 | nan |
73
+ | 0.1363 | 3.25 | 260 | 0.2225 | 0.3505 | 0.7010 | 0.7010 | nan | 0.7010 | nan | 0.0 | 0.7010 | nan |
74
+ | 0.1337 | 3.5 | 280 | 0.2229 | 0.3799 | 0.7599 | 0.7599 | nan | 0.7599 | nan | 0.0 | 0.7599 | nan |
75
+ | 0.1611 | 3.75 | 300 | 0.1971 | 0.3535 | 0.7070 | 0.7070 | nan | 0.7070 | nan | 0.0 | 0.7070 | nan |
76
+ | 0.1376 | 4.0 | 320 | 0.1835 | 0.3504 | 0.7007 | 0.7007 | nan | 0.7007 | nan | 0.0 | 0.7007 | nan |
77
+ | 0.1367 | 4.25 | 340 | 0.1735 | 0.3226 | 0.6453 | 0.6453 | nan | 0.6453 | nan | 0.0 | 0.6453 | nan |
78
+ | 0.1452 | 4.5 | 360 | 0.1689 | 0.3096 | 0.6192 | 0.6192 | nan | 0.6192 | nan | 0.0 | 0.6192 | nan |
79
+ | 0.1323 | 4.75 | 380 | 0.1741 | 0.3343 | 0.6685 | 0.6685 | nan | 0.6685 | nan | 0.0 | 0.6685 | nan |
80
+ | 0.1519 | 5.0 | 400 | 0.1647 | 0.3433 | 0.6866 | 0.6866 | nan | 0.6866 | nan | 0.0 | 0.6866 | nan |
81
+ | 0.1013 | 5.25 | 420 | 0.1645 | 0.3575 | 0.7149 | 0.7149 | nan | 0.7149 | nan | 0.0 | 0.7149 | nan |
82
+ | 0.0967 | 5.5 | 440 | 0.1645 | 0.3620 | 0.7241 | 0.7241 | nan | 0.7241 | nan | 0.0 | 0.7241 | nan |
83
+ | 0.1306 | 5.75 | 460 | 0.1646 | 0.3262 | 0.6523 | 0.6523 | nan | 0.6523 | nan | 0.0 | 0.6523 | nan |
84
+ | 0.2066 | 6.0 | 480 | 0.1600 | 0.3326 | 0.6651 | 0.6651 | nan | 0.6651 | nan | 0.0 | 0.6651 | nan |
85
+ | 0.0671 | 6.25 | 500 | 0.1546 | 0.3433 | 0.6867 | 0.6867 | nan | 0.6867 | nan | 0.0 | 0.6867 | nan |
86
+ | 0.0644 | 6.5 | 520 | 0.1612 | 0.3284 | 0.6568 | 0.6568 | nan | 0.6568 | nan | 0.0 | 0.6568 | nan |
87
+ | 0.0518 | 6.75 | 540 | 0.1575 | 0.3633 | 0.7266 | 0.7266 | nan | 0.7266 | nan | 0.0 | 0.7266 | nan |
88
+ | 0.086 | 7.0 | 560 | 0.1535 | 0.3490 | 0.6980 | 0.6980 | nan | 0.6980 | nan | 0.0 | 0.6980 | nan |
89
+ | 0.0602 | 7.25 | 580 | 0.1624 | 0.2988 | 0.5976 | 0.5976 | nan | 0.5976 | nan | 0.0 | 0.5976 | nan |
90
+ | 0.1332 | 7.5 | 600 | 0.1530 | 0.3532 | 0.7063 | 0.7063 | nan | 0.7063 | nan | 0.0 | 0.7063 | nan |
91
+ | 0.0494 | 7.75 | 620 | 0.1461 | 0.3732 | 0.7465 | 0.7465 | nan | 0.7465 | nan | 0.0 | 0.7465 | nan |
92
+ | 0.0685 | 8.0 | 640 | 0.1554 | 0.3198 | 0.6396 | 0.6396 | nan | 0.6396 | nan | 0.0 | 0.6396 | nan |
93
+ | 0.0492 | 8.25 | 660 | 0.1484 | 0.3563 | 0.7125 | 0.7125 | nan | 0.7125 | nan | 0.0 | 0.7125 | nan |
94
+ | 0.0525 | 8.5 | 680 | 0.1485 | 0.3341 | 0.6681 | 0.6681 | nan | 0.6681 | nan | 0.0 | 0.6681 | nan |
95
+ | 0.0911 | 8.75 | 700 | 0.1553 | 0.3257 | 0.6515 | 0.6515 | nan | 0.6515 | nan | 0.0 | 0.6515 | nan |
96
+ | 0.0493 | 9.0 | 720 | 0.1481 | 0.3598 | 0.7197 | 0.7197 | nan | 0.7197 | nan | 0.0 | 0.7197 | nan |
97
+ | 0.0445 | 9.25 | 740 | 0.1540 | 0.3536 | 0.7073 | 0.7073 | nan | 0.7073 | nan | 0.0 | 0.7073 | nan |
98
+ | 0.0723 | 9.5 | 760 | 0.1481 | 0.3461 | 0.6921 | 0.6921 | nan | 0.6921 | nan | 0.0 | 0.6921 | nan |
99
+ | 0.047 | 9.75 | 780 | 0.1479 | 0.3495 | 0.6990 | 0.6990 | nan | 0.6990 | nan | 0.0 | 0.6990 | nan |
100
+ | 0.0703 | 10.0 | 800 | 0.1489 | 0.3553 | 0.7106 | 0.7106 | nan | 0.7106 | nan | 0.0 | 0.7106 | nan |
101
+ | 0.0532 | 10.25 | 820 | 0.1475 | 0.3635 | 0.7270 | 0.7270 | nan | 0.7270 | nan | 0.0 | 0.7270 | nan |
102
+ | 0.0407 | 10.5 | 840 | 0.1481 | 0.3540 | 0.7079 | 0.7079 | nan | 0.7079 | nan | 0.0 | 0.7079 | nan |
103
+ | 0.0395 | 10.75 | 860 | 0.1545 | 0.3430 | 0.6861 | 0.6861 | nan | 0.6861 | nan | 0.0 | 0.6861 | nan |
104
+ | 0.1379 | 11.0 | 880 | 0.1531 | 0.3427 | 0.6854 | 0.6854 | nan | 0.6854 | nan | 0.0 | 0.6854 | nan |
105
+ | 0.0281 | 11.25 | 900 | 0.1483 | 0.3466 | 0.6932 | 0.6932 | nan | 0.6932 | nan | 0.0 | 0.6932 | nan |
106
+ | 0.0361 | 11.5 | 920 | 0.1560 | 0.3424 | 0.6848 | 0.6848 | nan | 0.6848 | nan | 0.0 | 0.6848 | nan |
107
+ | 0.0422 | 11.75 | 940 | 0.1494 | 0.3576 | 0.7152 | 0.7152 | nan | 0.7152 | nan | 0.0 | 0.7152 | nan |
108
+ | 0.0541 | 12.0 | 960 | 0.1502 | 0.3552 | 0.7105 | 0.7105 | nan | 0.7105 | nan | 0.0 | 0.7105 | nan |
109
+ | 0.0568 | 12.25 | 980 | 0.1549 | 0.3442 | 0.6885 | 0.6885 | nan | 0.6885 | nan | 0.0 | 0.6885 | nan |
110
+ | 0.0881 | 12.5 | 1000 | 0.1516 | 0.3481 | 0.6963 | 0.6963 | nan | 0.6963 | nan | 0.0 | 0.6963 | nan |
111
+ | 0.0478 | 12.75 | 1020 | 0.1527 | 0.3524 | 0.7047 | 0.7047 | nan | 0.7047 | nan | 0.0 | 0.7047 | nan |
112
+ | 0.0529 | 13.0 | 1040 | 0.1507 | 0.3557 | 0.7113 | 0.7113 | nan | 0.7113 | nan | 0.0 | 0.7113 | nan |
113
 
114
 
115
  ### Framework versions
config.json CHANGED
@@ -1,5 +1,5 @@
1
  {
2
- "_name_or_path": "sungile/custom-object-test6",
3
  "architectures": [
4
  "SegformerForSemanticSegmentation"
5
  ],
 
1
  {
2
+ "_name_or_path": "nvidia/mit-b0",
3
  "architectures": [
4
  "SegformerForSemanticSegmentation"
5
  ],
model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:a48629d086b06f320eee3c4f0e13383a71515fcc7fca8020e9e1a31c55998ad0
3
  size 14885804
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:293fe5bbbe4a533e30194c89419c142259fb8c3e638f1c606f3880bd6a8b47d8
3
  size 14885804
training_args.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:639badd1326ed9bee13cad53eaefec660e51f6bf674c2bd36d7e10cbf95e2736
3
  size 5304
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c8290f5abef5cbb2c08fd6a5cd14b39238620b2e4dd974c0bc5fb1128316464b
3
  size 5304