Hugging Face's logo

mdeputy
/
windowz_test-020625

Transformers
Safetensors
Unet
Generated from Trainer
Inference Endpoints
Model card Files Community
mdeputy commited on
Commit
281ba8d
·
verified ·
1 Parent(s): 080e26b

best_model.pt

Browse files
Files changed (3) hide show
  1. README.md +20 -25
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -18,12 +18,12 @@ should probably proofread and complete it, then remove this comment. -->
18
  This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
19
  It achieves the following results on the evaluation set:
20
  - Model Preparation Time: 0.001
21
- - Accuracy: 0.9521
22
- - F1: 0.9483
23
- - Iou: 0.9076
24
- - Contour Dice: 0.9035
25
- - Per Class Metrics: {0: {'f1': 0.97101, 'iou': 0.94365, 'accuracy': 0.95541, 'contour_dice': 0.97101}, 1: {'f1': 0.90428, 'iou': 0.82528, 'accuracy': 0.95685, 'contour_dice': 0.90428}, 2: {'f1': 0.27674, 'iou': 0.16059, 'accuracy': 0.99191, 'contour_dice': 0.27674}}
26
- - Loss: 0.4842
27
 
28
  ## Model description
29
 
@@ -55,25 +55,20 @@ The following hyperparameters were used during training:
55
 
56
  | Training Loss | Epoch | Step | Model Preparation Time | | Dice | Class Metrics | Validation Loss |
57
  |:-------------:|:------:|:----:|:----------------------:|:------:|:------:|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:---------------:|
58
- | 1.3502 | 0.0501 | 257 | 0.001 | 0.5644 | 0.0674 | {0: {'f1': 0.85985, 'iou': 0.75416, 'accuracy': 0.75632, 'contour_dice': 0.85985}, 1: {'f1': 3e-05, 'iou': 2e-05, 'accuracy': 0.75751, 'contour_dice': 3e-05}, 2: {'f1': 0.03477, 'iou': 0.01769, 'accuracy': 0.98186, 'contour_dice': 0.03477}} | 1.0501 |
59
- | 1.2779 | 0.1003 | 514 | 0.001 | 0.5614 | 0.0110 | {0: {'f1': 0.85654, 'iou': 0.74908, 'accuracy': 0.74943, 'contour_dice': 0.85654}, 1: {'f1': 0.0, 'iou': 0.0, 'accuracy': 0.7575, 'contour_dice': 0.0}, 2: {'f1': 0.18607, 'iou': 0.10258, 'accuracy': 0.99115, 'contour_dice': 0.18607}} | 0.9869 |
60
- | 1.2058 | 0.1504 | 771 | 0.001 | 0.5601 | 0.0024 | {0: {'f1': 0.85601, 'iou': 0.74826, 'accuracy': 0.74834, 'contour_dice': 0.85601}, 1: {'f1': 0.00043, 'iou': 0.00021, 'accuracy': 0.75755, 'contour_dice': 0.00043}, 2: {'f1': 0.04908, 'iou': 0.02516, 'accuracy': 0.99076, 'contour_dice': 0.04908}} | 0.9181 |
61
- | 1.1158 | 0.2005 | 1028 | 0.001 | 0.5610 | 0.0074 | {0: {'f1': 0.85634, 'iou': 0.74877, 'accuracy': 0.74901, 'contour_dice': 0.85634}, 1: {'f1': 0.00103, 'iou': 0.00052, 'accuracy': 0.75763, 'contour_dice': 0.00103}, 2: {'f1': 0.14378, 'iou': 0.07746, 'accuracy': 0.99122, 'contour_dice': 0.14378}} | 0.8743 |
62
- | 1.0785 | 0.2507 | 1285 | 0.001 | 0.5614 | 0.0087 | {0: {'f1': 0.85643, 'iou': 0.74892, 'accuracy': 0.74919, 'contour_dice': 0.85643}, 1: {'f1': 0.00618, 'iou': 0.0031, 'accuracy': 0.75825, 'contour_dice': 0.00618}, 2: {'f1': 0.07155, 'iou': 0.0371, 'accuracy': 0.99093, 'contour_dice': 0.07155}} | 0.8316 |
63
- | 1.0445 | 0.3008 | 1542 | 0.001 | 0.7385 | 0.6122 | {0: {'f1': 0.9132, 'iou': 0.84027, 'accuracy': 0.85815, 'contour_dice': 0.9132}, 1: {'f1': 0.619, 'iou': 0.44823, 'accuracy': 0.8647, 'contour_dice': 0.619}, 2: {'f1': 0.22291, 'iou': 0.12543, 'accuracy': 0.99173, 'contour_dice': 0.22291}} | 0.7703 |
64
- | 1.0092 | 0.3510 | 1799 | 0.001 | 0.7510 | 0.6389 | {0: {'f1': 0.91749, 'iou': 0.84755, 'accuracy': 0.86567, 'contour_dice': 0.91749}, 1: {'f1': 0.64415, 'iou': 0.47509, 'accuracy': 0.87163, 'contour_dice': 0.64415}, 2: {'f1': 0.31734, 'iou': 0.18859, 'accuracy': 0.99231, 'contour_dice': 0.31734}} | 0.7823 |
65
- | 0.9676 | 0.4011 | 2056 | 0.001 | 0.7371 | 0.6147 | {0: {'f1': 0.91344, 'iou': 0.84066, 'accuracy': 0.85863, 'contour_dice': 0.91344}, 1: {'f1': 0.60393, 'iou': 0.43259, 'accuracy': 0.86089, 'contour_dice': 0.60393}, 2: {'f1': 0.52376, 'iou': 0.3548, 'accuracy': 0.99253, 'contour_dice': 0.52376}} | 0.8004 |
66
- | 0.9308 | 0.4512 | 2313 | 0.001 | 0.8564 | 0.8337 | {0: {'f1': 0.95377, 'iou': 0.91162, 'accuracy': 0.92764, 'contour_dice': 0.95377}, 1: {'f1': 0.83301, 'iou': 0.71381, 'accuracy': 0.9292, 'contour_dice': 0.83301}, 2: {'f1': 0.25373, 'iou': 0.1453, 'accuracy': 0.9918, 'contour_dice': 0.25373}} | 0.7535 |
67
- | 0.9187 | 0.5014 | 2570 | 0.001 | 0.868 | 0.8442 | {0: {'f1': 0.95642, 'iou': 0.91649, 'accuracy': 0.93189, 'contour_dice': 0.95642}, 1: {'f1': 0.8514, 'iou': 0.74124, 'accuracy': 0.93689, 'contour_dice': 0.8514}, 2: {'f1': 0.43757, 'iou': 0.28006, 'accuracy': 0.99306, 'contour_dice': 0.43757}} | 0.7077 |
68
- | 0.8916 | 0.5515 | 2827 | 0.001 | 0.8656 | 0.8447 | {0: {'f1': 0.95636, 'iou': 0.91636, 'accuracy': 0.93186, 'contour_dice': 0.95636}, 1: {'f1': 0.84316, 'iou': 0.72885, 'accuracy': 0.93331, 'contour_dice': 0.84316}, 2: {'f1': 0.5173, 'iou': 0.34889, 'accuracy': 0.9935, 'contour_dice': 0.5173}} | 0.6670 |
69
- | 0.8723 | 0.6016 | 3084 | 0.001 | 0.9221 | 0.9210 | {0: {'f1': 0.97564, 'iou': 0.95244, 'accuracy': 0.96276, 'contour_dice': 0.97564}, 1: {'f1': 0.92036, 'iou': 0.85247, 'accuracy': 0.9635, 'contour_dice': 0.92036}, 2: {'f1': 0.46566, 'iou': 0.30349, 'accuracy': 0.99314, 'contour_dice': 0.46566}} | 0.6549 |
70
- | 0.8761 | 0.6518 | 3341 | 0.001 | 0.7678 | 0.7651 | {0: {'f1': 0.90349, 'iou': 0.82397, 'accuracy': 0.86319, 'contour_dice': 0.90349}, 1: {'f1': 0.76222, 'iou': 0.6158, 'accuracy': 0.86427, 'contour_dice': 0.76222}, 2: {'f1': 0.35206, 'iou': 0.21364, 'accuracy': 0.99248, 'contour_dice': 0.35206}} | 0.7303 |
71
- | 0.869 | 0.7019 | 3598 | 0.001 | 0.9259 | 0.9263 | {0: {'f1': 0.97721, 'iou': 0.95544, 'accuracy': 0.96519, 'contour_dice': 0.97721}, 1: {'f1': 0.92398, 'iou': 0.85871, 'accuracy': 0.96506, 'contour_dice': 0.92398}, 2: {'f1': 0.47308, 'iou': 0.30983, 'accuracy': 0.99326, 'contour_dice': 0.47308}} | 0.6818 |
72
- | 0.8526 | 0.7520 | 3855 | 0.001 | 0.9455 | 0.9507 | {0: {'f1': 0.98427, 'iou': 0.96902, 'accuracy': 0.97615, 'contour_dice': 0.98427}, 1: {'f1': 0.94744, 'iou': 0.90013, 'accuracy': 0.97519, 'contour_dice': 0.94744}, 2: {'f1': 0.38871, 'iou': 0.24124, 'accuracy': 0.99266, 'contour_dice': 0.38871}} | 0.5164 |
73
- | 0.8487 | 0.8022 | 4112 | 0.001 | 0.8958 | 0.8869 | {0: {'f1': 0.96679, 'iou': 0.93572, 'accuracy': 0.94866, 'contour_dice': 0.96679}, 1: {'f1': 0.88802, 'iou': 0.7986, 'accuracy': 0.95052, 'contour_dice': 0.88802}, 2: {'f1': 0.36537, 'iou': 0.22352, 'accuracy': 0.99239, 'contour_dice': 0.36537}} | 0.5553 |
74
- | 0.8519 | 0.8523 | 4369 | 0.001 | 0.9236 | 0.9231 | {0: {'f1': 0.97639, 'iou': 0.95387, 'accuracy': 0.96388, 'contour_dice': 0.97639}, 1: {'f1': 0.92437, 'iou': 0.85937, 'accuracy': 0.9653, 'contour_dice': 0.92437}, 2: {'f1': 0.29738, 'iou': 0.17466, 'accuracy': 0.99214, 'contour_dice': 0.29738}} | 0.4860 |
75
- | 0.8331 | 0.9025 | 4626 | 0.001 | 0.9076 | 0.9035 | {0: {'f1': 0.97101, 'iou': 0.94365, 'accuracy': 0.95541, 'contour_dice': 0.97101}, 1: {'f1': 0.90428, 'iou': 0.82528, 'accuracy': 0.95685, 'contour_dice': 0.90428}, 2: {'f1': 0.27674, 'iou': 0.16059, 'accuracy': 0.99191, 'contour_dice': 0.27674}} | 0.4842 |
76
- | 0.8357 | 0.9526 | 4883 | 0.001 | 0.8881 | 0.8770 | {0: {'f1': 0.96409, 'iou': 0.93067, 'accuracy': 0.94441, 'contour_dice': 0.96409}, 1: {'f1': 0.87736, 'iou': 0.78151, 'accuracy': 0.94613, 'contour_dice': 0.87736}, 2: {'f1': 0.40324, 'iou': 0.25254, 'accuracy': 0.99246, 'contour_dice': 0.40324}} | 0.5096 |
77
 
78
 
79
  ### Framework versions
 
18
  This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
19
  It achieves the following results on the evaluation set:
20
  - Model Preparation Time: 0.001
21
+ - Accuracy: 0.9796
22
+ - F1: 0.9749
23
+ - Iou: 0.9601
24
+ - Contour Dice: 0.9763
25
+ - Per Class Metrics: {0: {'f1': 0.99218, 'iou': 0.98448, 'accuracy': 0.98824, 'contour_dice': 0.99218}, 1: {'f1': 0.95952, 'iou': 0.92218, 'accuracy': 0.98031, 'contour_dice': 0.95952}, 2: {'f1': 0.00151, 'iou': 0.00075, 'accuracy': 0.9906, 'contour_dice': 0.00151}}
26
+ - Loss: 0.2439
27
 
28
  ## Model description
29
 
 
55
 
56
  | Training Loss | Epoch | Step | Model Preparation Time | | Dice | Class Metrics | Validation Loss |
57
  |:-------------:|:------:|:----:|:----------------------:|:------:|:------:|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:---------------:|
58
+ | 1.1036 | 0.0501 | 257 | 0.001 | 0.5982 | 0.2778 | {0: {'f1': 0.86413, 'iou': 0.76077, 'accuracy': 0.77129, 'contour_dice': 0.86413}, 1: {'f1': 0.21374, 'iou': 0.11966, 'accuracy': 0.76928, 'contour_dice': 0.21374}, 2: {'f1': 0.01912, 'iou': 0.00965, 'accuracy': 0.97722, 'contour_dice': 0.01912}} | 1.0658 |
59
+ | 1.0397 | 0.1003 | 514 | 0.001 | 0.6281 | 0.3228 | {0: {'f1': 0.87827, 'iou': 0.78297, 'accuracy': 0.79364, 'contour_dice': 0.87827}, 1: {'f1': 0.29681, 'iou': 0.17426, 'accuracy': 0.79658, 'contour_dice': 0.29681}, 2: {'f1': 0.02455, 'iou': 0.01243, 'accuracy': 0.98492, 'contour_dice': 0.02455}} | 0.8951 |
60
+ | 0.9914 | 0.1504 | 771 | 0.001 | 0.6255 | 0.3002 | {0: {'f1': 0.87683, 'iou': 0.78067, 'accuracy': 0.79052, 'contour_dice': 0.87683}, 1: {'f1': 0.29198, 'iou': 0.17095, 'accuracy': 0.79672, 'contour_dice': 0.29198}, 2: {'f1': 0.00531, 'iou': 0.00266, 'accuracy': 0.98785, 'contour_dice': 0.00531}} | 1.0984 |
61
+ | 0.9099 | 0.2005 | 1028 | 0.001 | 0.6361 | 0.3306 | {0: {'f1': 0.87929, 'iou': 0.78459, 'accuracy': 0.79547, 'contour_dice': 0.87929}, 1: {'f1': 0.33695, 'iou': 0.20261, 'accuracy': 0.80371, 'contour_dice': 0.33695}, 2: {'f1': 0.00299, 'iou': 0.0015, 'accuracy': 0.9905, 'contour_dice': 0.00299}} | 0.8636 |
62
+ | 0.8914 | 0.2507 | 1285 | 0.001 | 0.8276 | 0.7951 | {0: {'f1': 0.945, 'iou': 0.89573, 'accuracy': 0.91327, 'contour_dice': 0.945}, 1: {'f1': 0.78751, 'iou': 0.6495, 'accuracy': 0.9121, 'contour_dice': 0.78751}, 2: {'f1': 0.00757, 'iou': 0.0038, 'accuracy': 0.99051, 'contour_dice': 0.00757}} | 0.5194 |
63
+ | 0.8394 | 0.3008 | 1542 | 0.001 | 0.8440 | 0.8288 | {0: {'f1': 0.94952, 'iou': 0.9039, 'accuracy': 0.92204, 'contour_dice': 0.94952}, 1: {'f1': 0.81787, 'iou': 0.69186, 'accuracy': 0.9188, 'contour_dice': 0.81787}, 2: {'f1': 0.01225, 'iou': 0.00616, 'accuracy': 0.99049, 'contour_dice': 0.01225}} | 0.4643 |
64
+ | 0.8066 | 0.3510 | 1799 | 0.001 | 0.8633 | 0.8558 | {0: {'f1': 0.95845, 'iou': 0.92021, 'accuracy': 0.93548, 'contour_dice': 0.95845}, 1: {'f1': 0.83803, 'iou': 0.72121, 'accuracy': 0.92909, 'contour_dice': 0.83803}, 2: {'f1': 0.00216, 'iou': 0.00108, 'accuracy': 0.99053, 'contour_dice': 0.00216}} | 0.4510 |
65
+ | 0.7995 | 0.4011 | 2056 | 0.001 | 0.8625 | 0.8540 | {0: {'f1': 0.95811, 'iou': 0.91959, 'accuracy': 0.9349, 'contour_dice': 0.95811}, 1: {'f1': 0.83706, 'iou': 0.71978, 'accuracy': 0.92889, 'contour_dice': 0.83706}, 2: {'f1': 0.00225, 'iou': 0.00113, 'accuracy': 0.99056, 'contour_dice': 0.00225}} | 0.3804 |
66
+ | 0.7606 | 0.4512 | 2313 | 0.001 | 0.8932 | 0.8965 | {0: {'f1': 0.96927, 'iou': 0.94038, 'accuracy': 0.95262, 'contour_dice': 0.96927}, 1: {'f1': 0.87794, 'iou': 0.78243, 'accuracy': 0.94526, 'contour_dice': 0.87794}, 2: {'f1': 0.00084, 'iou': 0.00042, 'accuracy': 0.99059, 'contour_dice': 0.00084}} | 0.3936 |
67
+ | 0.7392 | 0.5014 | 2570 | 0.001 | 0.9602 | 0.9777 | {0: {'f1': 0.99254, 'iou': 0.9852, 'accuracy': 0.98882, 'contour_dice': 0.99254}, 1: {'f1': 0.9586, 'iou': 0.92049, 'accuracy': 0.97966, 'contour_dice': 0.9586}, 2: {'f1': 7e-05, 'iou': 3e-05, 'accuracy': 0.99059, 'contour_dice': 7e-05}} | 0.3214 |
68
+ | 0.7435 | 0.5515 | 2827 | 0.001 | 0.9601 | 0.9763 | {0: {'f1': 0.99218, 'iou': 0.98448, 'accuracy': 0.98824, 'contour_dice': 0.99218}, 1: {'f1': 0.95952, 'iou': 0.92218, 'accuracy': 0.98031, 'contour_dice': 0.95952}, 2: {'f1': 0.00151, 'iou': 0.00075, 'accuracy': 0.9906, 'contour_dice': 0.00151}} | 0.2439 |
69
+ | 0.7194 | 0.6016 | 3084 | 0.001 | 0.8241 | 0.7995 | {0: {'f1': 0.94141, 'iou': 0.8893, 'accuracy': 0.90932, 'contour_dice': 0.94141}, 1: {'f1': 0.79144, 'iou': 0.65487, 'accuracy': 0.90763, 'contour_dice': 0.79144}, 2: {'f1': 0.00311, 'iou': 0.00156, 'accuracy': 0.99061, 'contour_dice': 0.00311}} | 0.3798 |
70
+ | 0.701 | 0.6518 | 3341 | 0.001 | 0.9695 | 0.9865 | {0: {'f1': 0.99549, 'iou': 0.99102, 'accuracy': 0.99324, 'contour_dice': 0.99549}, 1: {'f1': 0.96954, 'iou': 0.94087, 'accuracy': 0.98502, 'contour_dice': 0.96954}, 2: {'f1': 0.00034, 'iou': 0.00017, 'accuracy': 0.99059, 'contour_dice': 0.00034}} | 0.2690 |
71
+ | 0.6962 | 0.7019 | 3598 | 0.001 | 0.9565 | 0.9714 | {0: {'f1': 0.99065, 'iou': 0.98148, 'accuracy': 0.98591, 'contour_dice': 0.99065}, 1: {'f1': 0.95637, 'iou': 0.91639, 'accuracy': 0.97893, 'contour_dice': 0.95637}, 2: {'f1': 0.00076, 'iou': 0.00038, 'accuracy': 0.9906, 'contour_dice': 0.00076}} | 0.2761 |
 
 
 
 
 
72
 
73
 
74
  ### Framework versions
model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:6b78ba10a5c1b9064a664658a29d3afa2c413804b393b6668f4fa2da25ef4de5
3
  size 2188724
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:fbd426f3bb780842b37b061e74f4410931899d764490f2d6c99cfaa704150735
3
  size 2188724
training_args.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:e1ae6012ddf95afdd3d8358098f85b8b1832ad99a3f879410d3a6f1c08736340
3
  size 5240
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:65022f8d0d045081b87d1dc88a1c7aaeee71985c38ac9931f8aa0004a9c5cda7
3
  size 5240