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segformer-b0-finetuned-wrinkle

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  1. README.md +173 -67
  2. model.safetensors +1 -1
  3. runs/Dec16_12-48-23_618ac8707a1e/events.out.tfevents.1734353309.618ac8707a1e.300.0 +3 -0
  4. runs/Dec16_16-16-40_f99d2b1e8b23/events.out.tfevents.1734365819.f99d2b1e8b23.676.0 +3 -0
  5. runs/Dec17_06-21-54_f22245073fd4/events.out.tfevents.1734416559.f22245073fd4.845.0 +3 -0
  6. training_args.bin +1 -1
README.md CHANGED
@@ -16,16 +16,16 @@ should probably proofread and complete it, then remove this comment. -->
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  # segformer-b0-finetuned-wrinkle
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- This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the face-wrinkles dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0189
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- - Mean Iou: 0.2163
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- - Mean Accuracy: 0.4327
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- - Overall Accuracy: 0.4327
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  - Accuracy Unlabeled: nan
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- - Accuracy Wrinkle: 0.4327
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  - Iou Unlabeled: 0.0
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- - Iou Wrinkle: 0.4327
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  ## Model description
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@@ -45,8 +45,8 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 6e-05
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- - train_batch_size: 16
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- - eval_batch_size: 16
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  - seed: 42
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  - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
@@ -56,64 +56,170 @@ The following hyperparameters were used during training:
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Unlabeled | Accuracy Wrinkle | Iou Unlabeled | Iou Wrinkle |
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- |:-------------:|:------:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:----------------:|:-------------:|:-----------:|
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- | 0.0122 | 0.1786 | 20 | 0.0186 | 0.1899 | 0.3798 | 0.3798 | nan | 0.3798 | 0.0 | 0.3798 |
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- | 0.0114 | 0.3571 | 40 | 0.0188 | 0.2007 | 0.4014 | 0.4014 | nan | 0.4014 | 0.0 | 0.4014 |
63
- | 0.0104 | 0.5357 | 60 | 0.0189 | 0.2127 | 0.4254 | 0.4254 | nan | 0.4254 | 0.0 | 0.4254 |
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- | 0.0116 | 0.7143 | 80 | 0.0187 | 0.2215 | 0.4430 | 0.4430 | nan | 0.4430 | 0.0 | 0.4430 |
65
- | 0.0104 | 0.8929 | 100 | 0.0189 | 0.1815 | 0.3630 | 0.3630 | nan | 0.3630 | 0.0 | 0.3630 |
66
- | 0.0151 | 1.0714 | 120 | 0.0187 | 0.1949 | 0.3898 | 0.3898 | nan | 0.3898 | 0.0 | 0.3898 |
67
- | 0.0155 | 1.25 | 140 | 0.0187 | 0.2073 | 0.4147 | 0.4147 | nan | 0.4147 | 0.0 | 0.4147 |
68
- | 0.0077 | 1.4286 | 160 | 0.0192 | 0.2406 | 0.4812 | 0.4812 | nan | 0.4812 | 0.0 | 0.4812 |
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- | 0.0117 | 1.6071 | 180 | 0.0191 | 0.2391 | 0.4782 | 0.4782 | nan | 0.4782 | 0.0 | 0.4782 |
70
- | 0.0063 | 1.7857 | 200 | 0.0188 | 0.1787 | 0.3573 | 0.3573 | nan | 0.3573 | 0.0 | 0.3573 |
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- | 0.01 | 1.9643 | 220 | 0.0185 | 0.2195 | 0.4389 | 0.4389 | nan | 0.4389 | 0.0 | 0.4389 |
72
- | 0.0109 | 2.1429 | 240 | 0.0191 | 0.1699 | 0.3398 | 0.3398 | nan | 0.3398 | 0.0 | 0.3398 |
73
- | 0.0104 | 2.3214 | 260 | 0.0191 | 0.2167 | 0.4335 | 0.4335 | nan | 0.4335 | 0.0 | 0.4335 |
74
- | 0.0145 | 2.5 | 280 | 0.0198 | 0.2604 | 0.5208 | 0.5208 | nan | 0.5208 | 0.0 | 0.5208 |
75
- | 0.0093 | 2.6786 | 300 | 0.0185 | 0.1963 | 0.3927 | 0.3927 | nan | 0.3927 | 0.0 | 0.3927 |
76
- | 0.0106 | 2.8571 | 320 | 0.0185 | 0.2080 | 0.4159 | 0.4159 | nan | 0.4159 | 0.0 | 0.4159 |
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- | 0.007 | 3.0357 | 340 | 0.0190 | 0.1894 | 0.3787 | 0.3787 | nan | 0.3787 | 0.0 | 0.3787 |
78
- | 0.01 | 3.2143 | 360 | 0.0189 | 0.2194 | 0.4389 | 0.4389 | nan | 0.4389 | 0.0 | 0.4389 |
79
- | 0.0118 | 3.3929 | 380 | 0.0186 | 0.2312 | 0.4625 | 0.4625 | nan | 0.4625 | 0.0 | 0.4625 |
80
- | 0.008 | 3.5714 | 400 | 0.0189 | 0.1746 | 0.3492 | 0.3492 | nan | 0.3492 | 0.0 | 0.3492 |
81
- | 0.0101 | 3.75 | 420 | 0.0185 | 0.1822 | 0.3644 | 0.3644 | nan | 0.3644 | 0.0 | 0.3644 |
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- | 0.0093 | 3.9286 | 440 | 0.0187 | 0.2126 | 0.4252 | 0.4252 | nan | 0.4252 | 0.0 | 0.4252 |
83
- | 0.008 | 4.1071 | 460 | 0.0186 | 0.2058 | 0.4116 | 0.4116 | nan | 0.4116 | 0.0 | 0.4116 |
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- | 0.0134 | 4.2857 | 480 | 0.0187 | 0.2335 | 0.4669 | 0.4669 | nan | 0.4669 | 0.0 | 0.4669 |
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- | 0.0119 | 4.4643 | 500 | 0.0191 | 0.1850 | 0.3700 | 0.3700 | nan | 0.3700 | 0.0 | 0.3700 |
86
- | 0.0064 | 4.6429 | 520 | 0.0187 | 0.1892 | 0.3785 | 0.3785 | nan | 0.3785 | 0.0 | 0.3785 |
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- | 0.0087 | 4.8214 | 540 | 0.0190 | 0.2253 | 0.4506 | 0.4506 | nan | 0.4506 | 0.0 | 0.4506 |
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- | 0.0122 | 5.0 | 560 | 0.0196 | 0.2598 | 0.5196 | 0.5196 | nan | 0.5196 | 0.0 | 0.5196 |
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- | 0.0071 | 5.1786 | 580 | 0.0188 | 0.2224 | 0.4448 | 0.4448 | nan | 0.4448 | 0.0 | 0.4448 |
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- | 0.0125 | 5.3571 | 600 | 0.0188 | 0.2051 | 0.4103 | 0.4103 | nan | 0.4103 | 0.0 | 0.4103 |
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- | 0.0093 | 5.5357 | 620 | 0.0192 | 0.2410 | 0.4821 | 0.4821 | nan | 0.4821 | 0.0 | 0.4821 |
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- | 0.0082 | 5.7143 | 640 | 0.0191 | 0.2291 | 0.4582 | 0.4582 | nan | 0.4582 | 0.0 | 0.4582 |
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- | 0.0089 | 5.8929 | 660 | 0.0187 | 0.1993 | 0.3985 | 0.3985 | nan | 0.3985 | 0.0 | 0.3985 |
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- | 0.0104 | 6.0714 | 680 | 0.0191 | 0.2049 | 0.4098 | 0.4098 | nan | 0.4098 | 0.0 | 0.4098 |
95
- | 0.0111 | 6.25 | 700 | 0.0187 | 0.2216 | 0.4431 | 0.4431 | nan | 0.4431 | 0.0 | 0.4431 |
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- | 0.0113 | 6.4286 | 720 | 0.0196 | 0.2525 | 0.5050 | 0.5050 | nan | 0.5050 | 0.0 | 0.5050 |
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- | 0.0099 | 6.6071 | 740 | 0.0189 | 0.2219 | 0.4439 | 0.4439 | nan | 0.4439 | 0.0 | 0.4439 |
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- | 0.0062 | 6.7857 | 760 | 0.0187 | 0.2349 | 0.4699 | 0.4699 | nan | 0.4699 | 0.0 | 0.4699 |
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- | 0.0132 | 6.9643 | 780 | 0.0188 | 0.2108 | 0.4217 | 0.4217 | nan | 0.4217 | 0.0 | 0.4217 |
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- | 0.0132 | 7.1429 | 800 | 0.0190 | 0.2097 | 0.4194 | 0.4194 | nan | 0.4194 | 0.0 | 0.4194 |
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- | 0.0141 | 7.3214 | 820 | 0.0187 | 0.2125 | 0.4251 | 0.4251 | nan | 0.4251 | 0.0 | 0.4251 |
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- | 0.0121 | 7.5 | 840 | 0.0189 | 0.2176 | 0.4351 | 0.4351 | nan | 0.4351 | 0.0 | 0.4351 |
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- | 0.0099 | 7.6786 | 860 | 0.0187 | 0.2002 | 0.4004 | 0.4004 | nan | 0.4004 | 0.0 | 0.4004 |
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- | 0.0168 | 7.8571 | 880 | 0.0188 | 0.2159 | 0.4319 | 0.4319 | nan | 0.4319 | 0.0 | 0.4319 |
105
- | 0.0064 | 8.0357 | 900 | 0.0188 | 0.2194 | 0.4387 | 0.4387 | nan | 0.4387 | 0.0 | 0.4387 |
106
- | 0.0121 | 8.2143 | 920 | 0.0191 | 0.2309 | 0.4618 | 0.4618 | nan | 0.4618 | 0.0 | 0.4618 |
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- | 0.0133 | 8.3929 | 940 | 0.0189 | 0.2101 | 0.4202 | 0.4202 | nan | 0.4202 | 0.0 | 0.4202 |
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- | 0.0105 | 8.5714 | 960 | 0.0190 | 0.2287 | 0.4573 | 0.4573 | nan | 0.4573 | 0.0 | 0.4573 |
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- | 0.0092 | 8.75 | 980 | 0.0188 | 0.2178 | 0.4356 | 0.4356 | nan | 0.4356 | 0.0 | 0.4356 |
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- | 0.0124 | 8.9286 | 1000 | 0.0191 | 0.2277 | 0.4553 | 0.4553 | nan | 0.4553 | 0.0 | 0.4553 |
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- | 0.0108 | 9.1071 | 1020 | 0.0189 | 0.2017 | 0.4033 | 0.4033 | nan | 0.4033 | 0.0 | 0.4033 |
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- | 0.0098 | 9.2857 | 1040 | 0.0190 | 0.2271 | 0.4542 | 0.4542 | nan | 0.4542 | 0.0 | 0.4542 |
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- | 0.0087 | 9.4643 | 1060 | 0.0189 | 0.2168 | 0.4335 | 0.4335 | nan | 0.4335 | 0.0 | 0.4335 |
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- | 0.008 | 9.6429 | 1080 | 0.0189 | 0.2219 | 0.4438 | 0.4438 | nan | 0.4438 | 0.0 | 0.4438 |
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- | 0.0071 | 9.8214 | 1100 | 0.0189 | 0.2204 | 0.4407 | 0.4407 | nan | 0.4407 | 0.0 | 0.4407 |
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- | 0.0072 | 10.0 | 1120 | 0.0189 | 0.2163 | 0.4327 | 0.4327 | nan | 0.4327 | 0.0 | 0.4327 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  # segformer-b0-finetuned-wrinkle
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19
+ This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the AmirGenAI/my-wrinkle-seg-dataset dataset.
20
  It achieves the following results on the evaluation set:
21
+ - Loss: 0.0170
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+ - Mean Iou: 0.1948
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+ - Mean Accuracy: 0.3896
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+ - Overall Accuracy: 0.3896
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  - Accuracy Unlabeled: nan
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+ - Accuracy Wrinkle: 0.3896
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  - Iou Unlabeled: 0.0
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+ - Iou Wrinkle: 0.3896
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30
  ## Model description
31
 
 
45
 
46
  The following hyperparameters were used during training:
47
  - learning_rate: 6e-05
48
+ - train_batch_size: 32
49
+ - eval_batch_size: 32
50
  - seed: 42
51
  - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
52
  - lr_scheduler_type: linear
 
56
 
57
  ### Training results
58
 
59
+ | Training Loss | Epoch | Step | Accuracy Unlabeled | Accuracy Wrinkle | Iou Unlabeled | Iou Wrinkle | Validation Loss | Mean Accuracy | Mean Iou | Overall Accuracy |
60
+ |:-------------:|:------:|:----:|:------------------:|:----------------:|:-------------:|:-----------:|:---------------:|:-------------:|:--------:|:----------------:|
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+ | 0.0207 | 0.0617 | 20 | nan | 0.3445 | 0.0 | 0.3445 | 0.0224 | 0.3445 | 0.1723 | 0.3445 |
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+ | 0.0235 | 0.1235 | 40 | nan | 0.3026 | 0.0 | 0.3026 | 0.0214 | 0.3026 | 0.1513 | 0.3026 |
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+ | 0.0159 | 0.1852 | 60 | nan | 0.3031 | 0.0 | 0.3031 | 0.0206 | 0.3031 | 0.1515 | 0.3031 |
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+ | 0.0214 | 0.2469 | 80 | nan | 0.2827 | 0.0 | 0.2827 | 0.0204 | 0.2827 | 0.1413 | 0.2827 |
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+ | 0.0204 | 0.3086 | 100 | nan | 0.2768 | 0.0 | 0.2768 | 0.0202 | 0.2768 | 0.1384 | 0.2768 |
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+ | 0.0231 | 0.3704 | 120 | nan | 0.2846 | 0.0 | 0.2846 | 0.0200 | 0.2846 | 0.1423 | 0.2846 |
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+ | 0.0151 | 0.4321 | 140 | nan | 0.2569 | 0.0 | 0.2569 | 0.0199 | 0.2569 | 0.1285 | 0.2569 |
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+ | 0.0245 | 0.4938 | 160 | nan | 0.2752 | 0.0 | 0.2752 | 0.0197 | 0.2752 | 0.1376 | 0.2752 |
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+ | 0.023 | 0.5556 | 180 | nan | 0.3322 | 0.0 | 0.3322 | 0.0200 | 0.3322 | 0.1661 | 0.3322 |
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+ | 0.0321 | 0.6173 | 200 | nan | 0.3031 | 0.0 | 0.3031 | 0.0198 | 0.3031 | 0.1516 | 0.3031 |
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+ | 0.0197 | 0.6790 | 220 | nan | 0.3157 | 0.0 | 0.3157 | 0.0196 | 0.3157 | 0.1578 | 0.3157 |
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+ | 0.0192 | 0.7407 | 240 | nan | 0.3430 | 0.0 | 0.3430 | 0.0198 | 0.3430 | 0.1715 | 0.3430 |
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+ | 0.0228 | 0.8025 | 260 | nan | 0.3144 | 0.0 | 0.3144 | 0.0194 | 0.3144 | 0.1572 | 0.3144 |
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+ | 0.0216 | 0.8642 | 280 | nan | 0.3338 | 0.0 | 0.3338 | 0.0194 | 0.3338 | 0.1669 | 0.3338 |
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+ | 0.0186 | 0.9259 | 300 | nan | 0.3411 | 0.0 | 0.3411 | 0.0193 | 0.3411 | 0.1705 | 0.3411 |
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+ | 0.0202 | 0.9877 | 320 | nan | 0.3215 | 0.0 | 0.3215 | 0.0192 | 0.3215 | 0.1608 | 0.3215 |
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+ | 0.0194 | 1.0494 | 340 | nan | 0.3286 | 0.0 | 0.3286 | 0.0194 | 0.3286 | 0.1643 | 0.3286 |
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+ | 0.0166 | 1.1111 | 360 | nan | 0.2658 | 0.0 | 0.2658 | 0.0193 | 0.2658 | 0.1329 | 0.2658 |
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+ | 0.0187 | 1.1728 | 380 | nan | 0.3133 | 0.0 | 0.3133 | 0.0191 | 0.3133 | 0.1567 | 0.3133 |
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+ | 0.0208 | 1.2346 | 400 | nan | 0.3254 | 0.0 | 0.3254 | 0.0190 | 0.3254 | 0.1627 | 0.3254 |
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+ | 0.0237 | 1.2963 | 420 | nan | 0.3093 | 0.0 | 0.3093 | 0.0190 | 0.3093 | 0.1546 | 0.3093 |
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+ | 0.0244 | 1.3580 | 440 | nan | 0.3167 | 0.0 | 0.3167 | 0.0189 | 0.3167 | 0.1583 | 0.3167 |
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+ | 0.0156 | 1.4198 | 460 | nan | 0.3408 | 0.0 | 0.3408 | 0.0191 | 0.3408 | 0.1704 | 0.3408 |
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+ | 0.0231 | 1.4815 | 480 | nan | 0.2716 | 0.0 | 0.2716 | 0.0190 | 0.2716 | 0.1358 | 0.2716 |
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+ | 0.0197 | 1.5432 | 500 | nan | 0.3540 | 0.0 | 0.3540 | 0.0190 | 0.3540 | 0.1770 | 0.3540 |
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+ | 0.013 | 1.6049 | 520 | nan | 0.3358 | 0.0 | 0.3358 | 0.0188 | 0.3358 | 0.1679 | 0.3358 |
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+ | 0.0158 | 1.6667 | 540 | nan | 0.3619 | 0.0 | 0.3619 | 0.0188 | 0.3619 | 0.1810 | 0.3619 |
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+ | 0.0212 | 1.7284 | 560 | nan | 0.3649 | 0.0 | 0.3649 | 0.0188 | 0.3649 | 0.1824 | 0.3649 |
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+ | 0.0231 | 1.7901 | 580 | nan | 0.2906 | 0.0 | 0.2906 | 0.0189 | 0.2906 | 0.1453 | 0.2906 |
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+ | 0.0158 | 1.8519 | 600 | nan | 0.3210 | 0.0 | 0.3210 | 0.0187 | 0.3210 | 0.1605 | 0.3210 |
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+ | 0.024 | 1.9136 | 620 | nan | 0.3117 | 0.0 | 0.3117 | 0.0187 | 0.3117 | 0.1558 | 0.3117 |
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+ | 0.0193 | 1.9753 | 640 | nan | 0.3596 | 0.0 | 0.3596 | 0.0187 | 0.3596 | 0.1798 | 0.3596 |
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+ | 0.0201 | 2.0370 | 660 | nan | 0.3628 | 0.0 | 0.3628 | 0.0187 | 0.3628 | 0.1814 | 0.3628 |
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+ | 0.0162 | 2.0988 | 680 | nan | 0.3238 | 0.0 | 0.3238 | 0.0185 | 0.3238 | 0.1619 | 0.3238 |
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+ | 0.0219 | 2.1605 | 700 | nan | 0.3622 | 0.0 | 0.3622 | 0.0186 | 0.3622 | 0.1811 | 0.3622 |
96
+ | 0.0207 | 2.2222 | 720 | nan | 0.3919 | 0.0 | 0.3919 | 0.0189 | 0.3919 | 0.1959 | 0.3919 |
97
+ | 0.0176 | 2.2840 | 740 | nan | 0.3116 | 0.0 | 0.3116 | 0.0185 | 0.3116 | 0.1558 | 0.3116 |
98
+ | 0.0149 | 2.3457 | 760 | nan | 0.3917 | 0.0 | 0.3917 | 0.0186 | 0.3917 | 0.1959 | 0.3917 |
99
+ | 0.0192 | 2.4074 | 780 | nan | 0.3097 | 0.0 | 0.3097 | 0.0184 | 0.3097 | 0.1548 | 0.3097 |
100
+ | 0.0202 | 2.4691 | 800 | nan | 0.3745 | 0.0 | 0.3745 | 0.0183 | 0.3745 | 0.1872 | 0.3745 |
101
+ | 0.0181 | 2.5309 | 820 | nan | 0.3687 | 0.0 | 0.3687 | 0.0185 | 0.3687 | 0.1844 | 0.3687 |
102
+ | 0.0168 | 2.5926 | 840 | nan | 0.3629 | 0.0 | 0.3629 | 0.0183 | 0.3629 | 0.1815 | 0.3629 |
103
+ | 0.0171 | 2.6543 | 860 | nan | 0.3148 | 0.0 | 0.3148 | 0.0183 | 0.3148 | 0.1574 | 0.3148 |
104
+ | 0.0166 | 2.7160 | 880 | nan | 0.3426 | 0.0 | 0.3426 | 0.0182 | 0.3426 | 0.1713 | 0.3426 |
105
+ | 0.0123 | 2.7778 | 900 | nan | 0.3670 | 0.0 | 0.3670 | 0.0183 | 0.3670 | 0.1835 | 0.3670 |
106
+ | 0.0149 | 2.8395 | 920 | nan | 0.3535 | 0.0 | 0.3535 | 0.0182 | 0.3535 | 0.1767 | 0.3535 |
107
+ | 0.016 | 2.9012 | 940 | nan | 0.3856 | 0.0 | 0.3856 | 0.0183 | 0.3856 | 0.1928 | 0.3856 |
108
+ | 0.0192 | 2.9630 | 960 | nan | 0.3647 | 0.0 | 0.3647 | 0.0182 | 0.3647 | 0.1823 | 0.3647 |
109
+ | 0.0188 | 3.0247 | 980 | nan | 0.3313 | 0.0 | 0.3313 | 0.0182 | 0.3313 | 0.1657 | 0.3313 |
110
+ | 0.0203 | 3.0864 | 1000 | nan | 0.3233 | 0.0 | 0.3233 | 0.0181 | 0.3233 | 0.1617 | 0.3233 |
111
+ | 0.0152 | 3.1481 | 1020 | nan | 0.3047 | 0.0 | 0.3047 | 0.0182 | 0.3047 | 0.1523 | 0.3047 |
112
+ | 0.0175 | 3.2099 | 1040 | nan | 0.3545 | 0.0 | 0.3545 | 0.0181 | 0.3545 | 0.1772 | 0.3545 |
113
+ | 0.0241 | 3.2716 | 1060 | nan | 0.3898 | 0.0 | 0.3898 | 0.0182 | 0.3898 | 0.1949 | 0.3898 |
114
+ | 0.0215 | 3.3333 | 1080 | nan | 0.3102 | 0.0 | 0.3102 | 0.0181 | 0.3102 | 0.1551 | 0.3102 |
115
+ | 0.0205 | 3.3951 | 1100 | nan | 0.3581 | 0.0 | 0.3581 | 0.0180 | 0.3581 | 0.1791 | 0.3581 |
116
+ | 0.0208 | 3.4568 | 1120 | nan | 0.3611 | 0.0 | 0.3611 | 0.0179 | 0.3611 | 0.1805 | 0.3611 |
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+ | 0.0184 | 3.5185 | 1140 | nan | 0.3151 | 0.0 | 0.3151 | 0.0180 | 0.3151 | 0.1576 | 0.3151 |
118
+ | 0.0159 | 3.5802 | 1160 | nan | 0.4039 | 0.0 | 0.4039 | 0.0182 | 0.4039 | 0.2019 | 0.4039 |
119
+ | 0.0219 | 3.6420 | 1180 | nan | 0.3444 | 0.0 | 0.3444 | 0.0181 | 0.3444 | 0.1722 | 0.3444 |
120
+ | 0.023 | 3.7037 | 1200 | nan | 0.3265 | 0.0 | 0.3265 | 0.0179 | 0.3265 | 0.1633 | 0.3265 |
121
+ | 0.0148 | 3.7654 | 1220 | nan | 0.3677 | 0.0 | 0.3677 | 0.0179 | 0.3677 | 0.1838 | 0.3677 |
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+ | 0.019 | 3.8272 | 1240 | nan | 0.3422 | 0.0 | 0.3422 | 0.0178 | 0.3422 | 0.1711 | 0.3422 |
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+ | 0.0154 | 3.8889 | 1260 | nan | 0.3611 | 0.0 | 0.3611 | 0.0179 | 0.3611 | 0.1806 | 0.3611 |
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+ | 0.0212 | 3.9506 | 1280 | nan | 0.3274 | 0.0 | 0.3274 | 0.0178 | 0.3274 | 0.1637 | 0.3274 |
125
+ | 0.0192 | 4.0123 | 1300 | nan | 0.3829 | 0.0 | 0.3829 | 0.0178 | 0.3829 | 0.1914 | 0.3829 |
126
+ | 0.0183 | 4.0741 | 1320 | nan | 0.4120 | 0.0 | 0.4120 | 0.0180 | 0.4120 | 0.2060 | 0.4120 |
127
+ | 0.0141 | 4.1358 | 1340 | nan | 0.3613 | 0.0 | 0.3613 | 0.0177 | 0.3613 | 0.1806 | 0.3613 |
128
+ | 0.0165 | 4.1975 | 1360 | nan | 0.3552 | 0.0 | 0.3552 | 0.0180 | 0.3552 | 0.1776 | 0.3552 |
129
+ | 0.018 | 4.2593 | 1380 | nan | 0.3646 | 0.0 | 0.3646 | 0.0177 | 0.3646 | 0.1823 | 0.3646 |
130
+ | 0.0166 | 4.3210 | 1400 | nan | 0.3557 | 0.0 | 0.3557 | 0.0177 | 0.3557 | 0.1778 | 0.3557 |
131
+ | 0.0193 | 4.3827 | 1420 | nan | 0.3518 | 0.0 | 0.3518 | 0.0177 | 0.3518 | 0.1759 | 0.3518 |
132
+ | 0.0173 | 4.4444 | 1440 | nan | 0.3640 | 0.0 | 0.3640 | 0.0176 | 0.3640 | 0.1820 | 0.3640 |
133
+ | 0.0159 | 4.5062 | 1460 | nan | 0.4083 | 0.0 | 0.4083 | 0.0178 | 0.4083 | 0.2042 | 0.4083 |
134
+ | 0.0186 | 4.5679 | 1480 | nan | 0.3679 | 0.0 | 0.3679 | 0.0177 | 0.3679 | 0.1839 | 0.3679 |
135
+ | 0.0214 | 4.6296 | 1500 | nan | 0.3567 | 0.0 | 0.3567 | 0.0176 | 0.3567 | 0.1783 | 0.3567 |
136
+ | 0.0192 | 4.6914 | 1520 | nan | 0.3595 | 0.0 | 0.3595 | 0.0176 | 0.3595 | 0.1797 | 0.3595 |
137
+ | 0.0173 | 4.7531 | 1540 | nan | 0.3567 | 0.0 | 0.3567 | 0.0176 | 0.3567 | 0.1784 | 0.3567 |
138
+ | 0.0185 | 4.8148 | 1560 | nan | 0.3830 | 0.0 | 0.3830 | 0.0176 | 0.3830 | 0.1915 | 0.3830 |
139
+ | 0.0179 | 4.8765 | 1580 | nan | 0.3851 | 0.0 | 0.3851 | 0.0176 | 0.3851 | 0.1926 | 0.3851 |
140
+ | 0.0152 | 4.9383 | 1600 | nan | 0.4017 | 0.0 | 0.4017 | 0.0177 | 0.4017 | 0.2009 | 0.4017 |
141
+ | 0.0281 | 5.0 | 1620 | nan | 0.3503 | 0.0 | 0.3503 | 0.0176 | 0.3503 | 0.1752 | 0.3503 |
142
+ | 0.0185 | 5.0617 | 1640 | nan | 0.4148 | 0.0 | 0.4148 | 0.0178 | 0.4148 | 0.2074 | 0.4148 |
143
+ | 0.0209 | 5.1235 | 1660 | nan | 0.3782 | 0.0 | 0.3782 | 0.0176 | 0.3782 | 0.1891 | 0.3782 |
144
+ | 0.0191 | 5.1852 | 1680 | nan | 0.3441 | 0.0 | 0.3441 | 0.0175 | 0.3441 | 0.1720 | 0.3441 |
145
+ | 0.0134 | 5.2469 | 1700 | nan | 0.3189 | 0.0 | 0.3189 | 0.0176 | 0.3189 | 0.1594 | 0.3189 |
146
+ | 0.0178 | 5.3086 | 1720 | nan | 0.3452 | 0.0 | 0.3452 | 0.0176 | 0.3452 | 0.1726 | 0.3452 |
147
+ | 0.0214 | 5.3704 | 1740 | nan | 0.4143 | 0.0 | 0.4143 | 0.0177 | 0.4143 | 0.2072 | 0.4143 |
148
+ | 0.0179 | 5.4321 | 1760 | nan | 0.3732 | 0.0 | 0.3732 | 0.0175 | 0.3732 | 0.1866 | 0.3732 |
149
+ | 0.0187 | 5.4938 | 1780 | nan | 0.3843 | 0.0 | 0.3843 | 0.0176 | 0.3843 | 0.1921 | 0.3843 |
150
+ | 0.0218 | 5.5556 | 1800 | nan | 0.3807 | 0.0 | 0.3807 | 0.0175 | 0.3807 | 0.1904 | 0.3807 |
151
+ | 0.0154 | 5.6173 | 1820 | nan | 0.3602 | 0.0 | 0.3602 | 0.0175 | 0.3602 | 0.1801 | 0.3602 |
152
+ | 0.021 | 5.6790 | 1840 | nan | 0.3445 | 0.0 | 0.3445 | 0.0175 | 0.3445 | 0.1723 | 0.3445 |
153
+ | 0.0191 | 5.7407 | 1860 | nan | 0.3290 | 0.0 | 0.3290 | 0.0175 | 0.3290 | 0.1645 | 0.3290 |
154
+ | 0.0194 | 5.8025 | 1880 | nan | 0.3564 | 0.0 | 0.3564 | 0.0174 | 0.3564 | 0.1782 | 0.3564 |
155
+ | 0.0121 | 5.8642 | 1900 | nan | 0.3860 | 0.0 | 0.3860 | 0.0175 | 0.3860 | 0.1930 | 0.3860 |
156
+ | 0.0194 | 5.9259 | 1920 | nan | 0.4023 | 0.0 | 0.4023 | 0.0175 | 0.4023 | 0.2011 | 0.4023 |
157
+ | 0.0159 | 5.9877 | 1940 | nan | 0.3953 | 0.0 | 0.3953 | 0.0173 | 0.3953 | 0.1976 | 0.3953 |
158
+ | 0.0142 | 6.0494 | 1960 | nan | 0.4036 | 0.0 | 0.4036 | 0.0173 | 0.4036 | 0.2018 | 0.4036 |
159
+ | 0.0165 | 6.1111 | 1980 | nan | 0.3593 | 0.0 | 0.3593 | 0.0173 | 0.3593 | 0.1796 | 0.3593 |
160
+ | 0.0166 | 6.1728 | 2000 | nan | 0.4104 | 0.0 | 0.4104 | 0.0174 | 0.4104 | 0.2052 | 0.4104 |
161
+ | 0.0164 | 6.2346 | 2020 | nan | 0.3653 | 0.0 | 0.3653 | 0.0174 | 0.3653 | 0.1826 | 0.3653 |
162
+ | 0.0267 | 6.2963 | 2040 | nan | 0.3582 | 0.0 | 0.3582 | 0.0173 | 0.3582 | 0.1791 | 0.3582 |
163
+ | 0.0202 | 6.3580 | 2060 | nan | 0.3613 | 0.0 | 0.3613 | 0.0173 | 0.3613 | 0.1806 | 0.3613 |
164
+ | 0.0134 | 6.4198 | 2080 | nan | 0.4004 | 0.0 | 0.4004 | 0.0174 | 0.4004 | 0.2002 | 0.4004 |
165
+ | 0.014 | 6.4815 | 2100 | nan | 0.3781 | 0.0 | 0.3781 | 0.0173 | 0.3781 | 0.1890 | 0.3781 |
166
+ | 0.0197 | 6.5432 | 2120 | nan | 0.3724 | 0.0 | 0.3724 | 0.0173 | 0.3724 | 0.1862 | 0.3724 |
167
+ | 0.0185 | 6.6049 | 2140 | nan | 0.3306 | 0.0 | 0.3306 | 0.0174 | 0.3306 | 0.1653 | 0.3306 |
168
+ | 0.0205 | 6.6667 | 2160 | nan | 0.3523 | 0.0 | 0.3523 | 0.0173 | 0.3523 | 0.1761 | 0.3523 |
169
+ | 0.0152 | 6.7284 | 2180 | nan | 0.3690 | 0.0 | 0.3690 | 0.0172 | 0.3690 | 0.1845 | 0.3690 |
170
+ | 0.0158 | 6.7901 | 2200 | 0.0172 | 0.1793 | 0.3586 | 0.3586 | nan | 0.3586 | 0.0 | 0.3586 |
171
+ | 0.0199 | 6.8519 | 2220 | 0.0174 | 0.2063 | 0.4126 | 0.4126 | nan | 0.4126 | 0.0 | 0.4126 |
172
+ | 0.0186 | 6.9136 | 2240 | 0.0173 | 0.1691 | 0.3382 | 0.3382 | nan | 0.3382 | 0.0 | 0.3382 |
173
+ | 0.0228 | 6.9753 | 2260 | 0.0173 | 0.1804 | 0.3609 | 0.3609 | nan | 0.3609 | 0.0 | 0.3609 |
174
+ | 0.0193 | 7.0370 | 2280 | 0.0172 | 0.1887 | 0.3775 | 0.3775 | nan | 0.3775 | 0.0 | 0.3775 |
175
+ | 0.0161 | 7.0988 | 2300 | 0.0172 | 0.1900 | 0.3799 | 0.3799 | nan | 0.3799 | 0.0 | 0.3799 |
176
+ | 0.0182 | 7.1605 | 2320 | 0.0172 | 0.1888 | 0.3775 | 0.3775 | nan | 0.3775 | 0.0 | 0.3775 |
177
+ | 0.0165 | 7.2222 | 2340 | 0.0172 | 0.2037 | 0.4075 | 0.4075 | nan | 0.4075 | 0.0 | 0.4075 |
178
+ | 0.0197 | 7.2840 | 2360 | 0.0172 | 0.1900 | 0.3800 | 0.3800 | nan | 0.3800 | 0.0 | 0.3800 |
179
+ | 0.0246 | 7.3457 | 2380 | 0.0172 | 0.1861 | 0.3722 | 0.3722 | nan | 0.3722 | 0.0 | 0.3722 |
180
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181
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182
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183
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184
+ | 0.0226 | 7.6543 | 2480 | 0.0172 | 0.1944 | 0.3889 | 0.3889 | nan | 0.3889 | 0.0 | 0.3889 |
185
+ | 0.0167 | 7.7160 | 2500 | 0.0172 | 0.1833 | 0.3666 | 0.3666 | nan | 0.3666 | 0.0 | 0.3666 |
186
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187
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188
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189
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190
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191
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192
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193
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194
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195
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196
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197
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198
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199
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200
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201
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202
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203
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204
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205
+ | 0.018 | 8.9506 | 2900 | 0.0171 | 0.1850 | 0.3700 | 0.3700 | nan | 0.3700 | 0.0 | 0.3700 |
206
+ | 0.0195 | 9.0123 | 2920 | 0.0171 | 0.2041 | 0.4081 | 0.4081 | nan | 0.4081 | 0.0 | 0.4081 |
207
+ | 0.0156 | 9.0741 | 2940 | 0.0171 | 0.1922 | 0.3844 | 0.3844 | nan | 0.3844 | 0.0 | 0.3844 |
208
+ | 0.0201 | 9.1358 | 2960 | 0.0171 | 0.1985 | 0.3971 | 0.3971 | nan | 0.3971 | 0.0 | 0.3971 |
209
+ | 0.0223 | 9.1975 | 2980 | 0.0171 | 0.1970 | 0.3940 | 0.3940 | nan | 0.3940 | 0.0 | 0.3940 |
210
+ | 0.0193 | 9.2593 | 3000 | 0.0170 | 0.1918 | 0.3836 | 0.3836 | nan | 0.3836 | 0.0 | 0.3836 |
211
+ | 0.0121 | 9.3210 | 3020 | 0.0170 | 0.1978 | 0.3956 | 0.3956 | nan | 0.3956 | 0.0 | 0.3956 |
212
+ | 0.0183 | 9.3827 | 3040 | 0.0170 | 0.1922 | 0.3845 | 0.3845 | nan | 0.3845 | 0.0 | 0.3845 |
213
+ | 0.0208 | 9.4444 | 3060 | 0.0170 | 0.1966 | 0.3932 | 0.3932 | nan | 0.3932 | 0.0 | 0.3932 |
214
+ | 0.0207 | 9.5062 | 3080 | 0.0170 | 0.1967 | 0.3933 | 0.3933 | nan | 0.3933 | 0.0 | 0.3933 |
215
+ | 0.0194 | 9.5679 | 3100 | 0.0170 | 0.1922 | 0.3843 | 0.3843 | nan | 0.3843 | 0.0 | 0.3843 |
216
+ | 0.0158 | 9.6296 | 3120 | 0.0170 | 0.1965 | 0.3929 | 0.3929 | nan | 0.3929 | 0.0 | 0.3929 |
217
+ | 0.0158 | 9.6914 | 3140 | 0.0170 | 0.1898 | 0.3796 | 0.3796 | nan | 0.3796 | 0.0 | 0.3796 |
218
+ | 0.0215 | 9.7531 | 3160 | 0.0170 | 0.1922 | 0.3845 | 0.3845 | nan | 0.3845 | 0.0 | 0.3845 |
219
+ | 0.0143 | 9.8148 | 3180 | 0.0170 | 0.1989 | 0.3979 | 0.3979 | nan | 0.3979 | 0.0 | 0.3979 |
220
+ | 0.0177 | 9.8765 | 3200 | 0.0170 | 0.1935 | 0.3870 | 0.3870 | nan | 0.3870 | 0.0 | 0.3870 |
221
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222
+ | 0.0189 | 10.0 | 3240 | 0.0170 | 0.1948 | 0.3896 | 0.3896 | nan | 0.3896 | 0.0 | 0.3896 |
223
 
224
 
225
  ### Framework versions
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