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Training in progress epoch 9

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  1. README.md +18 -17
  2. tf_model.h5 +1 -1
README.md CHANGED
@@ -15,28 +15,28 @@ probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [nvidia/segformer-b3-finetuned-ade-512-512](https://huggingface.co/nvidia/segformer-b3-finetuned-ade-512-512) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Train Loss: 0.3428
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- - Validation Loss: 0.3923
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- - Validation Mean Iou: 0.0119
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- - Validation Mean Accuracy: 0.0465
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- - Validation Overall Accuracy: 0.0430
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- - Validation Accuracy Clutter: 0.0327
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- - Validation Accuracy Building: 0.0166
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- - Validation Accuracy Road: 0.0977
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- - Validation Accuracy Static Car: 0.0003
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- - Validation Accuracy Tree: 0.1670
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- - Validation Accuracy Vegetation: 0.0113
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  - Validation Accuracy Human: 0.0
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  - Validation Accuracy Moving Car: nan
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- - Validation Iou Clutter: 0.0223
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- - Validation Iou Building: 0.0027
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- - Validation Iou Road: 0.0078
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- - Validation Iou Static Car: 0.0003
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- - Validation Iou Tree: 0.0617
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  - Validation Iou Vegetation: 0.0000
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  - Validation Iou Human: 0.0
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  - Validation Iou Moving Car: 0.0
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- - Epoch: 8
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  ## Model description
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@@ -71,6 +71,7 @@ The following hyperparameters were used during training:
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  | 0.3823 | 0.4131 | 0.0127 | 0.0504 | 0.0455 | 0.0374 | 0.0124 | 0.1251 | 0.0004 | 0.1705 | 0.0072 | 0.0 | nan | 0.0251 | 0.0020 | 0.0098 | 0.0004 | 0.0639 | 0.0000 | 0.0 | 0.0 | 6 |
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  | 0.3610 | 0.4006 | 0.0121 | 0.0518 | 0.0421 | 0.0300 | 0.0162 | 0.1272 | 0.0004 | 0.1675 | 0.0215 | 0.0 | nan | 0.0207 | 0.0026 | 0.0096 | 0.0004 | 0.0631 | 0.0001 | 0.0 | 0.0 | 7 |
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  | 0.3428 | 0.3923 | 0.0119 | 0.0465 | 0.0430 | 0.0327 | 0.0166 | 0.0977 | 0.0003 | 0.1670 | 0.0113 | 0.0 | nan | 0.0223 | 0.0027 | 0.0078 | 0.0003 | 0.0617 | 0.0000 | 0.0 | 0.0 | 8 |
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [nvidia/segformer-b3-finetuned-ade-512-512](https://huggingface.co/nvidia/segformer-b3-finetuned-ade-512-512) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Train Loss: 0.3207
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+ - Validation Loss: 0.3852
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+ - Validation Mean Iou: 0.0093
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+ - Validation Mean Accuracy: 0.0378
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+ - Validation Overall Accuracy: 0.0336
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+ - Validation Accuracy Clutter: 0.0293
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+ - Validation Accuracy Building: 0.0228
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+ - Validation Accuracy Road: 0.0896
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+ - Validation Accuracy Static Car: 0.0006
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+ - Validation Accuracy Tree: 0.1118
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+ - Validation Accuracy Vegetation: 0.0103
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  - Validation Accuracy Human: 0.0
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  - Validation Accuracy Moving Car: nan
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+ - Validation Iou Clutter: 0.0199
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+ - Validation Iou Building: 0.0037
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+ - Validation Iou Road: 0.0072
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+ - Validation Iou Static Car: 0.0006
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+ - Validation Iou Tree: 0.0427
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  - Validation Iou Vegetation: 0.0000
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  - Validation Iou Human: 0.0
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  - Validation Iou Moving Car: 0.0
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+ - Epoch: 9
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  ## Model description
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  | 0.3823 | 0.4131 | 0.0127 | 0.0504 | 0.0455 | 0.0374 | 0.0124 | 0.1251 | 0.0004 | 0.1705 | 0.0072 | 0.0 | nan | 0.0251 | 0.0020 | 0.0098 | 0.0004 | 0.0639 | 0.0000 | 0.0 | 0.0 | 6 |
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  | 0.3610 | 0.4006 | 0.0121 | 0.0518 | 0.0421 | 0.0300 | 0.0162 | 0.1272 | 0.0004 | 0.1675 | 0.0215 | 0.0 | nan | 0.0207 | 0.0026 | 0.0096 | 0.0004 | 0.0631 | 0.0001 | 0.0 | 0.0 | 7 |
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  | 0.3428 | 0.3923 | 0.0119 | 0.0465 | 0.0430 | 0.0327 | 0.0166 | 0.0977 | 0.0003 | 0.1670 | 0.0113 | 0.0 | nan | 0.0223 | 0.0027 | 0.0078 | 0.0003 | 0.0617 | 0.0000 | 0.0 | 0.0 | 8 |
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+ | 0.3207 | 0.3852 | 0.0093 | 0.0378 | 0.0336 | 0.0293 | 0.0228 | 0.0896 | 0.0006 | 0.1118 | 0.0103 | 0.0 | nan | 0.0199 | 0.0037 | 0.0072 | 0.0006 | 0.0427 | 0.0000 | 0.0 | 0.0 | 9 |
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  ### Framework versions
tf_model.h5 CHANGED
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