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nateraw
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mit-b0-finetuned-sidewalks-v2

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segformer
generated_from_keras_callback
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nateraw commited on
Commit
1590036
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1 Parent(s): cabe6fa

Training in progress epoch 4

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Files changed (2) hide show
  1. README.md +29 -18
  2. tf_model.h5 +1 -1
README.md CHANGED
@@ -14,24 +14,24 @@ probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Train Loss: 0.6320
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- - Validation Loss: 0.5173
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- - Validation Mean Iou: 0.2894
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- - Validation Mean Accuracy: 0.3454
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- - Validation Overall Accuracy: 0.8435
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- - Validation Per Category Iou: [0. 0.70789146 0.84902296 0.65266358 0.76099965 0.32934391
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- nan 0.29576422 0.43988204 0. 0.79276447 0.
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- 0. 0. 0. 0.42668367 0. 0.
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- 0.71717911 0. 0.32151249 0.50084444 0. nan
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- 0. 0.18711455 0. 0. 0.82903803 0.68990498
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- 0.8990059 0. 0.00213015 0.14819771 0. ]
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- - Validation Per Category Accuracy: [0. 0.84048763 0.93514369 0.68355212 0.88302113 0.458816
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- nan 0.38623272 0.69456442 0. 0.92379471 0.
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- 0. 0. 0. 0.50677438 0. 0.
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- 0.90362965 0. 0.4662386 0.57368294 0. nan
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- 0. 0.23281768 0. 0. 0.9001526 0.86786434
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- 0.95195314 0. 0.00333751 0.18532191 0. ]
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- - Epoch: 3
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  ## Model description
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@@ -101,6 +101,17 @@ The following hyperparameters were used during training:
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  0.90362965 0. 0.4662386 0.57368294 0. nan
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  0. 0.23281768 0. 0. 0.9001526 0.86786434
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  0.95195314 0. 0.00333751 0.18532191 0. ] | 3 |
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Train Loss: 0.5609
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+ - Validation Loss: 0.5099
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+ - Validation Mean Iou: 0.2920
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+ - Validation Mean Accuracy: 0.3599
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+ - Validation Overall Accuracy: 0.8385
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+ - Validation Per Category Iou: [0. 0.70817583 0.84131144 0.66573523 0.81449696 0.38891117
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+ nan 0.28124784 0.42659255 0. 0.80855146 0.
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+ 0. 0. 0. 0.46011866 0. 0.
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+ 0.65458792 0. 0.28411565 0.46758138 0. nan
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+ 0. 0.21849067 0. 0. 0.83829062 0.71207623
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+ 0.89929169 0. 0.02846127 0.13782635 0. ]
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+ - Validation Per Category Accuracy: [0. 0.88632871 0.91269832 0.79044294 0.88368528 0.57405218
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+ nan 0.35035973 0.77610775 0. 0.8889696 0.
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+ 0. 0. 0. 0.6020786 0. 0.
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+ 0.74586521 0. 0.61602403 0.54519561 0. nan
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+ 0. 0.28447396 0. 0. 0.94520232 0.85544414
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+ 0.95994042 0. 0.04680851 0.21407134 0. ]
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+ - Epoch: 4
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  ## Model description
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  0.90362965 0. 0.4662386 0.57368294 0. nan
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  0. 0.23281768 0. 0. 0.9001526 0.86786434
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  0.95195314 0. 0.00333751 0.18532191 0. ] | 3 |
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+ | 0.5609 | 0.5099 | 0.2920 | 0.3599 | 0.8385 | [0. 0.70817583 0.84131144 0.66573523 0.81449696 0.38891117
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+ nan 0.28124784 0.42659255 0. 0.80855146 0.
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+ 0. 0. 0. 0.46011866 0. 0.
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+ 0.65458792 0. 0.28411565 0.46758138 0. nan
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+ 0. 0.21849067 0. 0. 0.83829062 0.71207623
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+ 0.89929169 0. 0.02846127 0.13782635 0. ] | [0. 0.88632871 0.91269832 0.79044294 0.88368528 0.57405218
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+ nan 0.35035973 0.77610775 0. 0.8889696 0.
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+ 0. 0. 0. 0.6020786 0. 0.
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+ 0.74586521 0. 0.61602403 0.54519561 0. nan
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+ 0. 0.28447396 0. 0. 0.94520232 0.85544414
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+ 0.95994042 0. 0.04680851 0.21407134 0. ] | 4 |
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  ### Framework versions
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