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Training in progress epoch 24

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  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: 0.2324
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- - Validation Loss: 0.6074
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- - Validation Mean Iou: 0.3379
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- - Validation Mean Accuracy: 0.4106
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- - Validation Overall Accuracy: 0.8528
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- - Validation Per Category Iou: [0. 0.72434007 0.87301941 0.51447452 0.65357748 0.31026479
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- nan 0.44044211 0.50481839 0.03262782 0.81648207 0.
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- 0. nan 0. 0.57028611 0. 0.
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- 0.71488251 0.14924904 0.45551669 0.37382533 0. nan
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- 0. 0.39635836 0.179016 0. 0.85971264 0.81216021
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- 0.92138172 0.01167807 0.1977878 0.29963924 0. ]
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- - Validation Per Category Accuracy: [0. 0.78602724 0.94880444 0.62217131 0.89442006 0.42531888
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- nan 0.59441554 0.64546467 0.03471356 0.9292238 0.
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- 0. nan 0. 0.74615423 0. 0.
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- 0.88791835 0.16198532 0.66445513 0.45227575 0. nan
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- 0. 0.4809923 0.21058637 0. 0.93914912 0.91867471
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- 0.96219496 0.02304832 0.45697186 0.35359374 0. ]
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- - Epoch: 23
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  ## Model description
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@@ -351,6 +351,17 @@ The following hyperparameters were used during training:
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  0.88791835 0.16198532 0.66445513 0.45227575 0. nan
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  0. 0.4809923 0.21058637 0. 0.93914912 0.91867471
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  0.96219496 0.02304832 0.45697186 0.35359374 0. ] | 23 |
 
 
 
 
 
 
 
 
 
 
 
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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: 0.2424
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+ - Validation Loss: 0.6093
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+ - Validation Mean Iou: 0.3307
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+ - Validation Mean Accuracy: 0.4014
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+ - Validation Overall Accuracy: 0.8467
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+ - Validation Per Category Iou: [0. 0.73958869 0.86025659 0.4755376 0.53185114 0.36403392
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+ nan 0.431977 0.51665889 0.05667583 0.82699054 0.
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+ 0. nan 0. 0.59522006 0. 0.
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+ 0.70336309 0.14633348 0.35893874 0.36236139 0. nan
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+ 0. 0.38549316 0.20212979 0. 0.85264169 0.81347649
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+ 0.91720649 0.00336927 0.18366165 0.25489549 0. ]
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+ - Validation Per Category Accuracy: [0. 0.83988126 0.94645528 0.56990742 0.68333357 0.47459971
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+ nan 0.56392528 0.71480722 0.06313103 0.921812 0.
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+ 0. nan 0. 0.79483818 0. 0.
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+ 0.87930289 0.15972854 0.44215142 0.48526807 0. nan
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+ 0. 0.49199521 0.2562916 0. 0.94459632 0.92598071
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+ 0.96917316 0.00629628 0.40341886 0.30884273 0. ]
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+ - Epoch: 24
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  ## Model description
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  0.88791835 0.16198532 0.66445513 0.45227575 0. nan
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  0. 0.4809923 0.21058637 0. 0.93914912 0.91867471
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  0.96219496 0.02304832 0.45697186 0.35359374 0. ] | 23 |
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+ | 0.2424 | 0.6093 | 0.3307 | 0.4014 | 0.8467 | [0. 0.73958869 0.86025659 0.4755376 0.53185114 0.36403392
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+ nan 0.431977 0.51665889 0.05667583 0.82699054 0.
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+ 0. nan 0. 0.59522006 0. 0.
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+ 0.70336309 0.14633348 0.35893874 0.36236139 0. nan
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+ 0. 0.38549316 0.20212979 0. 0.85264169 0.81347649
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+ 0.91720649 0.00336927 0.18366165 0.25489549 0. ] | [0. 0.83988126 0.94645528 0.56990742 0.68333357 0.47459971
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+ nan 0.56392528 0.71480722 0.06313103 0.921812 0.
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+ 0. nan 0. 0.79483818 0. 0.
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+ 0.87930289 0.15972854 0.44215142 0.48526807 0. nan
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+ 0. 0.49199521 0.2562916 0. 0.94459632 0.92598071
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+ 0.96917316 0.00629628 0.40341886 0.30884273 0. ] | 24 |
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  ### Framework versions
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