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Training in progress epoch 8

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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: 0.4528
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- - Validation Loss: 0.6340
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- - Validation Mean Iou: 0.2980
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- - Validation Mean Accuracy: 0.3664
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- - Validation Overall Accuracy: 0.8212
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- - Validation Per Category Iou: [0. 0.60868123 0.83498291 0.18287132 0.46939835 0.31058578
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- nan 0.34162709 0.445366 0. 0.78966215 0.
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- 0. nan 0. 0.53583212 0. 0.
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- 0.71233622 0.03447214 0.47235409 0.37419598 0. nan
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- 0. 0.32268508 0.05312127 0. 0.83874416 0.79217023
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- 0.89975806 0.00192312 0.20492869 0.31166384 0. ]
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- - Validation Per Category Accuracy: [0. 0.70588336 0.94249106 0.19298309 0.73275474 0.44094168
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- nan 0.48341533 0.71859918 0. 0.90854187 0.
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- 0. nan 0. 0.6752697 0. 0.
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- 0.88312382 0.03451747 0.65575793 0.42127597 0. nan
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- 0. 0.39094462 0.05356577 0. 0.95291962 0.86480438
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- 0.95973926 0.00251199 0.29803261 0.40525743 0. ]
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- - Epoch: 7
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  ## Model description
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@@ -151,6 +151,17 @@ The following hyperparameters were used during training:
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  0.88312382 0.03451747 0.65575793 0.42127597 0. nan
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  0. 0.39094462 0.05356577 0. 0.95291962 0.86480438
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  0.95973926 0.00251199 0.29803261 0.40525743 0. ] | 7 |
 
 
 
 
 
 
 
 
 
 
 
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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: 0.4458
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+ - Validation Loss: 0.6356
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+ - Validation Mean Iou: 0.3066
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+ - Validation Mean Accuracy: 0.3759
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+ - Validation Overall Accuracy: 0.8311
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+ - Validation Per Category Iou: [0. 0.66186021 0.83364406 0.48364478 0.53627121 0.27582606
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+ nan 0.35739504 0.41076225 0. 0.77850446 0.
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+ 0. nan 0. 0.50299945 0. 0.
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+ 0.70340595 0.01741996 0.40137463 0.32885851 0. nan
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+ 0. 0.32114603 0.05439069 0. 0.84655176 0.80081688
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+ 0.90314194 0.00292704 0.24599153 0.34524384 0. ]
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+ - Validation Per Category Accuracy: [0. 0.74699777 0.95226432 0.65030589 0.70566846 0.35272168
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+ nan 0.47019568 0.71372001 0. 0.91011138 0.
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+ 0. nan 0. 0.62189092 0. 0.
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+ 0.87945472 0.01742109 0.52016264 0.36958738 0. nan
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+ 0. 0.3993222 0.05508716 0. 0.928178 0.89821483
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+ 0.96116851 0.0033765 0.40579212 0.46633448 0. ]
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+ - Epoch: 8
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  ## Model description
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  0.88312382 0.03451747 0.65575793 0.42127597 0. nan
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  0. 0.39094462 0.05356577 0. 0.95291962 0.86480438
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  0.95973926 0.00251199 0.29803261 0.40525743 0. ] | 7 |
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+ | 0.4458 | 0.6356 | 0.3066 | 0.3759 | 0.8311 | [0. 0.66186021 0.83364406 0.48364478 0.53627121 0.27582606
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+ nan 0.35739504 0.41076225 0. 0.77850446 0.
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+ 0. nan 0. 0.50299945 0. 0.
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+ 0.70340595 0.01741996 0.40137463 0.32885851 0. nan
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+ 0. 0.32114603 0.05439069 0. 0.84655176 0.80081688
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+ 0.90314194 0.00292704 0.24599153 0.34524384 0. ] | [0. 0.74699777 0.95226432 0.65030589 0.70566846 0.35272168
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+ nan 0.47019568 0.71372001 0. 0.91011138 0.
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+ 0. nan 0. 0.62189092 0. 0.
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+ 0.87945472 0.01742109 0.52016264 0.36958738 0. nan
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+ 0. 0.3993222 0.05508716 0. 0.928178 0.89821483
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+ 0.96116851 0.0033765 0.40579212 0.46633448 0. ] | 8 |
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  ### Framework versions
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