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Training in progress epoch 40

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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: 0.1853
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- - Validation Loss: 0.4315
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- - Validation Mean Iou: 0.3703
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- - Validation Mean Accuracy: 0.4396
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- - Validation Overall Accuracy: 0.8843
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- - Validation Per Category Iou: [0. 0.82385333 0.88384746 0.82923402 0.87047461 0.44946715
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- nan 0.50195066 0.5526193 0.13775167 0.85419626 0.11663244
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- 0. 0.24123441 0. 0.50296284 0. 0.
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- 0.75525625 0.01028213 0.42676119 0.62702595 0.06111111 nan
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- 0.01903464 0.32208879 0.27514231 0. 0.86733642 0.75225439
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- 0.93747993 0.18324185 0.01936191 0.19849636 0. ]
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- - Validation Per Category Accuracy: [0. 0.90365119 0.95252047 0.86895636 0.95780426 0.51196152
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- nan 0.66021153 0.84474181 0.20306721 0.91545736 0.16898056
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- 0. 0.37891914 0. 0.57321383 0. 0.
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- 0.86912221 0.01029375 0.54801488 0.73707468 0.06340058 nan
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- 0.02149592 0.43258561 0.31736381 0. 0.94644158 0.84006614
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- 0.97630627 0.4108325 0.04714226 0.34773038 0. ]
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- - Epoch: 39
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  ## Model description
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@@ -563,6 +563,17 @@ The following hyperparameters were used during training:
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  0.86912221 0.01029375 0.54801488 0.73707468 0.06340058 nan
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  0.02149592 0.43258561 0.31736381 0. 0.94644158 0.84006614
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  0.97630627 0.4108325 0.04714226 0.34773038 0. ] | 39 |
 
 
 
 
 
 
 
 
 
 
 
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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: 0.1750
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+ - Validation Loss: 0.4506
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+ - Validation Mean Iou: 0.3588
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+ - Validation Mean Accuracy: 0.4247
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+ - Validation Overall Accuracy: 0.8777
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+ - Validation Per Category Iou: [0. 0.8085732 0.87850952 0.80281118 0.80588458 0.43532471
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+ nan 0.49235495 0.56953178 0.04144004 0.86063777 0.1253508
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+ 0. 0.29125623 0. 0.56867524 0. 0.
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+ 0.72796854 0.03398534 0.34825502 0.58349517 0.04278075 nan
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+ 0.02356575 0.3145996 0.25091045 0. 0.86821676 0.7616297
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+ 0.94167999 0.0760155 0.01097801 0.17674597 0. ]
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+ - Validation Per Category Accuracy: [0. 0.8587409 0.96059527 0.84914689 0.95691624 0.49065318
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+ nan 0.64206647 0.80599476 0.04330176 0.94759276 0.13288378
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+ 0. 0.49401815 0. 0.68717916 0. 0.
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+ 0.83929688 0.03427065 0.62310627 0.69531488 0.04610951 nan
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+ 0.02716663 0.42729112 0.28005142 0. 0.94607512 0.87723316
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+ 0.97355068 0.11214495 0.02653317 0.23750462 0. ]
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+ - Epoch: 40
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  ## Model description
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  0.86912221 0.01029375 0.54801488 0.73707468 0.06340058 nan
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  0.02149592 0.43258561 0.31736381 0. 0.94644158 0.84006614
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  0.97630627 0.4108325 0.04714226 0.34773038 0. ] | 39 |
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+ | 0.1750 | 0.4506 | 0.3588 | 0.4247 | 0.8777 | [0. 0.8085732 0.87850952 0.80281118 0.80588458 0.43532471
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+ nan 0.49235495 0.56953178 0.04144004 0.86063777 0.1253508
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+ 0. 0.29125623 0. 0.56867524 0. 0.
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+ 0.72796854 0.03398534 0.34825502 0.58349517 0.04278075 nan
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+ 0.02356575 0.3145996 0.25091045 0. 0.86821676 0.7616297
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+ 0.94167999 0.0760155 0.01097801 0.17674597 0. ] | [0. 0.8587409 0.96059527 0.84914689 0.95691624 0.49065318
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+ nan 0.64206647 0.80599476 0.04330176 0.94759276 0.13288378
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+ 0. 0.49401815 0. 0.68717916 0. 0.
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+ 0.83929688 0.03427065 0.62310627 0.69531488 0.04610951 nan
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+ 0.02716663 0.42729112 0.28005142 0. 0.94607512 0.87723316
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+ 0.97355068 0.11214495 0.02653317 0.23750462 0. ] | 40 |
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  ### Framework versions
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