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Training in progress epoch 26

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  1. README.md +41 -18
  2. tf_model.h5 +1 -1
README.md CHANGED
@@ -14,24 +14,30 @@ 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: 0.2225
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- - Validation Loss: 0.6468
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- - Validation Mean Iou: 0.3391
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- - Validation Mean Accuracy: 0.4135
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- - Validation Overall Accuracy: 0.8494
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- - Validation Per Category Iou: [0. 0.70993004 0.86487011 0.52191637 0.57664557 0.3444165
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- nan 0.43372414 0.51182778 0.08290104 0.83020271 0.
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- 0. nan 0. 0.57442713 0. 0.
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- 0.73826685 0.15668916 0.47129259 0.34339061 0. nan
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- 0. 0.37774687 0.19761191 0. 0.85313493 0.81669651
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- 0.92318268 0.00461872 0.16799491 0.34913299 0. ]
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- - Validation Per Category Accuracy: [0. 0.76188591 0.94953714 0.62857903 0.76788451 0.49450254
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- nan 0.60497833 0.66535259 0.09517867 0.92364467 0.
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- 0. nan 0. 0.74902607 0. 0.
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- 0.88590133 0.172701 0.64600271 0.4212137 0. nan
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- 0. 0.45525406 0.24234548 0. 0.93503283 0.93763733
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- 0.96721471 0.0103905 0.45387632 0.46408109 0. ]
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- - Epoch: 25
 
 
 
 
 
 
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  ## Model description
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@@ -373,6 +379,23 @@ The following hyperparameters were used during training:
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  0.88590133 0.172701 0.64600271 0.4212137 0. nan
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  0. 0.45525406 0.24234548 0. 0.93503283 0.93763733
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  0.96721471 0.0103905 0.45387632 0.46408109 0. ] | 25 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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: 0.2174
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+ - Validation Loss: 0.6628
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+ - Validation Mean Iou: 0.3253
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+ - Validation Mean Accuracy: 0.4085
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+ - Validation Overall Accuracy: 0.8481
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+ - Validation Per Category Iou: [0.00000000e+00 7.12004421e-01 8.67849109e-01 5.06086069e-01
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+ 5.33272886e-01 3.43273619e-01 nan 4.54065518e-01
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+ 5.22321577e-01 1.22861668e-01 8.23942782e-01 4.09584272e-04
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+ 0.00000000e+00 0.00000000e+00 0.00000000e+00 5.68874956e-01
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+ 0.00000000e+00 0.00000000e+00 7.18493639e-01 1.36007016e-01
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+ 4.79722113e-01 3.68024008e-01 0.00000000e+00 nan
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+ 0.00000000e+00 3.63955101e-01 1.88599214e-01 0.00000000e+00
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+ 8.48893807e-01 8.09523434e-01 9.19749594e-01 6.16287868e-03
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+ 1.59932885e-01 2.80999069e-01 0.00000000e+00]
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+ - Validation Per Category Accuracy: [0.00000000e+00 8.06451570e-01 9.46650239e-01 6.53411928e-01
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+ 6.52714160e-01 4.89195197e-01 nan 6.01258726e-01
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+ 6.95476161e-01 1.31990925e-01 9.27085524e-01 6.27598651e-04
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+ 0.00000000e+00 nan 0.00000000e+00 7.68117571e-01
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+ 0.00000000e+00 0.00000000e+00 9.05658822e-01 1.41008573e-01
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+ 5.94104088e-01 4.50813623e-01 0.00000000e+00 nan
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+ 0.00000000e+00 4.44671381e-01 2.31125198e-01 0.00000000e+00
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+ 9.31240381e-01 9.32472058e-01 9.61985230e-01 1.10266532e-02
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+ 4.52431726e-01 3.41062626e-01 0.00000000e+00]
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+ - Epoch: 26
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  ## Model description
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  0.88590133 0.172701 0.64600271 0.4212137 0. nan
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  0. 0.45525406 0.24234548 0. 0.93503283 0.93763733
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  0.96721471 0.0103905 0.45387632 0.46408109 0. ] | 25 |
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+ | 0.2174 | 0.6628 | 0.3253 | 0.4085 | 0.8481 | [0.00000000e+00 7.12004421e-01 8.67849109e-01 5.06086069e-01
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+ 5.33272886e-01 3.43273619e-01 nan 4.54065518e-01
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+ 5.22321577e-01 1.22861668e-01 8.23942782e-01 4.09584272e-04
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+ 0.00000000e+00 0.00000000e+00 0.00000000e+00 5.68874956e-01
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+ 0.00000000e+00 0.00000000e+00 7.18493639e-01 1.36007016e-01
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+ 4.79722113e-01 3.68024008e-01 0.00000000e+00 nan
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+ 0.00000000e+00 3.63955101e-01 1.88599214e-01 0.00000000e+00
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+ 8.48893807e-01 8.09523434e-01 9.19749594e-01 6.16287868e-03
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+ 1.59932885e-01 2.80999069e-01 0.00000000e+00] | [0.00000000e+00 8.06451570e-01 9.46650239e-01 6.53411928e-01
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+ 6.52714160e-01 4.89195197e-01 nan 6.01258726e-01
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+ 6.95476161e-01 1.31990925e-01 9.27085524e-01 6.27598651e-04
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+ 0.00000000e+00 nan 0.00000000e+00 7.68117571e-01
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+ 0.00000000e+00 0.00000000e+00 9.05658822e-01 1.41008573e-01
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+ 5.94104088e-01 4.50813623e-01 0.00000000e+00 nan
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+ 0.00000000e+00 4.44671381e-01 2.31125198e-01 0.00000000e+00
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+ 9.31240381e-01 9.32472058e-01 9.61985230e-01 1.10266532e-02
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+ 4.52431726e-01 3.41062626e-01 0.00000000e+00] | 26 |
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  ### Framework versions
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