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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
a702506
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1 Parent(s): 6fee2d2

Training in progress epoch 2

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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: 0.8462
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- - Validation Loss: 0.6135
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- - Validation Mean Iou: 0.2551
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- - Validation Mean Accuracy: 0.2960
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- - Validation Overall Accuracy: 0.8200
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- - Validation Per Category Iou: [0. 0.66967645 0.80571406 0.56416239 0.66692248 0.24744912
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- nan 0.23994505 0.28962463 0. 0.76504783 0.
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- 0.6924468 0. 0.27988701 0.41876094 0. nan
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- 0. 0.14755829 0. 0. 0.81614463 0.68429711
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- 0.87710938 0. 0. 0.11234171 0. ]
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- - Validation Per Category Accuracy: [0. 0.83805933 0.94928385 0.59586511 0.72913519 0.30595504
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- nan 0.3128234 0.34805831 0. 0.87847495 0.
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- 0. 0. 0. 0.14205167 0. 0.
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- 0.87543619 0. 0.36001144 0.49498574 0. nan
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- 0. 0.18179115 0. 0. 0.92867923 0.7496178
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- 0.92220166 0. 0. 0.15398549 0. ]
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- - Epoch: 1
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  ## Model description
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@@ -79,6 +79,17 @@ The following hyperparameters were used during training:
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  0.87543619 0. 0.36001144 0.49498574 0. nan
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  0. 0.18179115 0. 0. 0.92867923 0.7496178
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  0.92220166 0. 0. 0.15398549 0. ] | 1 |
 
 
 
 
 
 
 
 
 
 
 
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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: 0.7134
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+ - Validation Loss: 0.5660
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+ - Validation Mean Iou: 0.2780
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+ - Validation Mean Accuracy: 0.3320
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+ - Validation Overall Accuracy: 0.8286
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+ - Validation Per Category Iou: [0. 0.64791461 0.83800512 0.67301044 0.68120631 0.27361472
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+ nan 0.26715802 0.43596999 0. 0.78649287 0.
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+ 0. 0. 0. 0.41256964 0. 0.
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+ 0.71114766 0. 0.31646321 0.44682442 0. nan
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+ 0. 0.17132551 0. 0. 0.81845697 0.67536699
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+ 0.88940936 0. 0. 0.1304862 0. ]
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+ - Validation Per Category Accuracy: [0. 0.85958877 0.92084269 0.82341633 0.74725972 0.33495972
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+ nan 0.40755277 0.56591531 0. 0.90641721 0.
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+ 0. 0. 0. 0.48144408 0. 0.
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+ 0.88294811 0. 0.46962078 0.47517397 0. nan
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+ 0. 0.20631607 0. 0. 0.90956851 0.85856042
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+ 0.94107052 0. 0. 0.16669713 0. ]
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+ - Epoch: 2
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  ## Model description
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  0.87543619 0. 0.36001144 0.49498574 0. nan
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  0. 0.18179115 0. 0. 0.92867923 0.7496178
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  0.92220166 0. 0. 0.15398549 0. ] | 1 |
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+ | 0.7134 | 0.5660 | 0.2780 | 0.3320 | 0.8286 | [0. 0.64791461 0.83800512 0.67301044 0.68120631 0.27361472
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+ nan 0.26715802 0.43596999 0. 0.78649287 0.
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+ 0. 0. 0. 0.41256964 0. 0.
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+ 0.71114766 0. 0.31646321 0.44682442 0. nan
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+ 0. 0.17132551 0. 0. 0.81845697 0.67536699
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+ 0.88940936 0. 0. 0.1304862 0. ] | [0. 0.85958877 0.92084269 0.82341633 0.74725972 0.33495972
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+ nan 0.40755277 0.56591531 0. 0.90641721 0.
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+ 0. 0. 0. 0.48144408 0. 0.
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+ 0.88294811 0. 0.46962078 0.47517397 0. nan
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+ 0. 0.20631607 0. 0. 0.90956851 0.85856042
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+ 0.94107052 0. 0. 0.16669713 0. ] | 2 |
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  ### Framework versions
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