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mit-b0-finetuned-sidewalks

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sayakpaul HF staff commited on
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5c12649
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1 Parent(s): 728c45a

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: 0.8850
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- - Validation Loss: 0.7741
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- - Validation Mean Iou: 0.2215
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- - Validation Mean Accuracy: 0.2711
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- - Validation Overall Accuracy: 0.7807
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- - Validation Per Category Iou: [0. 0.56319416 0.79436978 0.22447649 0.37746306 0.2182132
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- nan 0.17433499 0.35240193 0. 0.64391654 0.
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- 0. nan 0. 0. 0. 0.
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- 0.61824159 0. 0.36925143 0.09610409 0. nan
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- 0. 0.23049759 0. 0. 0.79662258 0.72121144
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- 0.85940151 0. 0.00144295 0.04769959 0. ]
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- - Validation Per Category Accuracy: [0. 0.7334003 0.94650286 0.24751216 0.4478931 0.27208929
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- nan 0.22448353 0.45667969 0. 0.92555657 0.
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- 0. nan 0. 0. 0. 0.
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- 0.85871282 0. 0.43579563 0.09928831 0. nan
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- 0. 0.25660062 0. 0. 0.93127726 0.85151776
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- 0.9323404 0. 0.00144459 0.05442322 0. ]
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- - Epoch: 1
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  ## Model description
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@@ -85,6 +85,17 @@ The following hyperparameters were used during training:
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  0.85871282 0. 0.43579563 0.09928831 0. nan
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  0. 0.25660062 0. 0. 0.93127726 0.85151776
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  0.9323404 0. 0.00144459 0.05442322 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: 0.7280
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+ - Validation Loss: 0.6948
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+ - Validation Mean Iou: 0.2608
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+ - Validation Mean Accuracy: 0.3178
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+ - Validation Overall Accuracy: 0.8009
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+ - Validation Per Category Iou: [0. 0.5833859 0.81088427 0.37870695 0.42920979 0.26901769
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+ nan 0.26967864 0.37309309 0. 0.73143999 0.
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+ 0. nan 0. 0.30875952 0. 0.
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+ 0.64460152 0. 0.36681761 0.20754432 0. nan
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+ 0. 0.27251923 0.01267829 0. 0.82057447 0.76705857
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+ 0.86538224 0. 0.13369659 0.09996937 0. ]
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+ - Validation Per Category Accuracy: [0. 0.71016102 0.95278314 0.44786052 0.50520329 0.32109583
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+ nan 0.37049571 0.63857903 0. 0.88589428 0.
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+ 0. nan 0. 0.34012586 0. 0.
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+ 0.88972948 0. 0.49551485 0.25354461 0. nan
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+ 0. 0.3309279 0.01267829 0. 0.93305477 0.86649237
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+ 0.94355496 0. 0.14937745 0.12218876 0. ]
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+ - Epoch: 2
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  ## Model description
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  0.85871282 0. 0.43579563 0.09928831 0. nan
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  0. 0.25660062 0. 0. 0.93127726 0.85151776
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  0.9323404 0. 0.00144459 0.05442322 0. ] | 1 |
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+ | 0.7280 | 0.6948 | 0.2608 | 0.3178 | 0.8009 | [0. 0.5833859 0.81088427 0.37870695 0.42920979 0.26901769
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+ nan 0.26967864 0.37309309 0. 0.73143999 0.
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+ 0. nan 0. 0.30875952 0. 0.
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+ 0.64460152 0. 0.36681761 0.20754432 0. nan
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+ 0. 0.27251923 0.01267829 0. 0.82057447 0.76705857
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+ 0.86538224 0. 0.13369659 0.09996937 0. ] | [0. 0.71016102 0.95278314 0.44786052 0.50520329 0.32109583
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+ nan 0.37049571 0.63857903 0. 0.88589428 0.
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+ 0. nan 0. 0.34012586 0. 0.
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+ 0.88972948 0. 0.49551485 0.25354461 0. nan
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+ 0. 0.3309279 0.01267829 0. 0.93305477 0.86649237
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+ 0.94355496 0. 0.14937745 0.12218876 0. ] | 2 |
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  ### Framework versions
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