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mit-b0-finetuned-sidewalks

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sayakpaul HF staff commited on
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25c3525
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1 Parent(s): 5c12649

Training in progress epoch 3

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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: 0.7280
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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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@@ -96,6 +96,17 @@ The following hyperparameters were used during training:
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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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  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: 0.6505
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+ - Validation Loss: 0.6601
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+ - Validation Mean Iou: 0.2774
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+ - Validation Mean Accuracy: 0.3400
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+ - Validation Overall Accuracy: 0.8158
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+ - Validation Per Category Iou: [0. 0.67274147 0.83098512 0.46721789 0.48492165 0.28810209
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+ nan 0.30676731 0.41116935 0. 0.73679658 0.
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+ 0. nan 0. 0.47421792 0. 0.
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+ 0.66232704 0. 0.40729478 0.27226345 0. nan
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+ 0. 0.22211219 0.00310618 0. 0.81170746 0.73786496
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+ 0.88368738 0. 0.07716099 0.12776685 0. ]
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+ - Validation Per Category Accuracy: [0. 0.80048159 0.93309497 0.558633 0.56439564 0.38053253
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+ nan 0.46424754 0.60183499 0. 0.92479351 0.
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+ 0. nan 0. 0.60493457 0. 0.
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+ 0.88399244 0. 0.55428873 0.34754253 0. nan
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+ 0. 0.25438648 0.00310618 0. 0.90931833 0.91190458
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+ 0.94609539 0. 0.08323588 0.15250888 0. ]
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+ - Epoch: 3
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  ## Model description
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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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+ | 0.6505 | 0.6601 | 0.2774 | 0.3400 | 0.8158 | [0. 0.67274147 0.83098512 0.46721789 0.48492165 0.28810209
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+ nan 0.30676731 0.41116935 0. 0.73679658 0.
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+ 0. nan 0. 0.47421792 0. 0.
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+ 0.66232704 0. 0.40729478 0.27226345 0. nan
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+ 0. 0.22211219 0.00310618 0. 0.81170746 0.73786496
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+ 0.88368738 0. 0.07716099 0.12776685 0. ] | [0. 0.80048159 0.93309497 0.558633 0.56439564 0.38053253
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+ nan 0.46424754 0.60183499 0. 0.92479351 0.
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+ 0. nan 0. 0.60493457 0. 0.
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+ 0.88399244 0. 0.55428873 0.34754253 0. nan
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+ 0. 0.25438648 0.00310618 0. 0.90931833 0.91190458
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+ 0.94609539 0. 0.08323588 0.15250888 0. ] | 3 |
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  ### Framework versions
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