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mit-b0-finetuned-sidewalks

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sayakpaul HF staff commited on
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1 Parent(s): 789ede0

Training in progress epoch 14

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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: 0.3241
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- - Validation Loss: 0.6287
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- - Validation Mean Iou: 0.3273
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- - Validation Mean Accuracy: 0.3978
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- - Validation Overall Accuracy: 0.8429
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- - Validation Per Category Iou: [0. 0.685145 0.85514983 0.51435122 0.58568553 0.33123954
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- nan 0.37904882 0.48699633 0.01165282 0.80640467 0.
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- 0. nan 0. 0.57752157 0. 0.
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- 0.70991794 0.08028905 0.46064235 0.36005242 0. nan
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- 0. 0.35412099 0.13762468 0. 0.85041598 0.81527344
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- 0.9123073 0. 0.22657474 0.33418397 0. ]
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- - Validation Per Category Accuracy: [0. 0.76391796 0.9469649 0.63487005 0.75620599 0.46553721
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- nan 0.50872319 0.65626602 0.01264889 0.90580182 0.
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- 0. nan 0. 0.72616372 0. 0.
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- 0.890303 0.08135797 0.6078355 0.43398998 0. nan
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- 0. 0.44669122 0.16006339 0. 0.93441314 0.92555522
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- 0.96272416 0. 0.48263053 0.42826041 0. ]
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- - Epoch: 13
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  ## Model description
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@@ -229,6 +229,17 @@ The following hyperparameters were used during training:
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  0.890303 0.08135797 0.6078355 0.43398998 0. nan
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  0. 0.44669122 0.16006339 0. 0.93441314 0.92555522
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  0.96272416 0. 0.48263053 0.42826041 0. ] | 13 |
 
 
 
 
 
 
 
 
 
 
 
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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: 0.3022
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+ - Validation Loss: 0.6032
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+ - Validation Mean Iou: 0.3218
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+ - Validation Mean Accuracy: 0.3854
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+ - Validation Overall Accuracy: 0.8424
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+ - Validation Per Category Iou: [0. 0.71587478 0.85670087 0.46056474 0.53488585 0.33850716
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+ nan 0.39350336 0.39935661 0.00419527 0.79331659 0.
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+ 0. nan 0. 0.54292597 0. 0.
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+ 0.70157662 0.10836491 0.46409267 0.33272244 0. nan
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+ 0. 0.35897761 0.13052432 0. 0.85299834 0.81782186
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+ 0.9117891 0.00236702 0.25552987 0.32071305 0. ]
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+ - Validation Per Category Accuracy: [0. 0.80394187 0.9358135 0.53614593 0.72288497 0.49714062
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+ nan 0.54396953 0.50146729 0.00436756 0.94495949 0.
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+ 0. nan 0. 0.60785636 0. 0.
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+ 0.88179116 0.12443174 0.61622522 0.36928296 0. nan
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+ 0. 0.43465805 0.14865293 0. 0.95160943 0.91951241
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+ 0.96357421 0.00432258 0.41442526 0.40644768 0. ]
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+ - Epoch: 14
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  ## Model description
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  0.890303 0.08135797 0.6078355 0.43398998 0. nan
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  0. 0.44669122 0.16006339 0. 0.93441314 0.92555522
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  0.96272416 0. 0.48263053 0.42826041 0. ] | 13 |
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+ | 0.3022 | 0.6032 | 0.3218 | 0.3854 | 0.8424 | [0. 0.71587478 0.85670087 0.46056474 0.53488585 0.33850716
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+ nan 0.39350336 0.39935661 0.00419527 0.79331659 0.
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+ 0. nan 0. 0.54292597 0. 0.
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+ 0.70157662 0.10836491 0.46409267 0.33272244 0. nan
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+ 0. 0.35897761 0.13052432 0. 0.85299834 0.81782186
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+ 0.9117891 0.00236702 0.25552987 0.32071305 0. ] | [0. 0.80394187 0.9358135 0.53614593 0.72288497 0.49714062
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+ nan 0.54396953 0.50146729 0.00436756 0.94495949 0.
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+ 0. nan 0. 0.60785636 0. 0.
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+ 0.88179116 0.12443174 0.61622522 0.36928296 0. nan
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+ 0. 0.43465805 0.14865293 0. 0.95160943 0.91951241
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+ 0.96357421 0.00432258 0.41442526 0.40644768 0. ] | 14 |
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  ### Framework versions
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