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mit-b0-finetuned-sidewalks

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sayakpaul HF staff commited on
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1 Parent(s): b07f200

Training in progress epoch 15

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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: 0.3022
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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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@@ -240,6 +240,17 @@ The following hyperparameters were used during training:
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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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  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: 0.2937
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+ - Validation Loss: 0.5953
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+ - Validation Mean Iou: 0.3305
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+ - Validation Mean Accuracy: 0.4030
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+ - Validation Overall Accuracy: 0.8449
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+ - Validation Per Category Iou: [0. 0.69638318 0.85825162 0.52324422 0.5433419 0.3469765
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+ nan 0.40975989 0.49170959 0.00172109 0.81852012 0.
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+ 0. nan 0. 0.54972175 0. 0.
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+ 0.72653579 0.12940395 0.49040852 0.36779631 0. nan
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+ 0. 0.34952524 0.12859991 0. 0.84955571 0.82163775
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+ 0.91348544 0.01357343 0.20901572 0.33696003 0. ]
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+ - Validation Per Category Accuracy: [0. 0.77149692 0.93467369 0.62786344 0.75698164 0.52205905
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+ nan 0.57849458 0.72399102 0.0020987 0.92177615 0.
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+ 0. nan 0. 0.66111028 0. 0.
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+ 0.89225829 0.13292311 0.62957849 0.44703839 0. nan
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+ 0. 0.41933079 0.14719493 0. 0.94294399 0.92316157
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+ 0.95997955 0.02286889 0.43984316 0.43884091 0. ]
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+ - Epoch: 15
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  ## Model description
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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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+ | 0.2937 | 0.5953 | 0.3305 | 0.4030 | 0.8449 | [0. 0.69638318 0.85825162 0.52324422 0.5433419 0.3469765
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+ nan 0.40975989 0.49170959 0.00172109 0.81852012 0.
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+ 0. nan 0. 0.54972175 0. 0.
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+ 0.72653579 0.12940395 0.49040852 0.36779631 0. nan
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+ 0. 0.34952524 0.12859991 0. 0.84955571 0.82163775
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+ 0.91348544 0.01357343 0.20901572 0.33696003 0. ] | [0. 0.77149692 0.93467369 0.62786344 0.75698164 0.52205905
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+ nan 0.57849458 0.72399102 0.0020987 0.92177615 0.
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+ 0. nan 0. 0.66111028 0. 0.
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+ 0.89225829 0.13292311 0.62957849 0.44703839 0. nan
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+ 0. 0.41933079 0.14719493 0. 0.94294399 0.92316157
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+ 0.95997955 0.02286889 0.43984316 0.43884091 0. ] | 15 |
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  ### Framework versions
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