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segformer-b0-finetuned-sudoku

Image Segmentation
Transformers
Safetensors
segformer
vision
Generated from Trainer
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End of training

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  1. README.md +14 -26
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -1,10 +1,10 @@
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  ---
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  license: other
 
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  tags:
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  - vision
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  - image-segmentation
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  - generated_from_trainer
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- base_model: nvidia/mit-b0
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  model-index:
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  - name: segformer-b0-finetuned-sudoku
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  results: []
@@ -17,14 +17,14 @@ should 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 the mrkprc1/SudokuBoundaries2 dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.7037
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- - Mean Iou: 0.2505
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- - Mean Accuracy: 0.4978
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- - Overall Accuracy: 0.4887
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- - Accuracy Unlabelled: 0.9784
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- - Accuracy Sudoku-boundary: 0.0173
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- - Iou Unlabelled: 0.4841
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- - Iou Sudoku-boundary: 0.0169
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  ## Model description
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@@ -43,33 +43,21 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 6e-06
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  - train_batch_size: 2
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  - eval_batch_size: 2
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 50
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Unlabelled | Accuracy Sudoku-boundary | Iou Unlabelled | Iou Sudoku-boundary |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------:|:------------------------:|:--------------:|:-------------------:|
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- | 0.5388 | 3.33 | 20 | 0.6914 | 0.3096 | 0.5259 | 0.5336 | 0.1248 | 0.9270 | 0.1160 | 0.5031 |
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- | 1.1103 | 6.67 | 40 | 0.6909 | 0.3320 | 0.5329 | 0.5393 | 0.1982 | 0.8677 | 0.1742 | 0.4897 |
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- | 0.2978 | 10.0 | 60 | 0.6971 | 0.2671 | 0.4987 | 0.4904 | 0.9321 | 0.0653 | 0.4729 | 0.0613 |
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- | 0.4739 | 13.33 | 80 | 0.6927 | 0.3257 | 0.5147 | 0.5101 | 0.7585 | 0.2709 | 0.4316 | 0.2198 |
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- | 0.562 | 16.67 | 100 | 0.6974 | 0.2695 | 0.4975 | 0.4894 | 0.9194 | 0.0756 | 0.4690 | 0.0701 |
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- | 0.8487 | 20.0 | 120 | 0.6944 | 0.2945 | 0.5041 | 0.4974 | 0.8555 | 0.1527 | 0.4550 | 0.1341 |
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- | 0.3803 | 23.33 | 140 | 0.6953 | 0.2906 | 0.5054 | 0.4983 | 0.8768 | 0.1339 | 0.4615 | 0.1197 |
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- | 0.4106 | 26.67 | 160 | 0.7065 | 0.2482 | 0.4999 | 0.4905 | 0.9917 | 0.0081 | 0.4884 | 0.0080 |
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- | 0.4016 | 30.0 | 180 | 0.7057 | 0.2507 | 0.4988 | 0.4896 | 0.9811 | 0.0165 | 0.4853 | 0.0162 |
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- | 0.3198 | 33.33 | 200 | 0.7114 | 0.2476 | 0.4987 | 0.4893 | 0.9896 | 0.0079 | 0.4873 | 0.0078 |
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- | 0.374 | 36.67 | 220 | 0.7286 | 0.2452 | 0.4997 | 0.4901 | 0.9989 | 0.0004 | 0.4900 | 0.0004 |
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- | 0.2486 | 40.0 | 240 | 0.6986 | 0.2751 | 0.4974 | 0.4897 | 0.9002 | 0.0946 | 0.4639 | 0.0863 |
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- | 0.513 | 43.33 | 260 | 0.6917 | 0.3192 | 0.5139 | 0.5086 | 0.7909 | 0.2369 | 0.4411 | 0.1972 |
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- | 0.3839 | 46.67 | 280 | 0.6934 | 0.3002 | 0.5079 | 0.5013 | 0.8495 | 0.1662 | 0.4552 | 0.1452 |
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- | 0.6526 | 50.0 | 300 | 0.7037 | 0.2505 | 0.4978 | 0.4887 | 0.9784 | 0.0173 | 0.4841 | 0.0169 |
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  ### Framework versions
 
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  ---
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  license: other
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+ base_model: nvidia/mit-b0
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  tags:
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  - vision
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  - image-segmentation
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  - generated_from_trainer
 
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  model-index:
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  - name: segformer-b0-finetuned-sudoku
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  results: []
 
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  This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the mrkprc1/SudokuBoundaries2 dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6963
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+ - Mean Iou: 0.2715
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+ - Mean Accuracy: 0.4994
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+ - Overall Accuracy: 0.4914
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+ - Accuracy Unlabelled: 0.9207
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+ - Accuracy Sudoku-boundary: 0.0782
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+ - Iou Unlabelled: 0.4703
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+ - Iou Sudoku-boundary: 0.0726
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 6e-07
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  - train_batch_size: 2
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  - eval_batch_size: 2
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - num_epochs: 10
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Unlabelled | Accuracy Sudoku-boundary | Iou Unlabelled | Iou Sudoku-boundary |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------:|:------------------------:|:--------------:|:-------------------:|
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+ | 0.5345 | 3.33 | 20 | 0.6911 | 0.3154 | 0.5281 | 0.5355 | 0.1414 | 0.9147 | 0.1299 | 0.5008 |
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+ | 1.1081 | 6.67 | 40 | 0.6904 | 0.3388 | 0.5351 | 0.5411 | 0.2242 | 0.8460 | 0.1933 | 0.4844 |
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+ | 0.3015 | 10.0 | 60 | 0.6963 | 0.2715 | 0.4994 | 0.4914 | 0.9207 | 0.0782 | 0.4703 | 0.0726 |
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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