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mrkprc1
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segformer-b0-finetuned-sudoku

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

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  1. README.md +31 -14
  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: 0.6963
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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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@@ -43,21 +43,38 @@ 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-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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  ---
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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: 1.5465
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+ - Mean Iou: 0.2407
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+ - Mean Accuracy: 0.5
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+ - Overall Accuracy: 0.4814
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+ - Accuracy Unlabelled: 1.0
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+ - Accuracy Sudoku-boundary: 0.0
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+ - Iou Unlabelled: 0.4814
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+ - Iou Sudoku-boundary: 0.0
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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-05
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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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+ | 0.6257 | 2.5 | 20 | 0.7024 | 0.2992 | 0.4856 | 0.4769 | 0.7186 | 0.2525 | 0.3981 | 0.2002 |
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+ | 0.6194 | 5.0 | 40 | 0.7513 | 0.2593 | 0.4960 | 0.4797 | 0.9332 | 0.0588 | 0.4633 | 0.0553 |
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+ | 0.6134 | 7.5 | 60 | 0.8649 | 0.2428 | 0.4993 | 0.4809 | 0.9921 | 0.0065 | 0.4792 | 0.0065 |
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+ | 0.4962 | 10.0 | 80 | 0.9245 | 0.2434 | 0.5006 | 0.4822 | 0.9949 | 0.0063 | 0.4805 | 0.0063 |
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+ | 0.5552 | 12.5 | 100 | 0.8606 | 0.2442 | 0.5009 | 0.4826 | 0.9939 | 0.0080 | 0.4804 | 0.0079 |
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+ | 0.6282 | 15.0 | 120 | 1.1507 | 0.2407 | 0.5000 | 0.4814 | 1.0000 | 0.0000 | 0.4813 | 0.0000 |
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+ | 0.4042 | 17.5 | 140 | 1.0916 | 0.2408 | 0.4997 | 0.4811 | 0.9988 | 0.0007 | 0.4810 | 0.0007 |
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+ | 0.8174 | 20.0 | 160 | 0.9731 | 0.2424 | 0.4991 | 0.4807 | 0.9926 | 0.0056 | 0.4792 | 0.0055 |
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+ | 0.5353 | 22.5 | 180 | 0.9754 | 0.2409 | 0.4991 | 0.4805 | 0.9964 | 0.0017 | 0.4801 | 0.0017 |
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+ | 0.4792 | 25.0 | 200 | 1.6835 | 0.2407 | 0.5 | 0.4814 | 1.0 | 0.0 | 0.4814 | 0.0 |
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+ | 0.4244 | 27.5 | 220 | 1.5039 | 0.2407 | 0.5 | 0.4814 | 1.0 | 0.0 | 0.4814 | 0.0 |
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+ | 0.376 | 30.0 | 240 | 2.2746 | 0.2407 | 0.5 | 0.4814 | 1.0 | 0.0 | 0.4814 | 0.0 |
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+ | 0.4129 | 32.5 | 260 | 2.0116 | 0.2407 | 0.5 | 0.4814 | 1.0 | 0.0 | 0.4814 | 0.0 |
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+ | 0.4717 | 35.0 | 280 | 1.8957 | 0.2407 | 0.5 | 0.4814 | 1.0 | 0.0 | 0.4814 | 0.0 |
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+ | 0.4229 | 37.5 | 300 | 1.7574 | 0.2407 | 0.5 | 0.4814 | 1.0 | 0.0 | 0.4814 | 0.0 |
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+ | 0.5708 | 40.0 | 320 | 2.0764 | 0.2407 | 0.5 | 0.4814 | 1.0 | 0.0 | 0.4814 | 0.0 |
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+ | 0.5826 | 42.5 | 340 | 1.6177 | 0.2407 | 0.5 | 0.4814 | 1.0 | 0.0 | 0.4814 | 0.0 |
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+ | 0.3765 | 45.0 | 360 | 1.8119 | 0.2407 | 0.5 | 0.4814 | 1.0 | 0.0 | 0.4814 | 0.0 |
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+ | 0.3704 | 47.5 | 380 | 1.6863 | 0.2407 | 0.5 | 0.4814 | 1.0 | 0.0 | 0.4814 | 0.0 |
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+ | 1.3265 | 50.0 | 400 | 1.5465 | 0.2407 | 0.5 | 0.4814 | 1.0 | 0.0 | 0.4814 | 0.0 |
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  ### Framework versions
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