End of training
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- model.safetensors +1 -1
- training_args.bin +1 -1
README.md
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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: []
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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.
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- Mean Iou: 0.
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- Mean Accuracy: 0.
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- Overall Accuracy: 0.
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- Accuracy Unlabelled: 0.
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- Accuracy Sudoku-boundary: 0.
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- Iou Unlabelled: 0.
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- Iou Sudoku-boundary: 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:
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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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| 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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### 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: 0.7037
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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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### 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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| 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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model.safetensors
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training_args.bin
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