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segformer-b0-finetuned-sudoku

Image Segmentation
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segformer
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metadata
license: other
base_model: nvidia/mit-b0
tags:
  - vision
  - image-segmentation
  - generated_from_trainer
model-index:
  - name: segformer-b0-finetuned-sudoku
    results: []

segformer-b0-finetuned-sudoku

This model is a fine-tuned version of nvidia/mit-b0 on the mrkprc1/SudokuBoundaries2 dataset. It achieves the following results on the evaluation set:

  • Loss: 1.5465
  • Mean Iou: 0.2407
  • Mean Accuracy: 0.5
  • Overall Accuracy: 0.4814
  • Accuracy Unlabelled: 1.0
  • Accuracy Sudoku-boundary: 0.0
  • Iou Unlabelled: 0.4814
  • Iou Sudoku-boundary: 0.0

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 6e-05
  • train_batch_size: 2
  • eval_batch_size: 2
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 50

Training results

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

Framework versions

  • Transformers 4.37.1
  • Pytorch 2.1.2
  • Datasets 2.16.1
  • Tokenizers 0.15.1