readme: ---
  license: other
  tags:
  - vision
  - image-segmentation
  - generated_from_trainer
  model-index:
  - name: segformer-b5-finetuned-magic-cards-230117-2
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # segformer-b5-finetuned-magic-cards-230117-2
  
  This model is a fine-tuned version of [nvidia/mit-b5](https://huggingface.co/nvidia/mit-b5) on the andrewljohnson/magic_cards dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0491
  - Mean Iou: 0.6649
  - Mean Accuracy: 0.9974
  - Overall Accuracy: 0.9972
  - Accuracy Unlabeled: nan
  - Accuracy Front: 0.9990
  - Accuracy Back: 0.9957
  - Iou Unlabeled: 0.0
  - Iou Front: 0.9990
  - Iou Back: 0.9957
  
  ## 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: 1
  - eval_batch_size: 1
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Unlabeled | Accuracy Front | Accuracy Back | Iou Unlabeled | Iou Front | Iou Back |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:--------------:|:-------------:|:-------------:|:---------:|:--------:|
  | 0.5968        | 0.33  | 20   | 0.4422          | 0.6366   | 0.9701        | 0.9690           | nan                | 0.9812         | 0.9590        | 0.0           | 0.9507    | 0.9590   |
  | 0.8955        | 0.66  | 40   | 0.2353          | 0.6496   | 0.9819        | 0.9807           | nan                | 0.9944         | 0.9695        | 0.0           | 0.9792    | 0.9695   |
  | 0.1269        | 0.98  | 60   | 0.1739          | 0.6566   | 0.9922        | 0.9916           | nan                | 0.9979         | 0.9866        | 0.0           | 0.9832    | 0.9866   |
  | 0.7629        | 1.31  | 80   | 0.1664          | 0.6561   | 0.9915        | 0.9909           | nan                | 0.9975         | 0.9856        | 0.0           | 0.9826    | 0.9856   |
  | 0.106         | 1.64  | 100  | 0.1005          | 0.6641   | 0.9968        | 0.9967           | nan                | 0.9978         | 0.9959        | 0.0           | 0.9966    | 0.9959   |
  | 0.3278        | 1.97  | 120  | 0.0577          | 0.6632   | 0.9948        | 0.9947           | nan                | 0.9963         | 0.9934        | 0.0           | 0.9963    | 0.9934   |
  | 0.061         | 2.3   | 140  | 0.0655          | 0.6642   | 0.9963        | 0.9962           | nan                | 0.9972         | 0.9953        | 0.0           | 0.9972    | 0.9953   |
  | 0.0766        | 2.62  | 160  | 0.0470          | 0.6635   | 0.9953        | 0.9954           | nan                | 0.9940         | 0.9966        | 0.0           | 0.9940    | 0.9966   |
  | 0.0664        | 2.95  | 180  | 0.0436          | 0.6617   | 0.9926        | 0.9931           | nan                | 0.9877         | 0.9975        | 0.0           | 0.9877    | 0.9975   |
  | 0.0655        | 3.28  | 200  | 0.0632          | 0.6649   | 0.9973        | 0.9971           | nan                | 0.9994         | 0.9953        | 0.0           | 0.9994    | 0.9953   |
  | 0.0356        | 3.61  | 220  | 0.0755          | 0.6661   | 0.9991        | 0.9991           | nan                | 0.9992         | 0.9991        | 0.0           | 0.9992    | 0.9991   |
  | 0.0516        | 3.93  | 240  | 0.0470          | 0.6643   | 0.9965        | 0.9963           | nan                | 0.9987         | 0.9943        | 0.0           | 0.9987    | 0.9943   |
  | 0.0517        | 4.26  | 260  | 0.0481          | 0.6645   | 0.9967        | 0.9965           | nan                | 0.9989         | 0.9945        | 0.0           | 0.9989    | 0.9945   |
  | 0.1886        | 4.59  | 280  | 0.0823          | 0.6659   | 0.9988        | 0.9987           | nan                | 0.9999         | 0.9977        | 0.0           | 0.9999    | 0.9977   |
  | 0.0453        | 4.92  | 300  | 0.0491          | 0.6649   | 0.9974        | 0.9972           | nan                | 0.9990         | 0.9957        | 0.0           | 0.9990    | 0.9957   |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.12.1
  - Datasets 2.8.0
  - Tokenizers 0.13.0.dev0
  