readme: ---
  license: other
  tags:
  - vision
  - image-segmentation
  - generated_from_trainer
  model-index:
  - name: segformer-b5-finetuned-magic-cards-230117
    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
  
  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: 0.2096
  - Mean Iou: 0.6629
  - Mean Accuracy: 0.9944
  - Overall Accuracy: 0.9944
  - Accuracy Unlabeled: nan
  - Accuracy Front: 0.9997
  - Accuracy Back: 0.9891
  - Iou Unlabeled: 0.0
  - Iou Front: 0.9997
  - Iou Back: 0.9891
  
  ## 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: 10
  
  ### 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 |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:--------------:|:-------------:|:-------------:|:---------:|:--------:|
  | 0.496         | 0.74  | 20   | 0.4441          | 0.6552   | 0.9838        | 0.9838           | nan                | 0.9786         | 0.9890        | 0.0           | 0.9786    | 0.9869   |
  | 0.1693        | 1.48  | 40   | 0.4098          | 0.6597   | 0.9897        | 0.9897           | nan                | 0.9943         | 0.9851        | 0.0           | 0.9943    | 0.9849   |
  | 0.1172        | 2.22  | 60   | 0.2734          | 0.6582   | 0.9874        | 0.9874           | nan                | 0.9977         | 0.9770        | 0.0           | 0.9977    | 0.9770   |
  | 0.1335        | 2.96  | 80   | 0.2637          | 0.6609   | 0.9914        | 0.9914           | nan                | 0.9959         | 0.9869        | 0.0           | 0.9959    | 0.9869   |
  | 0.0781        | 3.7   | 100  | 0.5178          | 0.6644   | 0.9966        | 0.9966           | nan                | 0.9998         | 0.9933        | 0.0           | 0.9998    | 0.9933   |
  | 0.1302        | 4.44  | 120  | 0.2753          | 0.6652   | 0.9978        | 0.9978           | nan                | 0.9993         | 0.9962        | 0.0           | 0.9993    | 0.9962   |
  | 0.0688        | 5.19  | 140  | 0.1458          | 0.6618   | 0.9926        | 0.9926           | nan                | 0.9950         | 0.9903        | 0.0           | 0.9950    | 0.9903   |
  | 0.0866        | 5.93  | 160  | 0.1763          | 0.6636   | 0.9954        | 0.9954           | nan                | 0.9962         | 0.9946        | 0.0           | 0.9962    | 0.9946   |
  | 0.0525        | 6.67  | 180  | 0.1812          | 0.6627   | 0.9941        | 0.9941           | nan                | 0.9988         | 0.9895        | 0.0           | 0.9988    | 0.9895   |
  | 0.0679        | 7.41  | 200  | 0.2246          | 0.6625   | 0.9937        | 0.9937           | nan                | 0.9990         | 0.9884        | 0.0           | 0.9990    | 0.9884   |
  | 0.0424        | 8.15  | 220  | 0.2079          | 0.6623   | 0.9934        | 0.9935           | nan                | 0.9996         | 0.9873        | 0.0           | 0.9996    | 0.9873   |
  | 0.0349        | 8.89  | 240  | 0.1559          | 0.6626   | 0.9939        | 0.9940           | nan                | 0.9987         | 0.9892        | 0.0           | 0.9987    | 0.9892   |
  | 0.0357        | 9.63  | 260  | 0.2096          | 0.6629   | 0.9944        | 0.9944           | nan                | 0.9997         | 0.9891        | 0.0           | 0.9997    | 0.9891   |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.12.1
  - Datasets 2.8.0
  - Tokenizers 0.13.0.dev0
  