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segformer-b5-finetuned-magic-cards-230117-3

Image Segmentation
Transformers
PyTorch
segformer
vision
Generated from Trainer
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segformer-b5-finetuned-magic-cards-230117-3 / README.md
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metadata
license: other
tags:
  - vision
  - image-segmentation
  - generated_from_trainer
model-index:
  - name: segformer-b5-finetuned-magic-cards-230117-3
    results: []

segformer-b5-finetuned-magic-cards-230117-3

This model is a fine-tuned version of nvidia/mit-b5 on the andrewljohnson/magic_cards dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0691
  • Mean Iou: 0.6585
  • Mean Accuracy: 0.9878
  • Overall Accuracy: 0.9912
  • Accuracy Unlabeled: nan
  • Accuracy Front: 0.9978
  • Accuracy Back: 0.9777
  • Iou Unlabeled: 0.0
  • Iou Front: 0.9978
  • Iou Back: 0.9777

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
1.2232 0.37 20 0.4691 0.6041 0.9201 0.9218 nan 0.9252 0.9150 0.0 0.9252 0.8870
0.2718 0.74 40 0.1983 0.6509 0.9764 0.9785 nan 0.9826 0.9702 0.0 0.9826 0.9702
0.255 1.11 60 0.0939 0.6524 0.9785 0.9794 nan 0.9812 0.9758 0.0 0.9812 0.9758
0.1103 1.48 80 0.0682 0.6536 0.9804 0.9813 nan 0.9830 0.9779 0.0 0.9830 0.9779
0.1373 1.85 100 0.1260 0.6631 0.9946 0.9961 nan 0.9989 0.9903 0.0 0.9989 0.9903
0.0566 2.22 120 0.1558 0.6578 0.9868 0.9912 nan 0.9999 0.9736 0.0 0.9999 0.9736
0.1535 2.59 140 0.1330 0.6558 0.9838 0.9883 nan 0.9973 0.9703 0.0 0.9973 0.9703
0.0586 2.96 160 0.2317 0.6599 0.9899 0.9933 nan 1.0000 0.9798 0.0 1.0000 0.9798
0.0727 3.33 180 0.1018 0.6586 0.9880 0.9919 nan 0.9995 0.9764 0.0 0.9995 0.9764
0.3588 3.7 200 0.1151 0.6608 0.9912 0.9939 nan 0.9993 0.9831 0.0 0.9993 0.9831
0.0463 4.07 220 0.0538 0.6610 0.9915 0.9934 nan 0.9969 0.9862 0.0 0.9969 0.9862
0.046 4.44 240 0.1201 0.6581 0.9871 0.9912 nan 0.9991 0.9751 0.0 0.9991 0.9751
0.0468 4.81 260 0.0691 0.6585 0.9878 0.9912 nan 0.9978 0.9777 0.0 0.9978 0.9777

Framework versions

  • Transformers 4.25.1
  • Pytorch 1.12.1
  • Datasets 2.8.0
  • Tokenizers 0.13.0.dev0