andrewljohnson's picture
update model card README.md
9eedb9a
metadata
license: other
tags:
  - vision
  - image-segmentation
  - generated_from_trainer
model-index:
  - name: segformer-b5-finetuned-magic-cards-230117
    results: []

segformer-b5-finetuned-magic-cards-230117

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: 0.2096
  • 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