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segformer-b0-finetuned-v0

Image Segmentation
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PyTorch
Safetensors
segformer
vision
Generated from Trainer
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segformer-b0-finetuned-v0 / README.md
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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-v0
    results: []

segformer-b0-finetuned-v0

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

  • Loss: 1.5847
  • Mean Iou: 0.1252
  • Mean Accuracy: 0.2052
  • Overall Accuracy: 0.2652
  • Accuracy Artery: nan
  • Accuracy Vein: 0.2256
  • Accuracy Nerve: 0.0
  • Accuracy Muscle1: 0.0
  • Accuracy Muscle2: 0.3266
  • Accuracy Muscle3: 0.0009
  • Accuracy Muscle4: 0.6780
  • Accuracy Unknown: nan
  • Iou Artery: 0.0
  • Iou Vein: 0.2256
  • Iou Nerve: 0.0
  • Iou Muscle1: 0.0
  • Iou Muscle2: 0.2135
  • Iou Muscle3: 0.0005
  • Iou Muscle4: 0.4366
  • Iou Unknown: nan

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 Artery Accuracy Vein Accuracy Nerve Accuracy Muscle1 Accuracy Muscle2 Accuracy Muscle3 Accuracy Muscle4 Accuracy Unknown Iou Artery Iou Vein Iou Nerve Iou Muscle1 Iou Muscle2 Iou Muscle3 Iou Muscle4 Iou Unknown
1.7835 10.0 10 1.9744 0.0620 0.1572 0.2117 nan 0.0834 0.0 0.0 0.2330 0.0002 0.6266 nan 0.0 0.0563 0.0 0.0 0.1422 0.0001 0.2975 0.0
1.4779 20.0 20 1.8578 0.0954 0.1794 0.2576 nan 0.0670 0.0 0.0 0.3099 0.0 0.6992 nan 0.0 0.0670 0.0 0.0 0.1857 0.0 0.4152 nan
1.3434 30.0 30 1.6759 0.1239 0.2014 0.2743 nan 0.1921 0.0 0.0 0.3566 0.0 0.6594 nan 0.0 0.1921 0.0 0.0 0.2244 0.0 0.4509 nan
1.2779 40.0 40 1.6276 0.1375 0.2263 0.3176 nan 0.2159 0.0 0.0 0.4348 0.0 0.7073 nan 0.0 0.2159 0.0 0.0 0.2784 0.0 0.4684 nan
1.1988 50.0 50 1.5847 0.1252 0.2052 0.2652 nan 0.2256 0.0 0.0 0.3266 0.0009 0.6780 nan 0.0 0.2256 0.0 0.0 0.2135 0.0005 0.4366 nan

Framework versions

  • Transformers 4.33.1
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.5
  • Tokenizers 0.13.3