segformerSAAD / README.md
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metadata
license: other
base_model: nvidia/mit-b0
tags:
  - vision
  - image-segmentation
  - generated_from_trainer
model-index:
  - name: segformerSAAD
    results: []

segformerSAAD

This model is a fine-tuned version of nvidia/mit-b0 on the saad7489/SixGUN dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7611
  • Mean Iou: 0.5823
  • Mean Accuracy: 0.8994
  • Overall Accuracy: 0.9474
  • Accuracy Bkg: 0.9505
  • Accuracy Knife: 0.8767
  • Accuracy Gun: 0.8711
  • Iou Bkg: 0.9471
  • Iou Knife: 0.4452
  • Iou Gun: 0.3544

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: 20
  • eval_batch_size: 20
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 30

Training results

Training Loss Epoch Step Validation Loss Mean Iou Mean Accuracy Overall Accuracy Accuracy Bkg Accuracy Knife Accuracy Gun Iou Bkg Iou Knife Iou Gun
0.9115 10.0 20 1.0252 0.5076 0.9065 0.9181 0.9188 0.8625 0.9382 0.9176 0.3218 0.2833
0.766 20.0 40 0.8278 0.5811 0.8914 0.9486 0.9523 0.8691 0.8527 0.9485 0.4288 0.3661
0.7862 30.0 60 0.7611 0.5823 0.8994 0.9474 0.9505 0.8767 0.8711 0.9471 0.4452 0.3544

Framework versions

  • Transformers 4.42.4
  • Pytorch 2.3.1+cu121
  • Datasets 2.21.0
  • Tokenizers 0.19.1