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segformer_finetuned_coasts

Image Segmentation
Transformers
PyTorch
segformer
vision
Generated from Trainer
Inference Endpoints
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segformer_finetuned_coasts / README.md
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metadata
license: other
base_model: nvidia/segformer-b0-finetuned-ade-512-512
tags:
  - vision
  - image-segmentation
  - generated_from_trainer
model-index:
  - name: segformer_finetuned_coasts
    results: []

segformer_finetuned_coasts

This model is a fine-tuned version of nvidia/segformer-b0-finetuned-ade-512-512 on the peldrak/coast dataset. It achieves the following results on the evaluation set:

  • Loss: 0.9618
  • Mean Iou: 0.2104
  • Mean Accuracy: 0.2661
  • Overall Accuracy: 0.7259
  • Accuracy Water: nan
  • Accuracy Whitewater: 0.0519
  • Accuracy Sediment: 0.0150
  • Accuracy Other Natural Terrain: 0.0024
  • Accuracy Vegetation: 0.5470
  • Accuracy Development: 0.0259
  • Accuracy Unknown: 0.9547
  • Iou Water: 0.0
  • Iou Whitewater: 0.0160
  • Iou Sediment: 0.0134
  • Iou Other Natural Terrain: 0.0022
  • Iou Vegetation: 0.4628
  • Iou Development: 0.0254
  • Iou Unknown: 0.9532

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: 4
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 0.05

Training results

Training Loss Epoch Step Validation Loss Mean Iou Mean Accuracy Overall Accuracy Accuracy Water Accuracy Whitewater Accuracy Sediment Accuracy Other Natural Terrain Accuracy Vegetation Accuracy Development Accuracy Unknown Iou Water Iou Whitewater Iou Sediment Iou Other Natural Terrain Iou Vegetation Iou Development Iou Unknown
1.7548 0.01 20 1.3306 0.1980 0.3291 0.6833 nan 0.5156 0.0933 0.0701 0.2872 0.0553 0.9531 0.0 0.0267 0.0755 0.0363 0.2664 0.0349 0.9461
1.5812 0.02 40 1.0977 0.2226 0.2976 0.7293 nan 0.1333 0.0446 0.0449 0.5497 0.0618 0.9509 0.0 0.0191 0.0357 0.0298 0.4724 0.0520 0.9489
1.3861 0.04 60 1.0240 0.2251 0.2920 0.7480 nan 0.0760 0.0161 0.0261 0.6433 0.0341 0.9564 0.0 0.0162 0.0144 0.0189 0.5387 0.0327 0.9549
1.023 0.05 80 0.9618 0.2104 0.2661 0.7259 nan 0.0519 0.0150 0.0024 0.5470 0.0259 0.9547 0.0 0.0160 0.0134 0.0022 0.4628 0.0254 0.9532

Framework versions

  • Transformers 4.33.0
  • Pytorch 2.0.0
  • Datasets 2.1.0
  • Tokenizers 0.13.3