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segformer-b0-finetuned-segments-satellite-terrain
ZeeeWP/segformer-b0-finetuned-segments-satellite-terrain
segformer-b0-finetuned-segments-satellite-terrain is a image segmentation model from ZeeeWP. Use it for the image segmentation task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as other.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Image Segmentation
- Library
- transformers
- License
- other
- Model type
- segformer
- Access
- Public
- Created
- Sep 19, 2024
- Updated
- Oct 30, 2025
- SHA
- 627f1361
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
segformer-b0-finetuned-segments-satellite-terrain
This model is a fine-tuned version of nvidia/mit-b0 on the ZeeeWP/terrain_map dataset. It achieves the following results on the evaluation set:
- Loss: 1.7429
- Mean Iou: 0.1997
- Mean Accuracy: 0.3405
- Overall Accuracy: 0.5221
- Accuracy Unlabeled: nan
- Accuracy Sand: 0.5941
- Accuracy Cliff: 0.5946
- Accuracy Bedrock flat: 0.7071
- Accuracy Bedrock lowhill: 0.0427
- Accuracy Bedrock highhill: 0.0
- Accuracy Gravel low hill: 0.4448
- Accuracy Gravel high hill: 0.0
- Iou Unlabeled: 0.0
- Iou Sand: 0.4244
- Iou Cliff: 0.4248
- Iou Bedrock flat: 0.4794
- Iou Bedrock lowhill: 0.0361
- Iou Bedrock highhill: 0.0
- Iou Gravel low hill: 0.2331
- Iou Gravel high hill: 0.0
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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Unlabeled | Accuracy Sand | Accuracy Cliff | Accuracy Bedrock flat | Accuracy Bedrock lowhill | Accuracy Bedrock highhill | Accuracy Gravel low hill | Accuracy Gravel high hill | Iou Unlabeled | Iou Sand | Iou Cliff | Iou Bedrock flat | Iou Bedrock lowhill | Iou Bedrock highhill | Iou Gravel low hill | Iou Gravel high hill |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1.6036 | 5.0 | 20 | 1.9238 | 0.1884 | 0.3339 | 0.5327 | nan | 0.5982 | 0.7346 | 0.6854 | 0.0081 | 0.0 | 0.3108 | 0.0 | 0.0 | 0.3493 | 0.4685 | 0.4768 | 0.0070 | 0.0 | 0.2055 | 0.0 |
| 1.7105 | 10.0 | 40 | 1.7429 | 0.1997 | 0.3405 | 0.5221 | nan | 0.5941 | 0.5946 | 0.7071 | 0.0427 | 0.0 | 0.4448 | 0.0 | 0.0 | 0.4244 | 0.4248 | 0.4794 | 0.0361 | 0.0 | 0.2331 | 0.0 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
- Task
- Image Segmentation
- Library
- transformers
- Type
- segformer
- License
- other
- Created
- Sep 19, 2024
- Updated
- Oct 30, 2025