segformer-b0-finetuned-segments-satellite-terrain
This model is a fine-tuned version of nvidia/mit-b0 on the ZeeeWP/terrain_map_obstacle dataset. It achieves the following results on the evaluation set:
- Loss: 0.4376
- Mean Iou: 0.3519
- Mean Accuracy: 0.7038
- Overall Accuracy: 0.7038
- Accuracy Unlabeled: nan
- Accuracy Obstacle: 0.7038
- Iou Unlabeled: 0.0
- Iou Obstacle: 0.7038
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: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Unlabeled | Accuracy Obstacle | Iou Unlabeled | Iou Obstacle |
---|---|---|---|---|---|---|---|---|---|---|
0.4655 | 3.3333 | 20 | 0.5979 | 0.2393 | 0.4786 | 0.4786 | nan | 0.4786 | 0.0 | 0.4786 |
0.409 | 6.6667 | 40 | 0.5183 | 0.3392 | 0.6784 | 0.6784 | nan | 0.6784 | 0.0 | 0.6784 |
0.3966 | 10.0 | 60 | 0.4376 | 0.3519 | 0.7038 | 0.7038 | nan | 0.7038 | 0.0 | 0.7038 |
Framework versions
- Transformers 4.44.1
- Pytorch 2.4.1
- Datasets 2.14.6
- Tokenizers 0.19.1
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Base model
nvidia/mit-b0