metadata
license: other
base_model: nvidia/mit-b0
tags:
- image-segmentation
- vision
- generated_from_trainer
model-index:
- name: segformer-finetuned-obb-1k-steps
results: []
segformer-finetuned-obb-1k-steps
This model is a fine-tuned version of nvidia/mit-b0 on the Spatiallysaying/obb dataset. It achieves the following results on the evaluation set:
- Loss: 0.0511
- Mean Iou: 0.2238
- Mean Accuracy: 0.4477
- Overall Accuracy: 0.4477
- Accuracy Backgound : nan
- Accuracy Rwy Obb: 0.4477
- Iou Backgound : 0.0
- Iou Rwy Obb: 0.4477
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: 1337
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: polynomial
- training_steps: 1000
Training results
| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Backgound | Accuracy Rwy Obb | Iou Backgound | Iou Rwy Obb |
|---|---|---|---|---|---|---|---|---|---|---|
| 0.3927 | 1.0 | 173 | 0.1096 | 0.1590 | 0.3180 | 0.3180 | nan | 0.3180 | 0.0 | 0.3180 |
| 0.0969 | 2.0 | 346 | 0.0704 | 0.2112 | 0.4224 | 0.4224 | nan | 0.4224 | 0.0 | 0.4224 |
| 0.0651 | 3.0 | 519 | 0.0598 | 0.2186 | 0.4371 | 0.4371 | nan | 0.4371 | 0.0 | 0.4371 |
| 0.0576 | 4.0 | 692 | 0.0530 | 0.2250 | 0.4500 | 0.4500 | nan | 0.4500 | 0.0 | 0.4500 |
| 0.0531 | 5.0 | 865 | 0.0529 | 0.2212 | 0.4424 | 0.4424 | nan | 0.4424 | 0.0 | 0.4424 |
| 0.0467 | 5.7803 | 1000 | 0.0511 | 0.2238 | 0.4477 | 0.4477 | nan | 0.4477 | 0.0 | 0.4477 |
Framework versions
- Transformers 4.43.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1