metadata
license: other
tags:
- vision
- image-segmentation
- generated_from_trainer
model-index:
- name: segformer-v-mesh-0
results: []
segformer-v-mesh-0
This model is a fine-tuned version of nvidia/mit-b2 on the Onegafer/vehicle_segmentation dataset. It achieves the following results on the evaluation set:
- Loss: 0.3350
- Mean Iou: 0.3373
- Mean Accuracy: 0.6746
- Overall Accuracy: 0.6746
- Accuracy Background: nan
- Accuracy Windows: 0.6746
- Iou Background: 0.0
- Iou Windows: 0.6746
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: 0.2
Training results
| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Background | Accuracy Windows | Iou Background | Iou Windows |
|---|---|---|---|---|---|---|---|---|---|---|
| 0.4394 | 0.16 | 20 | 0.3350 | 0.3373 | 0.6746 | 0.6746 | nan | 0.6746 | 0.0 | 0.6746 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3