|
--- |
|
license: other |
|
base_model: nvidia/segformer-b0-finetuned-ade-512-512 |
|
tags: |
|
- vision |
|
- image-segmentation |
|
- generated_from_trainer |
|
model-index: |
|
- name: segformer-b0-finetuned-deprem-satellite |
|
results: [] |
|
widget: |
|
- src: >- |
|
https://datasets-server.huggingface.co/assets/deprem-ml/deprem_satellite_semantic_whu_dataset/--/default/train/3/image/image.jpg |
|
example_title: Example 1 |
|
- src: >- |
|
https://datasets-server.huggingface.co/assets/deprem-ml/deprem_satellite_semantic_whu_dataset/--/default/train/9/image/image.jpg |
|
example_title: Example 2 |
|
datasets: |
|
- deprem-ml/deprem_satellite_semantic_whu_dataset |
|
--- |
|
|
|
<!-- 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-deprem-satellite |
|
|
|
This model is a fine-tuned version of [nvidia/segformer-b0-finetuned-ade-512-512](https://huggingface.co/nvidia/segformer-b0-finetuned-ade-512-512) on the deprem-ml/deprem_satellite_semantic_whu_dataset dataset. |
|
It achieves the following results on the evaluation set: |
|
- eval_loss: 0.0641 |
|
- eval_mean_iou: 0.9849 |
|
- eval_mean_accuracy: 0.9933 |
|
- eval_overall_accuracy: 0.9933 |
|
- eval_runtime: 94.2835 |
|
- eval_samples_per_second: 10.988 |
|
- eval_steps_per_second: 2.206 |
|
- epoch: 4.18 |
|
- step: 1980 |
|
|
|
## 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: 7e-05 |
|
- train_batch_size: 10 |
|
- eval_batch_size: 5 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 5 |
|
|
|
### Framework versions |
|
|
|
- Transformers 4.36.2 |
|
- Pytorch 2.1.2 |
|
- Datasets 2.16.1 |
|
- Tokenizers 0.15.0 |
