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---
license: other
base_model: nvidia/mit-b0
tags:
- vision
- image-segmentation
- generated_from_trainer
model-index:
- name: segformer-b0-finetuned-segments-sidewalk-oct-22
results: []
---
<!-- 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-sidewalk-oct-22
This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the bfwggggg/image-with-puzzle dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2327
- Mean Iou: 0.4736
- Mean Accuracy: 0.9472
- Overall Accuracy: 0.9472
- Accuracy Unlabeled: nan
- Accuracy Missing-puzzle: 0.9472
- Iou Unlabeled: 0.0
- Iou Missing-puzzle: 0.9472
## 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: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Unlabeled | Accuracy Missing-puzzle | Iou Unlabeled | Iou Missing-puzzle |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:-----------------------:|:-------------:|:------------------:|
| 0.5575 | 5.0 | 20 | 0.6601 | 0.4998 | 0.9996 | 0.9996 | nan | 0.9996 | 0.0 | 0.9996 |
| 0.365 | 10.0 | 40 | 0.5628 | 0.4980 | 0.9960 | 0.9960 | nan | 0.9960 | 0.0 | 0.9960 |
| 0.2788 | 15.0 | 60 | 0.3816 | 0.4812 | 0.9624 | 0.9624 | nan | 0.9624 | 0.0 | 0.9624 |
| 0.2527 | 20.0 | 80 | 0.3869 | 0.4806 | 0.9611 | 0.9611 | nan | 0.9611 | 0.0 | 0.9611 |
| 0.2145 | 25.0 | 100 | 0.2733 | 0.4663 | 0.9326 | 0.9326 | nan | 0.9326 | 0.0 | 0.9326 |
| 0.206 | 30.0 | 120 | 0.2672 | 0.4739 | 0.9478 | 0.9478 | nan | 0.9478 | 0.0 | 0.9478 |
| 0.1866 | 35.0 | 140 | 0.2351 | 0.4667 | 0.9334 | 0.9334 | nan | 0.9334 | 0.0 | 0.9334 |
| 0.1696 | 40.0 | 160 | 0.2099 | 0.4749 | 0.9497 | 0.9497 | nan | 0.9497 | 0.0 | 0.9497 |
| 0.1639 | 45.0 | 180 | 0.2058 | 0.4723 | 0.9445 | 0.9445 | nan | 0.9445 | 0.0 | 0.9445 |
| 0.1719 | 50.0 | 200 | 0.2327 | 0.4736 | 0.9472 | 0.9472 | nan | 0.9472 | 0.0 | 0.9472 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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