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---
license: other
tags:
- vision
- image-segmentation
- generated_from_trainer
model-index:
- name: safety-utcustom-train-SF30-RGB-b0
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. -->
# safety-utcustom-train-SF30-RGB-b0
This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the sam1120/safety-utcustom-TRAIN-30 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7492
- Mean Iou: 0.3878
- Mean Accuracy: 0.8431
- Overall Accuracy: 0.9233
- Accuracy Unlabeled: nan
- Accuracy Safe: 0.7575
- Accuracy Unsafe: 0.9287
- Iou Unlabeled: 0.0
- Iou Safe: 0.2418
- Iou Unsafe: 0.9214
## 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: 9e-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 120
### Training results
| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Unlabeled | Accuracy Safe | Accuracy Unsafe | Iou Unlabeled | Iou Safe | Iou Unsafe |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:-------------:|:---------------:|:-------------:|:--------:|:----------:|
| 1.1527 | 5.0 | 10 | 1.1085 | 0.0590 | 0.4585 | 0.1664 | nan | 0.7704 | 0.1465 | 0.0 | 0.0307 | 0.1464 |
| 1.1326 | 10.0 | 20 | 1.1091 | 0.0963 | 0.6082 | 0.2699 | nan | 0.9695 | 0.2470 | 0.0 | 0.0419 | 0.2470 |
| 1.0981 | 15.0 | 30 | 1.0980 | 0.1530 | 0.6989 | 0.4242 | nan | 0.9922 | 0.4055 | 0.0 | 0.0535 | 0.4055 |
| 1.086 | 20.0 | 40 | 1.0822 | 0.1916 | 0.7515 | 0.5256 | nan | 0.9927 | 0.5103 | 0.0 | 0.0644 | 0.5103 |
| 1.0466 | 25.0 | 50 | 1.0541 | 0.2226 | 0.7909 | 0.6043 | nan | 0.9902 | 0.5917 | 0.0 | 0.0761 | 0.5917 |
| 1.0533 | 30.0 | 60 | 1.0249 | 0.2444 | 0.8167 | 0.6580 | nan | 0.9863 | 0.6472 | 0.0 | 0.0861 | 0.6471 |
| 0.9779 | 35.0 | 70 | 1.0010 | 0.2607 | 0.8322 | 0.6966 | nan | 0.9771 | 0.6874 | 0.0 | 0.0951 | 0.6871 |
| 0.9161 | 40.0 | 80 | 0.9695 | 0.2808 | 0.8487 | 0.7412 | nan | 0.9635 | 0.7339 | 0.0 | 0.1091 | 0.7334 |
| 0.9843 | 45.0 | 90 | 0.9403 | 0.3004 | 0.8631 | 0.7823 | nan | 0.9494 | 0.7768 | 0.0 | 0.1254 | 0.7759 |
| 0.9568 | 50.0 | 100 | 0.9071 | 0.3176 | 0.8663 | 0.8169 | nan | 0.9191 | 0.8135 | 0.0 | 0.1412 | 0.8117 |
| 0.8443 | 55.0 | 110 | 0.8627 | 0.3403 | 0.8656 | 0.8576 | nan | 0.8742 | 0.8570 | 0.0 | 0.1672 | 0.8537 |
| 0.8765 | 60.0 | 120 | 0.8488 | 0.3450 | 0.8625 | 0.8657 | nan | 0.8591 | 0.8659 | 0.0 | 0.1729 | 0.8620 |
| 0.899 | 65.0 | 130 | 0.8429 | 0.3481 | 0.8629 | 0.8705 | nan | 0.8548 | 0.8710 | 0.0 | 0.1772 | 0.8669 |
| 0.7713 | 70.0 | 140 | 0.8085 | 0.3632 | 0.8497 | 0.8939 | nan | 0.8026 | 0.8969 | 0.0 | 0.1983 | 0.8912 |
| 0.8505 | 75.0 | 150 | 0.7821 | 0.3762 | 0.8465 | 0.9102 | nan | 0.7786 | 0.9145 | 0.0 | 0.2208 | 0.9079 |
| 0.7352 | 80.0 | 160 | 0.7841 | 0.3819 | 0.8392 | 0.9173 | nan | 0.7557 | 0.9226 | 0.0 | 0.2304 | 0.9153 |
| 0.7205 | 85.0 | 170 | 0.7502 | 0.3974 | 0.8400 | 0.9325 | nan | 0.7413 | 0.9388 | 0.0 | 0.2613 | 0.9309 |
| 0.711 | 90.0 | 180 | 0.7417 | 0.3962 | 0.8428 | 0.9313 | nan | 0.7484 | 0.9373 | 0.0 | 0.2591 | 0.9296 |
| 0.7855 | 95.0 | 190 | 0.7281 | 0.4003 | 0.8439 | 0.9343 | nan | 0.7473 | 0.9404 | 0.0 | 0.2683 | 0.9327 |
| 0.7632 | 100.0 | 200 | 0.7494 | 0.3883 | 0.8419 | 0.9237 | nan | 0.7545 | 0.9293 | 0.0 | 0.2430 | 0.9219 |
| 0.8145 | 105.0 | 210 | 0.7495 | 0.3862 | 0.8412 | 0.9219 | nan | 0.7551 | 0.9274 | 0.0 | 0.2387 | 0.9201 |
| 0.8217 | 110.0 | 220 | 0.7355 | 0.3933 | 0.8422 | 0.9282 | nan | 0.7502 | 0.9341 | 0.0 | 0.2533 | 0.9265 |
| 0.7784 | 115.0 | 230 | 0.7258 | 0.4088 | 0.8411 | 0.9413 | nan | 0.7340 | 0.9481 | 0.0 | 0.2864 | 0.9400 |
| 0.8349 | 120.0 | 240 | 0.7492 | 0.3878 | 0.8431 | 0.9233 | nan | 0.7575 | 0.9287 | 0.0 | 0.2418 | 0.9214 |
### Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3
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