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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-dots
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-dots
This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the rohan8020/test dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1328
- Mean Iou: 0.3201
- Mean Accuracy: 0.6402
- Overall Accuracy: 0.6402
- Accuracy Unlabeled: nan
- Accuracy Dots: 0.6402
- Iou Unlabeled: 0.0
- Iou Dots: 0.6402
## 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 Dots | Iou Unlabeled | Iou Dots |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:-------------:|:-------------:|:--------:|
| 0.5642 | 4.0 | 20 | 0.6209 | 0.4838 | 0.9677 | 0.9677 | nan | 0.9677 | 0.0 | 0.9677 |
| 0.4154 | 8.0 | 40 | 0.4119 | 0.2969 | 0.5939 | 0.5939 | nan | 0.5939 | 0.0 | 0.5939 |
| 0.3246 | 12.0 | 60 | 0.2900 | 0.3123 | 0.6246 | 0.6246 | nan | 0.6246 | 0.0 | 0.6246 |
| 0.2898 | 16.0 | 80 | 0.3168 | 0.4260 | 0.8520 | 0.8520 | nan | 0.8520 | 0.0 | 0.8520 |
| 0.2419 | 20.0 | 100 | 0.2201 | 0.3446 | 0.6892 | 0.6892 | nan | 0.6892 | 0.0 | 0.6892 |
| 0.2042 | 24.0 | 120 | 0.2199 | 0.3213 | 0.6426 | 0.6426 | nan | 0.6426 | 0.0 | 0.6426 |
| 0.1662 | 28.0 | 140 | 0.1797 | 0.3002 | 0.6005 | 0.6005 | nan | 0.6005 | 0.0 | 0.6005 |
| 0.1757 | 32.0 | 160 | 0.1611 | 0.2919 | 0.5839 | 0.5839 | nan | 0.5839 | 0.0 | 0.5839 |
| 0.1473 | 36.0 | 180 | 0.1477 | 0.3219 | 0.6439 | 0.6439 | nan | 0.6439 | 0.0 | 0.6439 |
| 0.1645 | 40.0 | 200 | 0.1448 | 0.3267 | 0.6534 | 0.6534 | nan | 0.6534 | 0.0 | 0.6534 |
| 0.1576 | 44.0 | 220 | 0.1389 | 0.3377 | 0.6754 | 0.6754 | nan | 0.6754 | 0.0 | 0.6754 |
| 0.1381 | 48.0 | 240 | 0.1328 | 0.3201 | 0.6402 | 0.6402 | nan | 0.6402 | 0.0 | 0.6402 |
### Framework versions
- Transformers 4.37.0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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