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---
license: other
base_model: nvidia/mit-b0
tags:
- vision
- image-segmentation
- generated_from_trainer
model-index:
- name: segformerSAAD
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. -->
# segformerSAAD
This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the saad7489/SixGUN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7611
- Mean Iou: 0.5823
- Mean Accuracy: 0.8994
- Overall Accuracy: 0.9474
- Accuracy Bkg: 0.9505
- Accuracy Knife: 0.8767
- Accuracy Gun: 0.8711
- Iou Bkg: 0.9471
- Iou Knife: 0.4452
- Iou Gun: 0.3544
## 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: 20
- eval_batch_size: 20
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Bkg | Accuracy Knife | Accuracy Gun | Iou Bkg | Iou Knife | Iou Gun |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------:|:--------------:|:------------:|:-------:|:---------:|:-------:|
| 0.9115 | 10.0 | 20 | 1.0252 | 0.5076 | 0.9065 | 0.9181 | 0.9188 | 0.8625 | 0.9382 | 0.9176 | 0.3218 | 0.2833 |
| 0.766 | 20.0 | 40 | 0.8278 | 0.5811 | 0.8914 | 0.9486 | 0.9523 | 0.8691 | 0.8527 | 0.9485 | 0.4288 | 0.3661 |
| 0.7862 | 30.0 | 60 | 0.7611 | 0.5823 | 0.8994 | 0.9474 | 0.9505 | 0.8767 | 0.8711 | 0.9471 | 0.4452 | 0.3544 |
### Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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