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---
base_model: nvidia/mit-b0
license: other
tags:
- vision
- image-segmentation
- generated_from_trainer
model-index:
- name: segformer-b0-finetuned-segments-SixrayKnife8-19-2024
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-SixrayKnife8-19-2024
This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the saad7489/SixraygunTest dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6355
- Mean Iou: 0.5008
- Mean Accuracy: 0.7954
- Overall Accuracy: 0.7906
- Accuracy Bkg: nan
- Accuracy Knife: 0.7186
- Accuracy Gun: 0.8722
- Iou Bkg: 0.0
- Iou Knife: 0.6915
- Iou Gun: 0.8110
## 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: 1e-05
- train_batch_size: 5
- eval_batch_size: 5
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------:|:--------------:|:------------:|:-------:|:---------:|:-------:|
| 0.7945 | 1.4286 | 20 | 0.7932 | 0.5023 | 0.8446 | 0.8389 | nan | 0.7531 | 0.9361 | 0.0 | 0.7186 | 0.7883 |
| 0.7385 | 2.8571 | 40 | 0.7324 | 0.5150 | 0.8445 | 0.8404 | nan | 0.7787 | 0.9103 | 0.0 | 0.7375 | 0.8074 |
| 0.7139 | 4.2857 | 60 | 0.7152 | 0.5033 | 0.8256 | 0.8200 | nan | 0.7358 | 0.9155 | 0.0 | 0.7072 | 0.8027 |
| 0.7405 | 5.7143 | 80 | 0.6747 | 0.4953 | 0.7972 | 0.7917 | nan | 0.7078 | 0.8866 | 0.0 | 0.6785 | 0.8075 |
| 0.6666 | 7.1429 | 100 | 0.6442 | 0.4937 | 0.7919 | 0.7860 | nan | 0.6964 | 0.8874 | 0.0 | 0.6723 | 0.8089 |
| 0.6357 | 8.5714 | 120 | 0.6210 | 0.4957 | 0.7874 | 0.7823 | nan | 0.7059 | 0.8688 | 0.0 | 0.6794 | 0.8076 |
| 0.6548 | 10.0 | 140 | 0.6355 | 0.5008 | 0.7954 | 0.7906 | nan | 0.7186 | 0.8722 | 0.0 | 0.6915 | 0.8110 |
### Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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