---
license: other
base_model: nvidia/mit-b0
tags:
- vision
- image-segmentation
- generated_from_trainer
model-index:
- name: segformer-b0-finetuned-segments-SixrayKnife8-21-2024_saad5
  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-SixrayKnife8-21-2024_saad5

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: 0.2720
- Mean Iou: 0.8171
- Mean Accuracy: 0.9114
- Overall Accuracy: 0.9868
- Accuracy Bkg: 0.9925
- Accuracy Knife: 0.8345
- Accuracy Gun: 0.9072
- Iou Bkg: 0.9878
- Iou Knife: 0.7337
- Iou Gun: 0.7298

## 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: 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: 20

### 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------:|:--------------:|:------------:|:-------:|:---------:|:-------:|
| 0.2986        | 5.0   | 20   | 0.2833          | 0.8180   | 0.9092        | 0.9869           | 0.9928       | 0.8290         | 0.9057       | 0.9879  | 0.7362    | 0.7299  |
| 0.2801        | 10.0  | 40   | 0.2780          | 0.8141   | 0.9117        | 0.9864           | 0.9921       | 0.8366         | 0.9063       | 0.9875  | 0.7281    | 0.7268  |
| 0.2908        | 15.0  | 60   | 0.2739          | 0.8178   | 0.9075        | 0.9869           | 0.9930       | 0.8289         | 0.9005       | 0.9880  | 0.7332    | 0.7321  |
| 0.2928        | 20.0  | 80   | 0.2720          | 0.8171   | 0.9114        | 0.9868           | 0.9925       | 0.8345         | 0.9072       | 0.9878  | 0.7337    | 0.7298  |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1