---
license: other
base_model: nvidia/mit-b0
tags:
- vision
- image-segmentation
- generated_from_trainer
model-index:
- name: Segformer_finetune
  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_finetune

This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the saad7489/SixKnifesorted dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8216
- Mean Iou: 0.4681
- Mean Accuracy: 0.8710
- Overall Accuracy: 0.9550
- Accuracy Bkg: 0.9636
- Accuracy Knife: 0.7783
- Accuracy Gun: nan
- Iou Bkg: 0.9533
- Iou Knife: 0.4511
- Iou Gun: 0.0

## 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: 5e-05
- train_batch_size: 30
- eval_batch_size: 30
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------:|:--------------:|:------------:|:-------:|:---------:|:-------:|
| 0.759         | 6.6667 | 20   | 0.8216          | 0.4681   | 0.8710        | 0.9550           | 0.9636       | 0.7783         | nan          | 0.9533  | 0.4511    | 0.0     |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1