---
license: other
tags:
- generated_from_trainer
model-index:
- name: segformer-b0-finetuned-segments-toolwear
  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-toolwear

This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co./nvidia/mit-b0) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2168
- Mean Iou: 0.3007
- Mean Accuracy: 0.6014
- Overall Accuracy: 0.6014
- Accuracy Unlabeled: nan
- Accuracy Tool: nan
- Accuracy Wear: 0.6014
- Iou Unlabeled: 0.0
- Iou Tool: nan
- Iou Wear: 0.6014

## 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: 25

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Unlabeled | Accuracy Tool | Accuracy Wear | Iou Unlabeled | Iou Tool | Iou Wear |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:-------------:|:-------------:|:-------------:|:--------:|:--------:|
| 0.9147        | 1.82  | 20   | 0.9308          | 0.3010   | 0.9029        | 0.9029           | nan                | nan           | 0.9029        | 0.0           | 0.0      | 0.9029   |
| 0.6788        | 3.64  | 40   | 0.6521          | 0.2589   | 0.7768        | 0.7768           | nan                | nan           | 0.7768        | 0.0           | 0.0      | 0.7768   |
| 0.4559        | 5.45  | 60   | 0.4600          | 0.2663   | 0.7989        | 0.7989           | nan                | nan           | 0.7989        | 0.0           | 0.0      | 0.7989   |
| 0.3799        | 7.27  | 80   | 0.3767          | 0.2061   | 0.6182        | 0.6182           | nan                | nan           | 0.6182        | 0.0           | 0.0      | 0.6182   |
| 0.4438        | 9.09  | 100  | 0.3259          | 0.3479   | 0.6958        | 0.6958           | nan                | nan           | 0.6958        | 0.0           | nan      | 0.6958   |
| 0.3534        | 10.91 | 120  | 0.3008          | 0.3057   | 0.6114        | 0.6114           | nan                | nan           | 0.6114        | 0.0           | nan      | 0.6114   |
| 0.3332        | 12.73 | 140  | 0.2805          | 0.3631   | 0.7261        | 0.7261           | nan                | nan           | 0.7261        | 0.0           | nan      | 0.7261   |
| 0.2543        | 14.55 | 160  | 0.2659          | 0.2927   | 0.5853        | 0.5853           | nan                | nan           | 0.5853        | 0.0           | nan      | 0.5853   |
| 0.2746        | 16.36 | 180  | 0.2324          | 0.2724   | 0.5449        | 0.5449           | nan                | nan           | 0.5449        | 0.0           | nan      | 0.5449   |
| 0.2532        | 18.18 | 200  | 0.2409          | 0.3597   | 0.7194        | 0.7194           | nan                | nan           | 0.7194        | 0.0           | nan      | 0.7194   |
| 0.2353        | 20.0  | 220  | 0.2369          | 0.3070   | 0.6139        | 0.6139           | nan                | nan           | 0.6139        | 0.0           | nan      | 0.6139   |
| 0.2192        | 21.82 | 240  | 0.2210          | 0.3041   | 0.6083        | 0.6083           | nan                | nan           | 0.6083        | 0.0           | nan      | 0.6083   |
| 0.2469        | 23.64 | 260  | 0.2168          | 0.3007   | 0.6014        | 0.6014           | nan                | nan           | 0.6014        | 0.0           | nan      | 0.6014   |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3