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---
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: 0.0517
- Mean Iou: 0.3741
- Mean Accuracy: 0.7482
- Overall Accuracy: 0.7482
- Accuracy Unlabeled: nan
- Accuracy Tool: nan
- Accuracy Wear: 0.7482
- Iou Unlabeled: 0.0
- Iou Tool: nan
- Iou Wear: 0.7482
## 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: 50
### 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:-------------:|:-------------:|:-------------:|:--------:|:--------:|
| 0.8497 | 1.82 | 20 | 0.8647 | 0.4917 | 0.9834 | 0.9834 | nan | nan | 0.9834 | 0.0 | nan | 0.9834 |
| 0.6095 | 3.64 | 40 | 0.5158 | 0.4642 | 0.9283 | 0.9283 | nan | nan | 0.9283 | 0.0 | nan | 0.9283 |
| 0.4377 | 5.45 | 60 | 0.4200 | 0.4646 | 0.9291 | 0.9291 | nan | nan | 0.9291 | 0.0 | nan | 0.9291 |
| 0.3756 | 7.27 | 80 | 0.3535 | 0.4780 | 0.9560 | 0.9560 | nan | nan | 0.9560 | 0.0 | nan | 0.9560 |
| 0.4256 | 9.09 | 100 | 0.2951 | 0.4873 | 0.9746 | 0.9746 | nan | nan | 0.9746 | 0.0 | nan | 0.9746 |
| 0.2748 | 10.91 | 120 | 0.2500 | 0.4817 | 0.9634 | 0.9634 | nan | nan | 0.9634 | 0.0 | nan | 0.9634 |
| 0.2347 | 12.73 | 140 | 0.2000 | 0.4065 | 0.8129 | 0.8129 | nan | nan | 0.8129 | 0.0 | nan | 0.8129 |
| 0.1777 | 14.55 | 160 | 0.1651 | 0.4340 | 0.8680 | 0.8680 | nan | nan | 0.8680 | 0.0 | nan | 0.8680 |
| 0.186 | 16.36 | 180 | 0.1530 | 0.4211 | 0.8422 | 0.8422 | nan | nan | 0.8422 | 0.0 | nan | 0.8422 |
| 0.1652 | 18.18 | 200 | 0.1143 | 0.4304 | 0.8608 | 0.8608 | nan | nan | 0.8608 | 0.0 | nan | 0.8608 |
| 0.1227 | 20.0 | 220 | 0.1436 | 0.4838 | 0.9676 | 0.9676 | nan | nan | 0.9676 | 0.0 | nan | 0.9676 |
| 0.1111 | 21.82 | 240 | 0.1014 | 0.3994 | 0.7988 | 0.7988 | nan | nan | 0.7988 | 0.0 | nan | 0.7988 |
| 0.0989 | 23.64 | 260 | 0.0914 | 0.3574 | 0.7147 | 0.7147 | nan | nan | 0.7147 | 0.0 | nan | 0.7147 |
| 0.1051 | 25.45 | 280 | 0.0871 | 0.2844 | 0.5689 | 0.5689 | nan | nan | 0.5689 | 0.0 | nan | 0.5689 |
| 0.0975 | 27.27 | 300 | 0.0679 | 0.3893 | 0.7786 | 0.7786 | nan | nan | 0.7786 | 0.0 | nan | 0.7786 |
| 0.0928 | 29.09 | 320 | 0.0723 | 0.4241 | 0.8483 | 0.8483 | nan | nan | 0.8483 | 0.0 | nan | 0.8483 |
| 0.0673 | 30.91 | 340 | 0.0653 | 0.3628 | 0.7255 | 0.7255 | nan | nan | 0.7255 | 0.0 | nan | 0.7255 |
| 0.0652 | 32.73 | 360 | 0.0641 | 0.4023 | 0.8047 | 0.8047 | nan | nan | 0.8047 | 0.0 | nan | 0.8047 |
| 0.0912 | 34.55 | 380 | 0.0734 | 0.4453 | 0.8906 | 0.8906 | nan | nan | 0.8906 | 0.0 | nan | 0.8906 |
| 0.0682 | 36.36 | 400 | 0.0609 | 0.3322 | 0.6644 | 0.6644 | nan | nan | 0.6644 | 0.0 | nan | 0.6644 |
| 0.0737 | 38.18 | 420 | 0.0619 | 0.4053 | 0.8107 | 0.8107 | nan | nan | 0.8107 | 0.0 | nan | 0.8107 |
| 0.06 | 40.0 | 440 | 0.0564 | 0.3593 | 0.7186 | 0.7186 | nan | nan | 0.7186 | 0.0 | nan | 0.7186 |
| 0.0555 | 41.82 | 460 | 0.0562 | 0.4025 | 0.8050 | 0.8050 | nan | nan | 0.8050 | 0.0 | nan | 0.8050 |
| 0.063 | 43.64 | 480 | 0.0550 | 0.3945 | 0.7891 | 0.7891 | nan | nan | 0.7891 | 0.0 | nan | 0.7891 |
| 0.0641 | 45.45 | 500 | 0.0554 | 0.4032 | 0.8065 | 0.8065 | nan | nan | 0.8065 | 0.0 | nan | 0.8065 |
| 0.0739 | 47.27 | 520 | 0.0549 | 0.3880 | 0.7760 | 0.7760 | nan | nan | 0.7760 | 0.0 | nan | 0.7760 |
| 0.0684 | 49.09 | 540 | 0.0517 | 0.3741 | 0.7482 | 0.7482 | nan | nan | 0.7482 | 0.0 | nan | 0.7482 |
### Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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