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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: 0.1291
- Mean Iou: 0.4322
- Mean Accuracy: 0.8644
- Overall Accuracy: 0.8644
- Accuracy Unlabeled: nan
- Accuracy Tool: nan
- Accuracy Wear: 0.8644
- Iou Unlabeled: 0.0
- Iou Tool: nan
- Iou Wear: 0.8644
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:-------------:|:-------------:|:-------------:|:--------:|:--------:|
| 0.8371 | 1.82 | 20 | 0.9482 | 0.3285 | 0.9854 | 0.9854 | nan | nan | 0.9854 | 0.0 | 0.0 | 0.9854 |
| 0.6335 | 3.64 | 40 | 0.7489 | 0.4996 | 0.9992 | 0.9992 | nan | nan | 0.9992 | 0.0 | nan | 0.9992 |
| 0.5053 | 5.45 | 60 | 0.5400 | 0.4975 | 0.9949 | 0.9949 | nan | nan | 0.9949 | 0.0 | nan | 0.9949 |
| 0.3924 | 7.27 | 80 | 0.4544 | 0.4905 | 0.9810 | 0.9810 | nan | nan | 0.9810 | 0.0 | nan | 0.9810 |
| 0.3419 | 9.09 | 100 | 0.3840 | 0.4727 | 0.9455 | 0.9455 | nan | nan | 0.9455 | 0.0 | nan | 0.9455 |
| 0.3379 | 10.91 | 120 | 0.3407 | 0.4648 | 0.9296 | 0.9296 | nan | nan | 0.9296 | 0.0 | nan | 0.9296 |
| 0.2639 | 12.73 | 140 | 0.3495 | 0.4780 | 0.9559 | 0.9559 | nan | nan | 0.9559 | 0.0 | nan | 0.9559 |
| 0.224 | 14.55 | 160 | 0.2815 | 0.4541 | 0.9081 | 0.9081 | nan | nan | 0.9081 | 0.0 | nan | 0.9081 |
| 0.1725 | 16.36 | 180 | 0.2896 | 0.4599 | 0.9199 | 0.9199 | nan | nan | 0.9199 | 0.0 | nan | 0.9199 |
| 0.1623 | 18.18 | 200 | 0.2540 | 0.4679 | 0.9359 | 0.9359 | nan | nan | 0.9359 | 0.0 | nan | 0.9359 |
| 0.1724 | 20.0 | 220 | 0.2567 | 0.4702 | 0.9404 | 0.9404 | nan | nan | 0.9404 | 0.0 | nan | 0.9404 |
| 0.1503 | 21.82 | 240 | 0.1967 | 0.4459 | 0.8919 | 0.8919 | nan | nan | 0.8919 | 0.0 | nan | 0.8919 |
| 0.1189 | 23.64 | 260 | 0.2153 | 0.4617 | 0.9234 | 0.9234 | nan | nan | 0.9234 | 0.0 | nan | 0.9234 |
| 0.1007 | 25.45 | 280 | 0.1695 | 0.4324 | 0.8648 | 0.8648 | nan | nan | 0.8648 | 0.0 | nan | 0.8648 |
| 0.0921 | 27.27 | 300 | 0.1540 | 0.4346 | 0.8691 | 0.8691 | nan | nan | 0.8691 | 0.0 | nan | 0.8691 |
| 0.0897 | 29.09 | 320 | 0.1657 | 0.4538 | 0.9077 | 0.9077 | nan | nan | 0.9077 | 0.0 | nan | 0.9077 |
| 0.0814 | 30.91 | 340 | 0.1519 | 0.4374 | 0.8749 | 0.8749 | nan | nan | 0.8749 | 0.0 | nan | 0.8749 |
| 0.0729 | 32.73 | 360 | 0.1444 | 0.4430 | 0.8861 | 0.8861 | nan | nan | 0.8861 | 0.0 | nan | 0.8861 |
| 0.0892 | 34.55 | 380 | 0.1283 | 0.4106 | 0.8213 | 0.8213 | nan | nan | 0.8213 | 0.0 | nan | 0.8213 |
| 0.07 | 36.36 | 400 | 0.1442 | 0.4374 | 0.8748 | 0.8748 | nan | nan | 0.8748 | 0.0 | nan | 0.8748 |
| 0.0619 | 38.18 | 420 | 0.1391 | 0.4296 | 0.8592 | 0.8592 | nan | nan | 0.8592 | 0.0 | nan | 0.8592 |
| 0.0563 | 40.0 | 440 | 0.1283 | 0.4402 | 0.8804 | 0.8804 | nan | nan | 0.8804 | 0.0 | nan | 0.8804 |
| 0.0582 | 41.82 | 460 | 0.1275 | 0.4297 | 0.8595 | 0.8595 | nan | nan | 0.8595 | 0.0 | nan | 0.8595 |
| 0.0575 | 43.64 | 480 | 0.1341 | 0.4362 | 0.8724 | 0.8724 | nan | nan | 0.8724 | 0.0 | nan | 0.8724 |
| 0.068 | 45.45 | 500 | 0.1132 | 0.4181 | 0.8362 | 0.8362 | nan | nan | 0.8362 | 0.0 | nan | 0.8362 |
| 0.0595 | 47.27 | 520 | 0.1285 | 0.4316 | 0.8632 | 0.8632 | nan | nan | 0.8632 | 0.0 | nan | 0.8632 |
| 0.0558 | 49.09 | 540 | 0.1291 | 0.4322 | 0.8644 | 0.8644 | nan | nan | 0.8644 | 0.0 | nan | 0.8644 |
### Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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