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---
license: other
base_model: nvidia/mit-b3
tags:
- generated_from_trainer
model-index:
- name: segformer_cracks
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_cracks
This model is a fine-tuned version of [nvidia/mit-b3](https://huggingface.co/nvidia/mit-b3) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0499
- Mean Iou: 0.7718
- Mean Accuracy: 0.8317
- Overall Accuracy: 0.9798
- Per Category Iou: [0.9792869895386617, 0.564265846038068]
- Per Category Accuracy: [0.9923313345080351, 0.671108360646227]
## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7
### Training results
| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Per Category Iou | Per Category Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:-------------:|:----------------:|:----------------------------------------:|:----------------------------------------:|
| 0.0686 | 1.0 | 1541 | 0.0557 | 0.7541 | 0.8082 | 0.9785 | [0.9779708221514636, 0.5303006858963294] | [0.9928845967047768, 0.6234677160845897] |
| 0.049 | 2.0 | 3082 | 0.0527 | 0.7633 | 0.8239 | 0.9790 | [0.9784073819168878, 0.5481400031368636] | [0.9920481107810992, 0.6557623260692017] |
| 0.0468 | 3.0 | 4623 | 0.0547 | 0.7526 | 0.7996 | 0.9788 | [0.9783360187606548, 0.5269084757862701] | [0.993975994702418, 0.6052805015161615] |
| 0.0456 | 4.0 | 6164 | 0.0509 | 0.7677 | 0.8276 | 0.9794 | [0.9788937969015667, 0.556522438909845] | [0.9922581622702671, 0.6629042271896711] |
| 0.044 | 5.0 | 7705 | 0.0505 | 0.7678 | 0.8265 | 0.9795 | [0.9789809420595871, 0.5566804258721124] | [0.9924358981457169, 0.6606494246283242] |
| 0.0436 | 6.0 | 9246 | 0.0502 | 0.7696 | 0.8265 | 0.9798 | [0.9792607857315766, 0.5598563478221208] | [0.9927329763880554, 0.6603118480646505] |
| 0.0431 | 7.0 | 10787 | 0.0499 | 0.7718 | 0.8317 | 0.9798 | [0.9792869895386617, 0.564265846038068] | [0.9923313345080351, 0.671108360646227] |
### Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1
- Datasets 2.14.5
- Tokenizers 0.13.3
|