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---
license: other
tags:
- generated_from_trainer
model-index:
- name: segformer-b0-DeepCrack
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-DeepCrack
This model is a fine-tuned version of [nvidia/mit-b4](https://huggingface.co/nvidia/mit-b4) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4264
- Mean Iou: 0.1964
- Mean Accuracy: 0.3929
- Overall Accuracy: 0.3929
- Accuracy Background: nan
- Accuracy Cracked: 0.3929
- Iou Background: 0.0
- Iou Cracked: 0.3929
## 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: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Background | Accuracy Cracked | Iou Background | Iou Cracked |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------:|:----------------:|:--------------:|:-----------:|
| 0.5096 | 1.0 | 20 | 0.4264 | 0.1964 | 0.3929 | 0.3929 | nan | 0.3929 | 0.0 | 0.3929 |
### Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
|