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--- |
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license: other |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: segformer-b0-DeepCrack |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# segformer-b0-DeepCrack |
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This model is a fine-tuned version of [nvidia/mit-b4](https://huggingface.co/nvidia/mit-b4) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0145 |
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- Mean Iou: 0.0585 |
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- Mean Accuracy: 0.1170 |
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- Overall Accuracy: 0.1170 |
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- Accuracy Background: nan |
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- Accuracy Cracked: 0.1170 |
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- Iou Background: 0.0 |
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- Iou Cracked: 0.1170 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 6e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Background | Accuracy Cracked | Iou Background | Iou Cracked | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------:|:----------------:|:--------------:|:-----------:| |
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| 0.3566 | 0.13 | 20 | 0.2932 | 0.0200 | 0.0401 | 0.0401 | nan | 0.0401 | 0.0 | 0.0401 | |
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| 0.1639 | 0.27 | 40 | 0.1326 | 0.1353 | 0.2706 | 0.2706 | nan | 0.2706 | 0.0 | 0.2706 | |
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| 0.0562 | 0.4 | 60 | 0.0548 | 0.0681 | 0.1363 | 0.1363 | nan | 0.1363 | 0.0 | 0.1363 | |
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| 0.0283 | 0.53 | 80 | 0.0294 | 0.0815 | 0.1630 | 0.1630 | nan | 0.1630 | 0.0 | 0.1630 | |
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| 0.0187 | 0.67 | 100 | 0.0194 | 0.0720 | 0.1439 | 0.1439 | nan | 0.1439 | 0.0 | 0.1439 | |
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| 0.0144 | 0.8 | 120 | 0.0160 | 0.0656 | 0.1313 | 0.1313 | nan | 0.1313 | 0.0 | 0.1313 | |
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| 0.0152 | 0.93 | 140 | 0.0145 | 0.0585 | 0.1170 | 0.1170 | nan | 0.1170 | 0.0 | 0.1170 | |
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### Framework versions |
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- Transformers 4.30.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
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