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--- |
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license: other |
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base_model: nvidia/mit-b5 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: Augmented-MIT-b5 |
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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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# Augmented-MIT-b5 |
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This model is a fine-tuned version of [nvidia/mit-b5](https://huggingface.co/nvidia/mit-b5) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0371 |
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- Mean Iou: 0.3355 |
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- Mean Accuracy: 0.6711 |
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- Overall Accuracy: 0.6711 |
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- Accuracy Background: nan |
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- Accuracy Crack: 0.6711 |
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- Iou Background: 0.0 |
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- Iou Crack: 0.6711 |
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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 Crack | Iou Background | Iou Crack | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------:|:--------------:|:--------------:|:---------:| |
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| 0.0365 | 0.14 | 1000 | 0.0446 | 0.3813 | 0.7627 | 0.7627 | nan | 0.7627 | 0.0 | 0.7627 | |
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| 0.0114 | 0.27 | 2000 | 0.0411 | 0.3691 | 0.7381 | 0.7381 | nan | 0.7381 | 0.0 | 0.7381 | |
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| 0.0148 | 0.41 | 3000 | 0.0400 | 0.3224 | 0.6448 | 0.6448 | nan | 0.6448 | 0.0 | 0.6448 | |
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| 0.0134 | 0.54 | 4000 | 0.0413 | 0.2819 | 0.5638 | 0.5638 | nan | 0.5638 | 0.0 | 0.5638 | |
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| 0.013 | 0.68 | 5000 | 0.0392 | 0.3618 | 0.7235 | 0.7235 | nan | 0.7235 | 0.0 | 0.7235 | |
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| 0.0532 | 0.81 | 6000 | 0.0373 | 0.3355 | 0.6710 | 0.6710 | nan | 0.6710 | 0.0 | 0.6710 | |
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| 0.0508 | 0.95 | 7000 | 0.0371 | 0.3355 | 0.6711 | 0.6711 | nan | 0.6711 | 0.0 | 0.6711 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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