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