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# vit-base-crack-classification-2

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0212
- Accuracy: 0.9917

## 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: 0.0002
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.222         | 1.0   | 203  | 0.2224          | 0.9097   |
| 0.0911        | 2.0   | 406  | 0.0806          | 0.9653   |
| 0.0163        | 3.0   | 609  | 0.0560          | 0.9681   |
| 0.0126        | 4.0   | 812  | 0.0554          | 0.9792   |
| 0.0233        | 5.0   | 1015 | 0.0347          | 0.9806   |
| 0.0096        | 6.0   | 1218 | 0.0949          | 0.9792   |
| 0.0013        | 7.0   | 1421 | 0.0440          | 0.9917   |
| 0.0011        | 8.0   | 1624 | 0.0222          | 0.9917   |
| 0.0009        | 9.0   | 1827 | 0.0213          | 0.9917   |
| 0.0009        | 10.0  | 2030 | 0.0212          | 0.9917   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

crack scratch tire flat dent glass shatter lamp broken