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# vit-base-crack-classification-aug-last

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: 0.0124
- F1: 0.9943

## 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: 6
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.4012        | 1.0   | 212  | 0.3809          | 0.8400 |
| 0.1153        | 2.0   | 424  | 0.1429          | 0.9465 |
| 0.0467        | 3.0   | 636  | 0.0742          | 0.9628 |
| 0.0097        | 4.0   | 848  | 0.0194          | 0.9907 |
| 0.0062        | 5.0   | 1060 | 0.0163          | 0.9943 |
| 0.0039        | 6.0   | 1272 | 0.0124          | 0.9943 |


### Framework versions

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

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