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# fisura-hormigon

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 imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0123
- Accuracy: 0.9978

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.0989        | 0.17  | 500   | 0.0477          | 0.9871   |
| 0.0531        | 0.33  | 1000  | 0.0493          | 0.9865   |
| 0.046         | 0.5   | 1500  | 0.0381          | 0.9894   |
| 0.0392        | 0.67  | 2000  | 0.1129          | 0.9734   |
| 0.0459        | 0.83  | 2500  | 0.0364          | 0.9904   |
| 0.0255        | 1.0   | 3000  | 0.0305          | 0.9934   |
| 0.0188        | 1.17  | 3500  | 0.0247          | 0.9949   |
| 0.0222        | 1.33  | 4000  | 0.0206          | 0.9921   |
| 0.02          | 1.5   | 4500  | 0.0154          | 0.9952   |
| 0.0191        | 1.67  | 5000  | 0.0132          | 0.9952   |
| 0.0141        | 1.83  | 5500  | 0.0294          | 0.9905   |
| 0.0201        | 2.0   | 6000  | 0.0155          | 0.9968   |
| 0.0114        | 2.17  | 6500  | 0.0161          | 0.9965   |
| 0.0071        | 2.33  | 7000  | 0.0124          | 0.9975   |
| 0.0083        | 2.5   | 7500  | 0.0141          | 0.9969   |
| 0.0143        | 2.67  | 8000  | 0.0242          | 0.9932   |
| 0.0088        | 2.83  | 8500  | 0.0123          | 0.9972   |
| 0.0034        | 3.0   | 9000  | 0.0120          | 0.9972   |
| 0.0064        | 3.17  | 9500  | 0.0100          | 0.9978   |
| 0.0012        | 3.33  | 10000 | 0.0166          | 0.996    |
| 0.006         | 3.5   | 10500 | 0.0110          | 0.998    |
| 0.0007        | 3.67  | 11000 | 0.0126          | 0.9972   |
| 0.0034        | 3.83  | 11500 | 0.0122          | 0.9979   |
| 0.0057        | 4.0   | 12000 | 0.0123          | 0.9978   |


### Framework versions

- Transformers 4.29.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3

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