


# pipe-failure_classification

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: 0.0255
- Accuracy: 1.0

## Model description

Image classification model using a pretrained Vision Transformer to categorize different types of pipe failures.

## Intended uses & limitations

Diagnostic for Failure on Pipe through image recognition

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 15   | 0.0516          | 0.9867   |
| No log        | 2.0   | 30   | 0.0441          | 0.9867   |
| No log        | 3.0   | 45   | 0.0497          | 0.9733   |
| No log        | 4.0   | 60   | 0.0464          | 0.9867   |
| No log        | 5.0   | 75   | 0.0677          | 0.9867   |
| No log        | 6.0   | 90   | 0.0208          | 1.0      |
| No log        | 7.0   | 105  | 0.0183          | 1.0      |
| No log        | 8.0   | 120  | 0.0943          | 0.9733   |
| No log        | 9.0   | 135  | 0.0216          | 1.0      |
| No log        | 10.0  | 150  | 0.0148          | 1.0      |
| No log        | 11.0  | 165  | 0.0144          | 1.0      |
| No log        | 12.0  | 180  | 0.0188          | 1.0      |
| No log        | 13.0  | 195  | 0.0602          | 0.9867   |
| No log        | 14.0  | 210  | 0.0882          | 0.9733   |
| No log        | 15.0  | 225  | 0.0314          | 0.9867   |
| No log        | 16.0  | 240  | 0.0127          | 1.0      |
| No log        | 17.0  | 255  | 0.0119          | 1.0      |
| No log        | 18.0  | 270  | 0.0117          | 1.0      |
| No log        | 19.0  | 285  | 0.0114          | 1.0      |
| No log        | 20.0  | 300  | 0.0131          | 1.0      |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2

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