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# camera-type

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0235
- Accuracy: 0.9916

## 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: 0.0001
- train_batch_size: 10
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0064        | 0.4   | 200  | 0.0235          | 0.9916   |
| 0.0034        | 0.79  | 400  | 0.0392          | 0.9941   |
| 0.0066        | 1.19  | 600  | 0.1011          | 0.9840   |
| 0.0           | 1.58  | 800  | 0.1227          | 0.9840   |
| 0.0           | 1.98  | 1000 | 0.1232          | 0.9840   |
| 0.0           | 2.37  | 1200 | 0.1433          | 0.9840   |
| 0.0           | 2.77  | 1400 | 0.1416          | 0.9840   |
| 0.0           | 3.16  | 1600 | 0.1408          | 0.9840   |
| 0.0           | 3.56  | 1800 | 0.1401          | 0.9840   |
| 0.0           | 3.95  | 2000 | 0.1394          | 0.9840   |
| 0.0           | 4.35  | 2200 | 0.1390          | 0.9840   |
| 0.0           | 4.74  | 2400 | 0.1389          | 0.9840   |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3

cctv phone topdown