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# image_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: 1.9492
- Accuracy: 0.5312

## 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: 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: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 40   | 1.3627          | 0.4313   |
| No log        | 2.0   | 80   | 1.3275          | 0.4875   |
| No log        | 3.0   | 120  | 1.2246          | 0.5188   |
| No log        | 4.0   | 160  | 1.3181          | 0.5437   |
| No log        | 5.0   | 200  | 1.2843          | 0.55     |
| No log        | 6.0   | 240  | 1.3726          | 0.4938   |
| No log        | 7.0   | 280  | 1.4959          | 0.475    |
| No log        | 8.0   | 320  | 1.4542          | 0.4875   |
| No log        | 9.0   | 360  | 1.7002          | 0.4625   |
| No log        | 10.0  | 400  | 1.5043          | 0.5      |
| No log        | 11.0  | 440  | 1.5684          | 0.5062   |
| No log        | 12.0  | 480  | 1.6611          | 0.5      |
| 0.5862        | 13.0  | 520  | 1.7354          | 0.4688   |
| 0.5862        | 14.0  | 560  | 1.7357          | 0.4813   |
| 0.5862        | 15.0  | 600  | 1.7006          | 0.4875   |
| 0.5862        | 16.0  | 640  | 1.8564          | 0.4938   |
| 0.5862        | 17.0  | 680  | 1.8633          | 0.475    |
| 0.5862        | 18.0  | 720  | 1.7142          | 0.5062   |
| 0.5862        | 19.0  | 760  | 1.9792          | 0.4562   |
| 0.5862        | 20.0  | 800  | 1.8761          | 0.5      |
| 0.5862        | 21.0  | 840  | 2.0587          | 0.45     |
| 0.5862        | 22.0  | 880  | 2.0288          | 0.4813   |
| 0.5862        | 23.0  | 920  | 1.6472          | 0.5563   |
| 0.5862        | 24.0  | 960  | 2.0372          | 0.5      |
| 0.1675        | 25.0  | 1000 | 1.8781          | 0.5312   |
| 0.1675        | 26.0  | 1040 | 2.0097          | 0.5062   |
| 0.1675        | 27.0  | 1080 | 1.8897          | 0.5188   |
| 0.1675        | 28.0  | 1120 | 1.8845          | 0.5188   |
| 0.1675        | 29.0  | 1160 | 1.9099          | 0.5312   |
| 0.1675        | 30.0  | 1200 | 1.9492          | 0.5312   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1

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