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# swin-tiny-patch4-window7-224-finetuned-teeth_dataset

This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1564
- Accuracy: 0.8391

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.8   | 3    | 4.5796          | 0.0152   |
| No log        | 1.87  | 7    | 4.5200          | 0.0261   |
| 4.5616        | 2.93  | 11   | 4.4705          | 0.0326   |
| 4.5616        | 4.0   | 15   | 4.4127          | 0.0674   |
| 4.5616        | 4.8   | 18   | 4.3493          | 0.0804   |
| 4.44          | 5.87  | 22   | 4.2425          | 0.1130   |
| 4.44          | 6.93  | 26   | 4.1107          | 0.1370   |
| 4.1823        | 8.0   | 30   | 3.9340          | 0.1609   |
| 4.1823        | 8.8   | 33   | 3.7821          | 0.1935   |
| 4.1823        | 9.87  | 37   | 3.5314          | 0.2783   |
| 3.6357        | 10.93 | 41   | 3.2857          | 0.3043   |
| 3.6357        | 12.0  | 45   | 3.1064          | 0.3696   |
| 3.6357        | 12.8  | 48   | 2.9713          | 0.3826   |
| 3.0041        | 13.87 | 52   | 2.7172          | 0.4870   |
| 3.0041        | 14.93 | 56   | 2.5111          | 0.5435   |
| 2.4604        | 16.0  | 60   | 2.3561          | 0.5696   |
| 2.4604        | 16.8  | 63   | 2.2684          | 0.5717   |
| 2.4604        | 17.87 | 67   | 2.0961          | 0.6348   |
| 1.971         | 18.93 | 71   | 1.9555          | 0.6783   |
| 1.971         | 20.0  | 75   | 1.8400          | 0.6891   |
| 1.971         | 20.8  | 78   | 1.7856          | 0.7239   |
| 1.651         | 21.87 | 82   | 1.6797          | 0.7370   |
| 1.651         | 22.93 | 86   | 1.6007          | 0.7717   |
| 1.3665        | 24.0  | 90   | 1.5256          | 0.7739   |
| 1.3665        | 24.8  | 93   | 1.4876          | 0.7652   |
| 1.3665        | 25.87 | 97   | 1.4395          | 0.7783   |
| 1.1954        | 26.93 | 101  | 1.3679          | 0.7870   |
| 1.1954        | 28.0  | 105  | 1.3043          | 0.8022   |
| 1.1954        | 28.8  | 108  | 1.2906          | 0.8022   |
| 0.9886        | 29.87 | 112  | 1.2313          | 0.8109   |
| 0.9886        | 30.93 | 116  | 1.1829          | 0.8348   |
| 0.8803        | 32.0  | 120  | 1.1564          | 0.8391   |
| 0.8803        | 32.8  | 123  | 1.1421          | 0.8304   |
| 0.8803        | 33.87 | 127  | 1.1144          | 0.8326   |
| 0.815         | 34.93 | 131  | 1.1074          | 0.8304   |
| 0.815         | 36.0  | 135  | 1.0919          | 0.8283   |
| 0.815         | 36.8  | 138  | 1.0821          | 0.8326   |
| 0.7619        | 37.87 | 142  | 1.0701          | 0.8348   |
| 0.7619        | 38.93 | 146  | 1.0642          | 0.8348   |
| 0.6991        | 40.0  | 150  | 1.0631          | 0.8391   |


### Framework versions

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

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