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# surface_grade-swin-tiny-patch4-window7-224-finetuned-v1

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: 1.4768
- Accuracy: 0.4094

## 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: 30

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.6612        | 1.0   | 734   | 1.6258          | 0.2908   |
| 1.6119        | 2.0   | 1468  | 1.5665          | 0.3149   |
| 1.5692        | 3.0   | 2202  | 1.5426          | 0.3301   |
| 1.5691        | 4.0   | 2936  | 1.4929          | 0.3599   |
| 1.5401        | 5.0   | 3670  | 1.4630          | 0.3702   |
| 1.5245        | 6.0   | 4404  | 1.4586          | 0.3728   |
| 1.5342        | 7.0   | 5138  | 1.4018          | 0.4008   |
| 1.5268        | 8.0   | 5872  | 1.3966          | 0.4040   |
| 1.4918        | 9.0   | 6606  | 1.4097          | 0.3960   |
| 1.4447        | 10.0  | 7340  | 1.3942          | 0.3997   |
| 1.468         | 11.0  | 8074  | 1.3802          | 0.4164   |
| 1.4379        | 12.0  | 8808  | 1.3927          | 0.4091   |
| 1.4152        | 13.0  | 9542  | 1.3916          | 0.4091   |
| 1.3845        | 14.0  | 10276 | 1.3901          | 0.4063   |
| 1.3659        | 15.0  | 11010 | 1.3846          | 0.4121   |
| 1.3429        | 16.0  | 11744 | 1.4010          | 0.4099   |
| 1.3534        | 17.0  | 12478 | 1.3968          | 0.4115   |
| 1.3026        | 18.0  | 13212 | 1.4060          | 0.4106   |
| 1.2955        | 19.0  | 13946 | 1.4469          | 0.4008   |
| 1.2849        | 20.0  | 14680 | 1.4081          | 0.4136   |
| 1.2331        | 21.0  | 15414 | 1.4188          | 0.4089   |
| 1.2313        | 22.0  | 16148 | 1.4256          | 0.4101   |
| 1.2           | 23.0  | 16882 | 1.4414          | 0.4100   |
| 1.2271        | 24.0  | 17616 | 1.4540          | 0.4088   |
| 1.2142        | 25.0  | 18350 | 1.4528          | 0.4064   |
| 1.1986        | 26.0  | 19084 | 1.4566          | 0.4090   |
| 1.134         | 27.0  | 19818 | 1.4648          | 0.4104   |
| 1.1756        | 28.0  | 20552 | 1.4700          | 0.4089   |
| 1.1415        | 29.0  | 21286 | 1.4791          | 0.4082   |
| 1.1411        | 30.0  | 22020 | 1.4768          | 0.4094   |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.0.1+cu117
- Datasets 2.17.0
- Tokenizers 0.15.2

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