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# cards-top_left_swin-tiny-patch4-window7-224-finetuned-v3_more_data

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: 0.9722
- Accuracy: 0.5941

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.5501        | 1.0   | 1346  | 1.2633          | 0.4645   |
| 1.4882        | 2.0   | 2692  | 1.1866          | 0.4951   |
| 1.5148        | 3.0   | 4038  | 1.1644          | 0.5066   |
| 1.4605        | 4.0   | 5384  | 1.1546          | 0.5105   |
| 1.425         | 5.0   | 6730  | 1.0940          | 0.5361   |
| 1.4452        | 6.0   | 8076  | 1.0750          | 0.5530   |
| 1.4507        | 7.0   | 9422  | 1.0997          | 0.5301   |
| 1.4435        | 8.0   | 10768 | 1.0835          | 0.5445   |
| 1.3904        | 9.0   | 12114 | 1.0587          | 0.5493   |
| 1.3826        | 10.0  | 13460 | 1.0434          | 0.5581   |
| 1.4186        | 11.0  | 14806 | 1.0515          | 0.5536   |
| 1.3938        | 12.0  | 16152 | 1.0283          | 0.5635   |
| 1.3763        | 13.0  | 17498 | 1.0140          | 0.5740   |
| 1.3873        | 14.0  | 18844 | 1.0557          | 0.5470   |
| 1.3833        | 15.0  | 20190 | 1.0244          | 0.5638   |
| 1.385         | 16.0  | 21536 | 1.0345          | 0.5584   |
| 1.3492        | 17.0  | 22882 | 0.9997          | 0.5757   |
| 1.3332        | 18.0  | 24228 | 1.0106          | 0.5697   |
| 1.399         | 19.0  | 25574 | 0.9867          | 0.5846   |
| 1.3117        | 20.0  | 26920 | 0.9929          | 0.5833   |
| 1.362         | 21.0  | 28266 | 0.9895          | 0.5861   |
| 1.3279        | 22.0  | 29612 | 0.9853          | 0.5858   |
| 1.3057        | 23.0  | 30958 | 0.9872          | 0.5865   |
| 1.3217        | 24.0  | 32304 | 0.9761          | 0.5909   |
| 1.2854        | 25.0  | 33650 | 0.9800          | 0.5910   |
| 1.3194        | 26.0  | 34996 | 0.9867          | 0.5901   |
| 1.2733        | 27.0  | 36342 | 0.9927          | 0.5871   |
| 1.2949        | 28.0  | 37688 | 0.9755          | 0.5939   |
| 1.2836        | 29.0  | 39034 | 0.9738          | 0.5940   |
| 1.2974        | 30.0  | 40380 | 0.9722          | 0.5941   |


### Framework versions

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

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