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# swin-tiny-patch4-window7-224-finetuned-eurosat-kornia

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: 0.5886
- Accuracy: 0.5909

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 3    | 0.6243          | 0.6818   |
| No log        | 2.0   | 6    | 0.5460          | 0.7273   |
| No log        | 3.0   | 9    | 0.5540          | 0.7273   |
| 0.6502        | 4.0   | 12   | 0.5747          | 0.6818   |
| 0.6502        | 5.0   | 15   | 0.5886          | 0.5909   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0

clethrionomys sylvaemus