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# swin-tiny-patch4-window7-224-finetuned-eurosat-finetuned-cifar100

This model was trained from scratch on the cifar10 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3047
- Accuracy: 0.9066

## 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7695        | 1.0   | 351  | 0.4700          | 0.8668   |
| 0.6836        | 2.0   | 703  | 0.3270          | 0.9      |
| 0.6207        | 2.99  | 1053 | 0.3047          | 0.9066   |


### Framework versions

- Transformers 4.30.1
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

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