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# google_eurosat

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the image_folder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0650
- Accuracy: 0.9894

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.1819        | 1.0    | 608  | 0.1604          | 0.9759   |
| 0.6554        | 2.0    | 1216 | 0.0953          | 0.9824   |
| 0.4079        | 2.9959 | 1821 | 0.0650          | 0.9894   |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.2.0+cpu
- Datasets 2.0.0
- Tokenizers 0.21.0

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