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# vit-msn-small-finetuned-eurosat

This model is a fine-tuned version of [facebook/vit-msn-small](https://huggingface.co/facebook/vit-msn-small) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6607
- Accuracy: 0.8105

## 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: 0.0002
- 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: 6

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.115         | 0.9362 | 11   | 1.0397          | 0.6526   |
| 0.8536        | 1.9574 | 23   | 0.7698          | 0.7579   |
| 0.5677        | 2.9787 | 35   | 0.7200          | 0.7895   |
| 0.419         | 4.0    | 47   | 0.7286          | 0.7842   |
| 0.3365        | 4.9362 | 58   | 0.6607          | 0.8105   |
| 0.2317        | 5.6170 | 66   | 0.6649          | 0.8      |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1

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