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# Remote-Sensing-UAV-image-classification

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an [jonathan-roberts1/RSSCN7](https://huggingface.co/datasets/jonathan-roberts1/RSSCN7) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0593
- Accuracy: 0.9907

## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3922        | 0.71  | 100  | 0.4227          | 0.8821   |
| 0.2986        | 1.43  | 200  | 0.3142          | 0.9089   |
| 0.1109        | 2.14  | 300  | 0.2056          | 0.9518   |
| 0.0864        | 2.86  | 400  | 0.2472          | 0.9375   |
| 0.0193        | 3.57  | 500  | 0.0593          | 0.9907   |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
field forest grass industry parking resident river or lake