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# kruti-15/vit-base-patch16-224-in21k-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 an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0223
- Train Accuracy: 0.9964
- Train Top-3-accuracy: 1.0
- Train Apcer: 0.5004
- Train Bpcer: 0.4996
- Validation Loss: 0.0220
- Validation Accuracy: 0.9968
- Validation Top-3-accuracy: 1.0
- Validation Apcer: 0.4993
- Validation Bpcer: 0.5007
- Epoch: 4

## 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:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 135, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.09}
- training_precision: float32

### Training results

| Train Loss | Train Accuracy | Train Top-3-accuracy | Train Apcer | Train Bpcer | Validation Loss | Validation Accuracy | Validation Top-3-accuracy | Validation Apcer | Validation Bpcer | Epoch |
|:----------:|:--------------:|:--------------------:|:-----------:|:-----------:|:---------------:|:-------------------:|:-------------------------:|:----------------:|:----------------:|:-----:|
| 0.2475     | 0.9291         | 1.0                  | 0.5039      | 0.4961      | 0.0704          | 0.9830              | 1.0                       | 0.5016           | 0.4984           | 0     |
| 0.0475     | 0.9886         | 1.0                  | 0.4971      | 0.5029      | 0.0333          | 0.9917              | 1.0                       | 0.4972           | 0.5028           | 1     |
| 0.0289     | 0.9934         | 1.0                  | 0.5014      | 0.4986      | 0.0255          | 0.9946              | 1.0                       | 0.5003           | 0.4997           | 2     |
| 0.0240     | 0.9953         | 1.0                  | 0.5004      | 0.4996      | 0.0228          | 0.9959              | 1.0                       | 0.4990           | 0.5010           | 3     |
| 0.0223     | 0.9964         | 1.0                  | 0.5004      | 0.4996      | 0.0220          | 0.9968              | 1.0                       | 0.4993           | 0.5007           | 4     |


### Framework versions

- Transformers 4.39.3
- TensorFlow 2.15.0
- Datasets 2.18.0
- Tokenizers 0.15.2

real attack