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# satyam2652/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: 3.1431
- Train Accuracy: 1.0
- Train Top-3-accuracy: 1.0
- Validation Loss: 3.6270
- Validation Accuracy: 0.9566
- Validation Top-3-accuracy: 0.9948
- Epoch: 9

## 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': 1680, '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': 0.01}
- training_precision: float32

### Training results

| Train Loss | Train Accuracy | Train Top-3-accuracy | Validation Loss | Validation Accuracy | Validation Top-3-accuracy | Epoch |
|:----------:|:--------------:|:--------------------:|:---------------:|:-------------------:|:-------------------------:|:-----:|
| 5.3716     | 0.1168         | 0.1875               | 5.2023          | 0.3802              | 0.5556                    | 0     |
| 4.8783     | 0.7768         | 0.8929               | 4.7966          | 0.7257              | 0.9115                    | 1     |
| 4.4274     | 0.9360         | 0.9933               | 4.4790          | 0.8212              | 0.9618                    | 2     |
| 4.0789     | 0.9769         | 0.9985               | 4.2315          | 0.8837              | 0.9740                    | 3     |
| 3.8025     | 0.9926         | 1.0                  | 4.0327          | 0.9062              | 0.9878                    | 4     |
| 3.5840     | 0.9970         | 1.0                  | 3.8840          | 0.9253              | 0.9913                    | 5     |
| 3.4123     | 1.0            | 1.0                  | 3.7695          | 0.9392              | 0.9931                    | 6     |
| 3.2826     | 1.0            | 1.0                  | 3.6876          | 0.9462              | 0.9948                    | 7     |
| 3.1937     | 1.0            | 1.0                  | 3.6414          | 0.9583              | 0.9948                    | 8     |
| 3.1431     | 1.0            | 1.0                  | 3.6270          | 0.9566              | 0.9948                    | 9     |


### Framework versions

- Transformers 4.37.2
- TensorFlow 2.15.0
- Datasets 2.16.1
- Tokenizers 0.15.1

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