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# srikrishnateja/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: 0.0403
- Train Accuracy: 0.9952
- Train Top-3-accuracy: 1.0
- Validation Loss: 0.1351
- Validation Accuracy: 0.9645
- Validation Top-3-accuracy: 1.0
- 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: {'inner_optimizer': {'module': 'transformers.optimization_tf', 'class_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 425, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.8999999761581421, 'beta_2': 0.9990000128746033, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}, 'registered_name': 'AdamWeightDecay'}, 'dynamic': True, 'initial_scale': 32768.0, 'dynamic_growth_steps': 2000}
- training_precision: mixed_float16

### Training results

| Train Loss | Train Accuracy | Train Top-3-accuracy | Validation Loss | Validation Accuracy | Validation Top-3-accuracy | Epoch |
|:----------:|:--------------:|:--------------------:|:---------------:|:-------------------:|:-------------------------:|:-----:|
| 0.4326     | 0.8143         | 1.0                  | 0.2613          | 0.9102              | 1.0                       | 0     |
| 0.1770     | 0.9413         | 1.0                  | 0.1919          | 0.9332              | 1.0                       | 1     |
| 0.0943     | 0.9760         | 1.0                  | 0.1654          | 0.9436              | 1.0                       | 2     |
| 0.0576     | 0.9863         | 1.0                  | 0.1457          | 0.9520              | 1.0                       | 3     |
| 0.0403     | 0.9952         | 1.0                  | 0.1351          | 0.9645              | 1.0                       | 4     |


### Framework versions

- Transformers 4.38.1
- TensorFlow 2.15.0
- Datasets 2.17.1
- Tokenizers 0.15.1

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