
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->

# jayashprasad/vit-base-patch16-224-in21k-rock360

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on Rock 360 dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.4089
- Train Accuracy: 0.9875
- Validation Loss: 0.7470
- Validation Accuracy: 0.7250
- Epoch: 7

## 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': {'class_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 160, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}}, 'dynamic': True, 'initial_scale': 32768.0, 'dynamic_growth_steps': 2000}
- training_precision: mixed_float16

### Training results

| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 1.0814     | 0.4417         | 1.0415          | 0.5917              | 0     |
| 0.9565     | 0.7917         | 0.9933          | 0.6667              | 1     |
| 0.8566     | 0.8542         | 0.9488          | 0.6833              | 2     |
| 0.7581     | 0.9208         | 0.9017          | 0.6833              | 3     |
| 0.6599     | 0.9500         | 0.8592          | 0.7250              | 4     |
| 0.5664     | 0.9667         | 0.8179          | 0.7083              | 5     |
| 0.4843     | 0.9833         | 0.7797          | 0.7333              | 6     |
| 0.4089     | 0.9875         | 0.7470          | 0.7250              | 7     |


### Framework versions

- Transformers 4.35.2
- TensorFlow 2.10.1
- Datasets 2.15.0
- Tokenizers 0.15.0

i m s