
<!-- 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. -->

# RenSurii/vit-base-patch16-224-in21k-finetuned-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 the mnist dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.3712
- Train Accuracy: 0.9621
- Validation Loss: 0.3312
- Validation Accuracy: 0.9621
- Epoch: 5

## 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': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': 1.0, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': False, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 6000, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 2.0107     | 0.8548         | 1.5288          | 0.8548              | 0     |
| 1.3538     | 0.9149         | 0.9913          | 0.9149              | 1     |
| 0.9517     | 0.934          | 0.7421          | 0.9340              | 2     |
| 0.6882     | 0.9467         | 0.5690          | 0.9467              | 3     |
| 0.4999     | 0.9554         | 0.4264          | 0.9554              | 4     |
| 0.3712     | 0.9621         | 0.3312          | 0.9621              | 5     |


### Framework versions

- Transformers 4.47.0.dev0
- TensorFlow 2.18.0
- Datasets 3.1.0
- Tokenizers 0.20.3

0 1 2 3 4 5 6 7 8 9