---
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_keras_callback
model-index:
- name: vit-base-patch16-224-7class224
  results: []
---

<!-- 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. -->

# vit-base-patch16-224-7class224

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0078
- Train Accuracy: 0.9540
- Train Top-3-accuracy: 0.9960
- Validation Loss: 0.1065
- Validation Accuracy: 0.9569
- Validation Top-3-accuracy: 0.9963
- Epoch: 6

## 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': 630, '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 |
|:----------:|:--------------:|:--------------------:|:---------------:|:-------------------:|:-------------------------:|:-----:|
| 0.6954     | 0.6170         | 0.9295               | 0.3090          | 0.7653              | 0.9734                    | 0     |
| 0.1603     | 0.8272         | 0.9819               | 0.1722          | 0.8640              | 0.9865                    | 1     |
| 0.0448     | 0.8890         | 0.9892               | 0.1220          | 0.9071              | 0.9912                    | 2     |
| 0.0201     | 0.9192         | 0.9924               | 0.1171          | 0.9289              | 0.9934                    | 3     |
| 0.0132     | 0.9359         | 0.9942               | 0.1132          | 0.9416              | 0.9948                    | 4     |
| 0.0089     | 0.9466         | 0.9952               | 0.1095          | 0.9506              | 0.9957                    | 5     |
| 0.0078     | 0.9540         | 0.9960               | 0.1065          | 0.9569              | 0.9963                    | 6     |


### Framework versions

- Transformers 4.41.2
- TensorFlow 2.15.0
- Datasets 2.20.0
- Tokenizers 0.19.1