---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_keras_callback
model-index:
- name: VIT_fourclass_Jun25
  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_fourclass_Jun25

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: 0.0938
- Validation Loss: 2.3960
- Train Accuracy: 0.51
- Epoch: 14

## 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': 'SGD', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': np.float32(0.01), 'momentum': 0.0, 'nesterov': False}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Train Accuracy | Epoch |
|:----------:|:---------------:|:--------------:|:-----:|
| 0.9196     | 1.2060          | 0.38           | 0     |
| 0.3792     | 1.4807          | 0.48           | 1     |
| 0.2729     | 1.7396          | 0.45           | 2     |
| 0.2006     | 2.4379          | 0.29           | 3     |
| 0.1996     | 2.4795          | 0.36           | 4     |
| 0.1734     | 2.7916          | 0.35           | 5     |
| 0.1860     | 4.1270          | 0.09           | 6     |
| 0.1490     | 2.7235          | 0.37           | 7     |
| 0.1077     | 3.5380          | 0.26           | 8     |
| 0.1173     | 2.7697          | 0.42           | 9     |
| 0.1526     | 2.7868          | 0.42           | 10    |
| 0.1161     | 3.1132          | 0.36           | 11    |
| 0.1093     | 3.5738          | 0.33           | 12    |
| 0.0884     | 3.1227          | 0.37           | 13    |
| 0.0938     | 2.3960          | 0.51           | 14    |


### Framework versions

- Transformers 4.52.4
- TensorFlow 2.18.0
- Datasets 3.6.0
- Tokenizers 0.21.1