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# traynothein_resize_foreclasss

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: 0.0744
- Train Accuracy: 0.9404
- Train Top-3-accuracy: 0.9991
- Validation Loss: 0.2720
- Validation Accuracy: 0.9431
- Validation Top-3-accuracy: 0.9991
- 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': 658, '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 |
|:----------:|:--------------:|:--------------------:|:---------------:|:-------------------:|:-------------------------:|:-----:|
| 0.6708     | 0.7378         | 0.9752               | 0.4218          | 0.8246              | 0.9933                    | 0     |
| 0.3109     | 0.8569         | 0.9956               | 0.3083          | 0.8754              | 0.9968                    | 1     |
| 0.2024     | 0.8899         | 0.9975               | 0.2776          | 0.9011              | 0.9979                    | 2     |
| 0.1370     | 0.9104         | 0.9982               | 0.2734          | 0.9170              | 0.9985                    | 3     |
| 0.0996     | 0.9237         | 0.9986               | 0.2775          | 0.9288              | 0.9988                    | 4     |
| 0.0814     | 0.9334         | 0.9989               | 0.2695          | 0.9372              | 0.9990                    | 5     |
| 0.0744     | 0.9404         | 0.9991               | 0.2720          | 0.9431              | 0.9991                    | 6     |


### Framework versions

- Transformers 4.44.2
- TensorFlow 2.15.1
- Datasets 3.0.0
- Tokenizers 0.19.1

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