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# Entrnal_5class_agumm_last_newV7_model

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: 0.0959
- Train Accuracy: 0.9365
- Train Top-3-accuracy: 0.9913
- Validation Loss: 0.3424
- Validation Accuracy: 0.9390
- Validation Top-3-accuracy: 0.9917
- Epoch: 9

## 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': 620, '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 |
|:----------:|:--------------:|:--------------------:|:---------------:|:-------------------:|:-------------------------:|:-----:|
| 1.1895     | 0.4833         | 0.8342               | 0.8125          | 0.6525              | 0.9200                    | 0     |
| 0.5511     | 0.7329         | 0.9448               | 0.4587          | 0.7829              | 0.9601                    | 1     |
| 0.3174     | 0.8164         | 0.9677               | 0.3909          | 0.8395              | 0.9735                    | 2     |
| 0.2299     | 0.8576         | 0.9772               | 0.3711          | 0.8709              | 0.9802                    | 3     |
| 0.1699     | 0.8824         | 0.9824               | 0.3564          | 0.8920              | 0.9842                    | 4     |
| 0.1344     | 0.9003         | 0.9856               | 0.3389          | 0.9073              | 0.9865                    | 5     |
| 0.1187     | 0.9131         | 0.9875               | 0.3391          | 0.9183              | 0.9884                    | 6     |
| 0.1060     | 0.9229         | 0.9891               | 0.3424          | 0.9267              | 0.9898                    | 7     |
| 0.0992     | 0.9304         | 0.9903               | 0.3426          | 0.9334              | 0.9908                    | 8     |
| 0.0959     | 0.9365         | 0.9913               | 0.3424          | 0.9390              | 0.9917                    | 9     |


### Framework versions

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

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