
<!-- 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. -->

# AlaaHussien/weather_classifier_model2

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: 0.0700
- Validation Loss: 0.2853
- Train Accuracy: 0.9250
- Train Precision: 0.9267
- Train Recall: 0.9250
- Train F1: 0.9248
- Epoch: 19

## 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': 109780, '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 | Validation Loss | Train Accuracy | Train Precision | Train Recall | Train F1 | Epoch |
|:----------:|:---------------:|:--------------:|:---------------:|:------------:|:--------:|:-----:|
| 1.2545     | 0.6449          | 0.8944         | 0.9010          | 0.8944       | 0.8907   | 0     |
| 0.5392     | 0.3960          | 0.9177         | 0.9191          | 0.9177       | 0.9181   | 1     |
| 0.3498     | 0.3183          | 0.9264         | 0.9271          | 0.9264       | 0.9263   | 2     |
| 0.2787     | 0.2797          | 0.9323         | 0.9331          | 0.9323       | 0.9323   | 3     |
| 0.2155     | 0.2695          | 0.9257         | 0.9279          | 0.9257       | 0.9260   | 4     |
| 0.1899     | 0.3079          | 0.9126         | 0.9165          | 0.9126       | 0.9121   | 5     |
| 0.1599     | 0.2749          | 0.9235         | 0.9259          | 0.9235       | 0.9241   | 6     |
| 0.1470     | 0.2709          | 0.9243         | 0.9257          | 0.9243       | 0.9237   | 7     |
| 0.1305     | 0.2566          | 0.9257         | 0.9263          | 0.9257       | 0.9259   | 8     |
| 0.1131     | 0.2699          | 0.9257         | 0.9271          | 0.9257       | 0.9260   | 9     |
| 0.1042     | 0.2719          | 0.9228         | 0.9240          | 0.9228       | 0.9229   | 10    |
| 0.0977     | 0.2857          | 0.9199         | 0.9208          | 0.9199       | 0.9197   | 11    |
| 0.0816     | 0.2592          | 0.9279         | 0.9294          | 0.9279       | 0.9281   | 12    |
| 0.0894     | 0.2888          | 0.9228         | 0.9256          | 0.9228       | 0.9226   | 13    |
| 0.1011     | 0.2978          | 0.9264         | 0.9287          | 0.9264       | 0.9264   | 14    |
| 0.0756     | 0.2590          | 0.9330         | 0.9344          | 0.9330       | 0.9330   | 15    |
| 0.0668     | 0.2863          | 0.9228         | 0.9255          | 0.9228       | 0.9235   | 16    |
| 0.0650     | 0.2871          | 0.9264         | 0.9282          | 0.9264       | 0.9262   | 17    |
| 0.0644     | 0.3003          | 0.9257         | 0.9279          | 0.9257       | 0.9261   | 18    |
| 0.0700     | 0.2853          | 0.9250         | 0.9267          | 0.9250       | 0.9248   | 19    |


### Framework versions

- Transformers 4.51.3
- TensorFlow 2.18.0
- Datasets 3.6.0
- Tokenizers 0.21.1

dew fogsmog frost glaze hail lightning rain rainbow rime sandstorm snow