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# AlaaHussien/weather_classifier

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: 0.1169
- Validation Loss: 0.2788
- Train Accuracy: 0.9206
- Train Precision: 0.9220
- Train Recall: 0.9206
- Train F1: 0.9208
- Epoch: 4

## 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': 27445, '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 |
|:----------:|:---------------:|:--------------:|:---------------:|:------------:|:--------:|:-----:|
| 0.1984     | 0.2676          | 0.9250         | 0.9266          | 0.9250       | 0.9244   | 0     |
| 0.1562     | 0.2494          | 0.9279         | 0.9293          | 0.9279       | 0.9280   | 1     |
| 0.1384     | 0.2656          | 0.9228         | 0.9238          | 0.9228       | 0.9227   | 2     |
| 0.1186     | 0.2668          | 0.9243         | 0.9248          | 0.9243       | 0.9238   | 3     |
| 0.1169     | 0.2788          | 0.9206         | 0.9220          | 0.9206       | 0.9208   | 4     |


### 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