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# AlaaHussien/final_weather

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: 0.1179
- Validation Loss: 0.2876
- Train Accuracy: 0.9235
- Train Precision: 0.9249
- Train Recall: 0.9235
- Train F1: 0.9237
- 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 |
|:----------:|:---------------:|:--------------:|:---------------:|:------------:|:--------:|:-----:|
| 0.1824     | 0.3373          | 0.9039         | 0.9071          | 0.9039       | 0.9041   | 0     |
| 0.1671     | 0.2880          | 0.9133         | 0.9159          | 0.9133       | 0.9132   | 1     |
| 0.1320     | 0.3227          | 0.9126         | 0.9149          | 0.9126       | 0.9127   | 2     |
| 0.1241     | 0.2833          | 0.9199         | 0.9223          | 0.9199       | 0.9200   | 3     |
| 0.1179     | 0.2876          | 0.9235         | 0.9249          | 0.9235       | 0.9237   | 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