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# weather-base

This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2184
- Accuracy: 0.9359

## 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:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3368        | 1.0   | 171  | 0.2780          | 0.9009   |
| 0.2129        | 2.0   | 342  | 0.2333          | 0.9300   |
| 0.1827        | 3.0   | 513  | 0.2440          | 0.9213   |
| 0.1475        | 4.0   | 684  | 0.2306          | 0.9315   |
| 0.1284        | 5.0   | 855  | 0.2192          | 0.9359   |
| 0.0526        | 6.0   | 1026 | 0.2184          | 0.9359   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2

dew fogsmog frost glaze hail lightning rain rainbow rime sandstorm snow