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# weather-mod

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: 0.0907
- Accuracy: 0.9745

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4096        | 1.0   | 118  | 0.3402          | 0.8790   |
| 0.2749        | 2.0   | 236  | 0.1482          | 0.9490   |
| 0.1989        | 3.0   | 354  | 0.1297          | 0.9660   |
| 0.1129        | 4.0   | 472  | 0.1074          | 0.9788   |
| 0.0827        | 5.0   | 590  | 0.1023          | 0.9745   |
| 0.0644        | 6.0   | 708  | 0.0907          | 0.9745   |


### 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