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# deit-tiny-patch16-224-FireRisk

This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9478
- Accuracy: 0.6253
- Precision: 0.5221
- Recall: 0.5179
- F1: 0.5190

## 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: 0.0001
- train_batch_size: 512
- eval_batch_size: 512
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.9714        | 1.0   | 138  | 0.9923          | 0.6114   | 0.5167    | 0.5118 | 0.5070 |
| 0.9482        | 2.0   | 276  | 0.9760          | 0.6094   | 0.4985    | 0.5138 | 0.5030 |
| 0.9263        | 3.0   | 414  | 0.9398          | 0.6314   | 0.5226    | 0.5202 | 0.5180 |
| 0.903         | 4.0   | 552  | 0.9683          | 0.6183   | 0.5141    | 0.5021 | 0.5039 |
| 0.8536        | 5.0   | 690  | 0.9478          | 0.6253   | 0.5221    | 0.5179 | 0.5190 |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0

very low low moderate high very high non-burnable water