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# vit-fire-detection

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:
- Loss: 0.0087
- Precision: 0.9974
- Recall: 0.9974
- Accuracy: 0.9974
- F1 Score: 0.9974

## 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: 0.0002
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Accuracy | F1 Score |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:--------:|:--------:|
| 0.0928        | 1.0   | 190  | 0.0455          | 0.9870    | 0.9868 | 0.9868   | 0.9869   |
| 0.0432        | 2.0   | 380  | 0.0477          | 0.9885    | 0.9881 | 0.9881   | 0.9883   |
| 0.0186        | 3.0   | 570  | 0.0156          | 0.9974    | 0.9974 | 0.9974   | 0.9974   |
| 0.015         | 4.0   | 760  | 0.0208          | 0.9961    | 0.9960 | 0.9960   | 0.9961   |
| 0.0043        | 5.0   | 950  | 0.0087          | 0.9974    | 0.9974 | 0.9974   | 0.9974   |


### Framework versions

- Transformers 4.36.0
- Pytorch 2.1.1+cpu
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "accuracy"], "base_model": "google/vit-base-patch16-224-in21k", "model-index": [{"name": "vit-fire-detection", "results": []}]}
transformers tensorboard safetensors vit image-classification generated_from_trainer base_model:google/vit-base-patch16-224-in21k license:apache-2.0 autotrain_compatible endpoints_compatible region:us