---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
model-index:
- name: vit-fire-detection
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# 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 the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0524
- Precision: 0.9803
- Recall: 0.9802

## 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: 0.002
- 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 0.5087        | 1.0   | 190  | 0.5356          | 0.8054    | 0.7421 |
| 0.2943        | 2.0   | 380  | 0.1430          | 0.9536    | 0.9524 |
| 0.2409        | 3.0   | 570  | 0.1360          | 0.9541    | 0.9537 |
| 0.1722        | 4.0   | 760  | 0.1265          | 0.9557    | 0.9550 |
| 0.1726        | 5.0   | 950  | 0.1011          | 0.9633    | 0.9630 |
| 0.1563        | 6.0   | 1140 | 0.0946          | 0.9695    | 0.9696 |
| 0.1181        | 7.0   | 1330 | 0.0961          | 0.9643    | 0.9630 |
| 0.1288        | 8.0   | 1520 | 0.0616          | 0.9765    | 0.9762 |
| 0.0858        | 9.0   | 1710 | 0.0699          | 0.9765    | 0.9762 |
| 0.0539        | 10.0  | 1900 | 0.0524          | 0.9803    | 0.9802 |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.14.0.dev20221111
- Datasets 2.8.0
- Tokenizers 0.12.1