readme: ---
  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
  