readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - imagefolder
  metrics:
  - accuracy
  model-index:
  - name: fogsmog_hfclass
    results:
    - task:
        name: Image Classification
        type: image-classification
      dataset:
        name: imagefolder
        type: imagefolder
        config: default
        split: test
        args: default
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.91
  ---
  
  <!-- 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. -->
  
  # fogsmog_hfclass
  
  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 imagefolder dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3700
  - Accuracy: 0.91
  
  ## 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: 16
  - eval_batch_size: 16
  - seed: 42
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 64
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_ratio: 0.1
  - num_epochs: 20
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.6766        | 1.0   | 25   | 0.6299          | 0.795    |
  | 0.3444        | 2.0   | 50   | 0.3701          | 0.8625   |
  | 0.2456        | 3.0   | 75   | 0.2988          | 0.885    |
  | 0.1402        | 4.0   | 100  | 0.3076          | 0.905    |
  | 0.1275        | 5.0   | 125  | 0.4505          | 0.8525   |
  | 0.0909        | 6.0   | 150  | 0.3739          | 0.8825   |
  | 0.0792        | 7.0   | 175  | 0.3642          | 0.885    |
  | 0.0482        | 8.0   | 200  | 0.3812          | 0.885    |
  | 0.0451        | 9.0   | 225  | 0.3290          | 0.9      |
  | 0.0526        | 10.0  | 250  | 0.4004          | 0.8825   |
  | 0.0575        | 11.0  | 275  | 0.2842          | 0.925    |
  | 0.0457        | 12.0  | 300  | 0.3952          | 0.895    |
  | 0.0505        | 13.0  | 325  | 0.4411          | 0.885    |
  | 0.0324        | 14.0  | 350  | 0.4185          | 0.8925   |
  | 0.0354        | 15.0  | 375  | 0.3347          | 0.9025   |
  | 0.0443        | 16.0  | 400  | 0.2949          | 0.915    |
  | 0.0305        | 17.0  | 425  | 0.3603          | 0.905    |
  | 0.0234        | 18.0  | 450  | 0.3858          | 0.8875   |
  | 0.0219        | 19.0  | 475  | 0.3541          | 0.91     |
  | 0.0284        | 20.0  | 500  | 0.3700          | 0.91     |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.13.1+cu117
  - Datasets 2.9.0
  - Tokenizers 0.13.2
  