readme: ---
  license: apache-2.0
  tags:
  - image-classification
  - vision
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: vit-base-patch32-224-in21-leicester_binary
    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-base-patch32-224-in21-leicester_binary
  
  This model is a fine-tuned version of [google/vit-base-patch32-224-in21k](https://huggingface.co/google/vit-base-patch32-224-in21k) on the davanstrien/leicester_loaded_annotations_binary dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0628
  - F1: 0.9873
  
  ## 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: 2e-05
  - train_batch_size: 64
  - eval_batch_size: 128
  - seed: 1337
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 40.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | No log        | 1.0   | 7    | 0.4529          | 0.8608 |
  | 0.5024        | 2.0   | 14   | 0.3989          | 0.8608 |
  | 0.3533        | 3.0   | 21   | 0.3741          | 0.8608 |
  | 0.3533        | 4.0   | 28   | 0.3161          | 0.8608 |
  | 0.285         | 5.0   | 35   | 0.2824          | 0.8608 |
  | 0.2491        | 6.0   | 42   | 0.2701          | 0.8608 |
  | 0.2491        | 7.0   | 49   | 0.2062          | 0.9114 |
  | 0.2032        | 8.0   | 56   | 0.2050          | 0.9494 |
  | 0.157         | 9.0   | 63   | 0.2013          | 0.9494 |
  | 0.1127        | 10.0  | 70   | 0.1960          | 0.9367 |
  | 0.1127        | 11.0  | 77   | 0.1417          | 0.9494 |
  | 0.0903        | 12.0  | 84   | 0.1307          | 0.9494 |
  | 0.0922        | 13.0  | 91   | 0.0870          | 0.9873 |
  | 0.0922        | 14.0  | 98   | 0.2048          | 0.9241 |
  | 0.0595        | 15.0  | 105  | 0.1204          | 0.9620 |
  | 0.0527        | 16.0  | 112  | 0.2553          | 0.9367 |
  | 0.0527        | 17.0  | 119  | 0.1675          | 0.9367 |
  | 0.0477        | 18.0  | 126  | 0.2265          | 0.9241 |
  | 0.0411        | 19.0  | 133  | 0.1901          | 0.9367 |
  | 0.0299        | 20.0  | 140  | 0.2423          | 0.9241 |
  | 0.0299        | 21.0  | 147  | 0.0639          | 0.9873 |
  | 0.0487        | 22.0  | 154  | 0.1255          | 0.9494 |
  | 0.0359        | 23.0  | 161  | 0.1213          | 0.9494 |
  | 0.0359        | 24.0  | 168  | 0.0727          | 0.9747 |
  | 0.0302        | 25.0  | 175  | 0.1116          | 0.9494 |
  | 0.0304        | 26.0  | 182  | 0.1062          | 0.9494 |
  | 0.0304        | 27.0  | 189  | 0.2097          | 0.9241 |
  | 0.0274        | 28.0  | 196  | 0.1276          | 0.9494 |
  | 0.0291        | 29.0  | 203  | 0.0967          | 0.9494 |
  | 0.0202        | 30.0  | 210  | 0.0765          | 0.9747 |
  | 0.0202        | 31.0  | 217  | 0.0628          | 0.9873 |
  | 0.0232        | 32.0  | 224  | 0.1388          | 0.9494 |
  | 0.0264        | 33.0  | 231  | 0.1062          | 0.9494 |
  | 0.0264        | 34.0  | 238  | 0.1320          | 0.9494 |
  | 0.0219        | 35.0  | 245  | 0.1528          | 0.9494 |
  | 0.0194        | 36.0  | 252  | 0.1746          | 0.9494 |
  | 0.0194        | 37.0  | 259  | 0.1609          | 0.9494 |
  | 0.0204        | 38.0  | 266  | 0.1482          | 0.9494 |
  | 0.0217        | 39.0  | 273  | 0.1522          | 0.9494 |
  | 0.0216        | 40.0  | 280  | 0.1499          | 0.9494 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  