readme: ---
  license: apache-2.0
  tags:
  - image-classification
  - vision
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: convnext-small-224-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. -->
  
  # convnext-small-224-leicester_binary
  
  This model is a fine-tuned version of [facebook/convnext-small-224](https://huggingface.co/facebook/convnext-small-224) on the davanstrien/leicester_loaded_annotations_binary dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1283
  - F1: 0.9620
  
  ## 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: 30.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | No log        | 1.0   | 7    | 0.5143          | 0.8608 |
  | 0.5872        | 2.0   | 14   | 0.4215          | 0.8608 |
  | 0.3903        | 3.0   | 21   | 0.4127          | 0.8608 |
  | 0.3903        | 4.0   | 28   | 0.3605          | 0.8608 |
  | 0.3163        | 5.0   | 35   | 0.3152          | 0.8608 |
  | 0.2942        | 6.0   | 42   | 0.2942          | 0.8608 |
  | 0.2942        | 7.0   | 49   | 0.2669          | 0.8608 |
  | 0.2755        | 8.0   | 56   | 0.2316          | 0.8608 |
  | 0.2281        | 9.0   | 63   | 0.2104          | 0.8608 |
  | 0.2076        | 10.0  | 70   | 0.1938          | 0.8608 |
  | 0.2076        | 11.0  | 77   | 0.1803          | 0.8608 |
  | 0.1832        | 12.0  | 84   | 0.1704          | 0.8608 |
  | 0.1758        | 13.0  | 91   | 0.1650          | 0.8608 |
  | 0.1758        | 14.0  | 98   | 0.1714          | 0.8608 |
  | 0.167         | 15.0  | 105  | 0.1575          | 0.8608 |
  | 0.1519        | 16.0  | 112  | 0.1549          | 0.8608 |
  | 0.1519        | 17.0  | 119  | 0.1705          | 0.8608 |
  | 0.1422        | 18.0  | 126  | 0.1478          | 0.8608 |
  | 0.1444        | 19.0  | 133  | 0.1437          | 0.8608 |
  | 0.1396        | 20.0  | 140  | 0.1398          | 0.8608 |
  | 0.1396        | 21.0  | 147  | 0.1351          | 0.8608 |
  | 0.1293        | 22.0  | 154  | 0.1370          | 0.8987 |
  | 0.1361        | 23.0  | 161  | 0.1335          | 0.8987 |
  | 0.1361        | 24.0  | 168  | 0.1311          | 0.9367 |
  | 0.1246        | 25.0  | 175  | 0.1289          | 0.9620 |
  | 0.1211        | 26.0  | 182  | 0.1283          | 0.9620 |
  | 0.1211        | 27.0  | 189  | 0.1294          | 0.9620 |
  | 0.1182        | 28.0  | 196  | 0.1306          | 0.9620 |
  | 0.1172        | 29.0  | 203  | 0.1312          | 0.9620 |
  | 0.1102        | 30.0  | 210  | 0.1318          | 0.9620 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  