readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: dit_base_binary_task
    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. -->
  
  # dit_base_binary_task
  
  This model is a fine-tuned version of [microsoft/dit-base](https://huggingface.co/microsoft/dit-base) on the davanstrien/leicester_loaded_annotations_binary dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0513
  - Accuracy: 0.9873
  - F1: 0.9600
  
  ## 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: 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: 50
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | No log        | 0.87  | 5    | 0.6816          | 0.5      | 0.2476 |
  | 0.7387        | 1.87  | 10   | 0.5142          | 0.8354   | 0.0    |
  | 0.7387        | 2.87  | 15   | 0.4690          | 0.8354   | 0.0    |
  | 0.4219        | 3.87  | 20   | 0.5460          | 0.8354   | 0.0    |
  | 0.4219        | 4.87  | 25   | 0.4703          | 0.8354   | 0.0    |
  | 0.3734        | 5.87  | 30   | 0.4371          | 0.8354   | 0.0    |
  | 0.3734        | 6.87  | 35   | 0.4147          | 0.8354   | 0.0    |
  | 0.3261        | 7.87  | 40   | 0.4272          | 0.8354   | 0.0    |
  | 0.3261        | 8.87  | 45   | 0.4038          | 0.8354   | 0.0    |
  | 0.3078        | 9.87  | 50   | 0.3418          | 0.8354   | 0.0    |
  | 0.3078        | 10.87 | 55   | 0.3042          | 0.8354   | 0.0    |
  | 0.2501        | 11.87 | 60   | 0.2799          | 0.8354   | 0.0    |
  | 0.2501        | 12.87 | 65   | 0.1419          | 0.9367   | 0.7619 |
  | 0.1987        | 13.87 | 70   | 0.1224          | 0.9494   | 0.8182 |
  | 0.1987        | 14.87 | 75   | 0.0749          | 0.9747   | 0.9167 |
  | 0.1391        | 15.87 | 80   | 0.0539          | 0.9810   | 0.9412 |
  | 0.1391        | 16.87 | 85   | 0.0830          | 0.9873   | 0.9600 |
  | 0.1085        | 17.87 | 90   | 0.0443          | 0.9873   | 0.9600 |
  | 0.1085        | 18.87 | 95   | 0.0258          | 0.9937   | 0.9804 |
  | 0.1039        | 19.87 | 100  | 0.1025          | 0.9684   | 0.8936 |
  | 0.1039        | 20.87 | 105  | 0.1597          | 0.9684   | 0.8936 |
  | 0.1217        | 21.87 | 110  | 0.0278          | 0.9937   | 0.9811 |
  | 0.1217        | 22.87 | 115  | 0.0458          | 0.9873   | 0.9600 |
  | 0.0609        | 23.87 | 120  | 0.0478          | 0.9937   | 0.9804 |
  | 0.0609        | 24.87 | 125  | 0.0671          | 0.9747   | 0.9231 |
  | 0.1031        | 25.87 | 130  | 0.0751          | 0.9873   | 0.9600 |
  | 0.1031        | 26.87 | 135  | 0.1963          | 0.9557   | 0.8444 |
  | 0.0601        | 27.87 | 140  | 0.0870          | 0.9747   | 0.9167 |
  | 0.0601        | 28.87 | 145  | 0.0890          | 0.9747   | 0.9167 |
  | 0.0799        | 29.87 | 150  | 0.1017          | 0.9747   | 0.9167 |
  | 0.0799        | 30.87 | 155  | 0.0041          | 1.0      | 1.0    |
  | 0.0441        | 31.87 | 160  | 0.0332          | 0.9873   | 0.9615 |
  | 0.0441        | 32.87 | 165  | 0.0839          | 0.9747   | 0.9167 |
  | 0.0757        | 33.87 | 170  | 0.0722          | 0.9873   | 0.9600 |
  | 0.0757        | 34.87 | 175  | 0.0168          | 0.9937   | 0.9804 |
  | 0.0555        | 35.87 | 180  | 0.0443          | 0.9937   | 0.9804 |
  | 0.0555        | 36.87 | 185  | 0.0227          | 0.9873   | 0.9615 |
  | 0.0336        | 37.87 | 190  | 0.0128          | 0.9937   | 0.9804 |
  | 0.0336        | 38.87 | 195  | 0.0169          | 0.9937   | 0.9811 |
  | 0.0405        | 39.87 | 200  | 0.0193          | 0.9937   | 0.9804 |
  | 0.0405        | 40.87 | 205  | 0.1216          | 0.9810   | 0.9388 |
  | 0.0578        | 41.87 | 210  | 0.0307          | 0.9937   | 0.9804 |
  | 0.0578        | 42.87 | 215  | 0.0539          | 0.9873   | 0.9600 |
  | 0.0338        | 43.87 | 220  | 0.0573          | 0.9937   | 0.9804 |
  | 0.0338        | 44.87 | 225  | 0.0086          | 1.0      | 1.0    |
  | 0.0417        | 45.87 | 230  | 0.0491          | 0.9873   | 0.9600 |
  | 0.0417        | 46.87 | 235  | 0.0089          | 1.0      | 1.0    |
  | 0.0538        | 47.87 | 240  | 0.0846          | 0.9810   | 0.9388 |
  | 0.0538        | 48.87 | 245  | 0.0452          | 0.9810   | 0.9388 |
  | 0.0364        | 49.87 | 250  | 0.0513          | 0.9873   | 0.9600 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.12.1
  - Datasets 2.7.1
  - Tokenizers 0.13.1
  