readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - sort_v2
  metrics:
  - f1
  - accuracy
  model-index:
  - name: favs_sort_classification_v2
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: sort_v2
        type: sort_v2
        config: default
        split: train
        args: default
      metrics:
      - name: F1
        type: f1
        value: 0.9801324503311257
      - name: Accuracy
        type: accuracy
        value: 0.896551724137931
  ---
  
  <!-- 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. -->
  
  # favs_sort_classification_v2
  
  This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the sort_v2 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1553
  - F1: 0.9801
  - Roc Auc: 0.9805
  - Accuracy: 0.8966
  
  ## 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: 1.5e-05
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 25
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
  | 0.5589        | 1.0   | 21   | 0.5325          | 0.4815 | 0.6585  | 0.0345   |
  | 0.4621        | 2.0   | 42   | 0.4465          | 0.5225 | 0.6780  | 0.0      |
  | 0.4144        | 3.0   | 63   | 0.4131          | 0.5950 | 0.7172  | 0.0345   |
  | 0.3669        | 4.0   | 84   | 0.3793          | 0.6167 | 0.7279  | 0.0345   |
  | 0.3524        | 5.0   | 105  | 0.3455          | 0.6880 | 0.7689  | 0.0690   |
  | 0.2987        | 6.0   | 126  | 0.3086          | 0.8116 | 0.8533  | 0.4138   |
  | 0.2734        | 7.0   | 147  | 0.2767          | 0.8392 | 0.8772  | 0.5172   |
  | 0.2532        | 8.0   | 168  | 0.2483          | 0.8472 | 0.8837  | 0.5172   |
  | 0.2166        | 9.0   | 189  | 0.2285          | 0.8707 | 0.9032  | 0.5862   |
  | 0.19          | 10.0  | 210  | 0.2012          | 0.9459 | 0.9525  | 0.7586   |
  | 0.1833        | 11.0  | 231  | 0.1856          | 0.9530 | 0.9590  | 0.7931   |
  | 0.1751        | 12.0  | 252  | 0.1748          | 0.9595 | 0.9610  | 0.7931   |
  | 0.173         | 13.0  | 273  | 0.1633          | 0.9467 | 0.9569  | 0.7931   |
  | 0.16          | 14.0  | 294  | 0.1553          | 0.9801 | 0.9805  | 0.8966   |
  | 0.1396        | 15.0  | 315  | 0.1503          | 0.9733 | 0.9740  | 0.8621   |
  | 0.1467        | 16.0  | 336  | 0.1417          | 0.9737 | 0.9785  | 0.8621   |
  | 0.1271        | 17.0  | 357  | 0.1380          | 0.9669 | 0.9720  | 0.8621   |
  | 0.1228        | 18.0  | 378  | 0.1346          | 0.9669 | 0.9720  | 0.8621   |
  | 0.1257        | 19.0  | 399  | 0.1308          | 0.9801 | 0.9805  | 0.8966   |
  | 0.1156        | 20.0  | 420  | 0.1280          | 0.9801 | 0.9805  | 0.8966   |
  | 0.1242        | 21.0  | 441  | 0.1250          | 0.9801 | 0.9805  | 0.8966   |
  | 0.1146        | 22.0  | 462  | 0.1236          | 0.9801 | 0.9805  | 0.8966   |
  | 0.1262        | 23.0  | 483  | 0.1228          | 0.9801 | 0.9805  | 0.8966   |
  | 0.1268        | 24.0  | 504  | 0.1227          | 0.9801 | 0.9805  | 0.8966   |
  | 0.1133        | 25.0  | 525  | 0.1224          | 0.9801 | 0.9805  | 0.8966   |
  
  
  ### Framework versions
  
  - Transformers 4.21.1
  - Pytorch 1.12.1
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  