readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: 4L_weight_decay
    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. -->
  
  # 4L_weight_decay
  
  This model was trained from scratch on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1312
  - Precision: 0.7006
  - Recall: 0.6863
  - F1: 0.6934
  - Accuracy: 0.9524
  
  ## 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: 3e-05
  - train_batch_size: 16
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | 0.157         | 1.0   | 5561  | 0.1464          | 0.6943    | 0.6153 | 0.6524 | 0.9465   |
  | 0.1454        | 2.0   | 11122 | 0.1396          | 0.6921    | 0.6491 | 0.6699 | 0.9486   |
  | 0.1414        | 3.0   | 16683 | 0.1372          | 0.6841    | 0.6746 | 0.6793 | 0.9492   |
  | 0.1335        | 4.0   | 22244 | 0.1339          | 0.6997    | 0.6617 | 0.6802 | 0.9505   |
  | 0.1308        | 5.0   | 27805 | 0.1339          | 0.6963    | 0.6763 | 0.6862 | 0.9510   |
  | 0.1285        | 6.0   | 33366 | 0.1320          | 0.7102    | 0.6639 | 0.6863 | 0.9519   |
  | 0.1257        | 7.0   | 38927 | 0.1306          | 0.7031    | 0.6771 | 0.6898 | 0.9521   |
  | 0.1222        | 8.0   | 44488 | 0.1324          | 0.7005    | 0.6836 | 0.6919 | 0.9522   |
  | 0.1207        | 9.0   | 50049 | 0.1313          | 0.7017    | 0.6832 | 0.6923 | 0.9524   |
  | 0.1195        | 10.0  | 55610 | 0.1312          | 0.7006    | 0.6863 | 0.6934 | 0.9524   |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.11.0+cu113
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  