readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: tiny_no_focal_v2
    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. -->
  
  # tiny_no_focal_v2
  
  This model was trained from scratch on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1314
  - Precision: 0.7013
  - Recall: 0.6837
  - F1: 0.6924
  - Accuracy: 0.9522
  
  ## 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | 0.1574        | 1.0   | 5561  | 0.1471          | 0.6907    | 0.6186 | 0.6527 | 0.9462   |
  | 0.1456        | 2.0   | 11122 | 0.1396          | 0.6923    | 0.6473 | 0.6690 | 0.9485   |
  | 0.1412        | 3.0   | 16683 | 0.1373          | 0.6845    | 0.6705 | 0.6774 | 0.9490   |
  | 0.1338        | 4.0   | 22244 | 0.1343          | 0.6988    | 0.6640 | 0.6810 | 0.9505   |
  | 0.1311        | 5.0   | 27805 | 0.1342          | 0.6971    | 0.6751 | 0.6859 | 0.9510   |
  | 0.1289        | 6.0   | 33366 | 0.1324          | 0.7081    | 0.6653 | 0.6860 | 0.9517   |
  | 0.1258        | 7.0   | 38927 | 0.1309          | 0.7053    | 0.6731 | 0.6888 | 0.9521   |
  | 0.1223        | 8.0   | 44488 | 0.1325          | 0.7001    | 0.6818 | 0.6908 | 0.9519   |
  | 0.1213        | 9.0   | 50049 | 0.1316          | 0.7020    | 0.6813 | 0.6915 | 0.9522   |
  | 0.1197        | 10.0  | 55610 | 0.1314          | 0.7013    | 0.6837 | 0.6924 | 0.9522   |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.11.0+cu113
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  