readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: tiny_focal_v2_label
    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_focal_v2_label
  
  This model was trained from scratch on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0558
  - Precision: 0.6979
  - Recall: 0.6747
  - F1: 0.6861
  - Accuracy: 0.9513
  
  ## 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | 0.0661        | 1.0   | 5561  | 0.0616          | 0.6850    | 0.6202 | 0.6510 | 0.9457   |
  | 0.0613        | 2.0   | 11122 | 0.0587          | 0.6952    | 0.6351 | 0.6638 | 0.9480   |
  | 0.0596        | 3.0   | 16683 | 0.0577          | 0.6814    | 0.6679 | 0.6746 | 0.9485   |
  | 0.0555        | 4.0   | 22244 | 0.0567          | 0.6855    | 0.6693 | 0.6773 | 0.9492   |
  | 0.0543        | 5.0   | 27805 | 0.0560          | 0.6966    | 0.6657 | 0.6808 | 0.9503   |
  | 0.0529        | 6.0   | 33366 | 0.0558          | 0.7060    | 0.6587 | 0.6816 | 0.9510   |
  | 0.052         | 7.0   | 38927 | 0.0552          | 0.7009    | 0.6662 | 0.6831 | 0.9510   |
  | 0.0506        | 8.0   | 44488 | 0.0559          | 0.6921    | 0.6783 | 0.6852 | 0.9508   |
  | 0.0501        | 9.0   | 50049 | 0.0556          | 0.6991    | 0.6716 | 0.6851 | 0.9512   |
  | 0.0491        | 10.0  | 55610 | 0.0558          | 0.6979    | 0.6747 | 0.6861 | 0.9513   |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.11.0+cu113
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  