readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: tiny_focal_v3
    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_v3
  
  This model was trained from scratch on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0023
  - Precision: 0.6975
  - Recall: 0.6822
  - F1: 0.6898
  - Accuracy: 0.9515
  
  ## 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | 0.004         | 1.0   | 5561  | 0.0032          | 0.6900    | 0.6102 | 0.6477 | 0.9454   |
  | 0.0032        | 2.0   | 11122 | 0.0028          | 0.6901    | 0.6406 | 0.6644 | 0.9477   |
  | 0.0029        | 3.0   | 16683 | 0.0026          | 0.6956    | 0.6509 | 0.6725 | 0.9490   |
  | 0.0025        | 4.0   | 22244 | 0.0025          | 0.6838    | 0.6764 | 0.6801 | 0.9493   |
  | 0.0024        | 5.0   | 27805 | 0.0024          | 0.6954    | 0.6715 | 0.6832 | 0.9504   |
  | 0.0023        | 6.0   | 33366 | 0.0024          | 0.7125    | 0.6524 | 0.6811 | 0.9512   |
  | 0.0021        | 7.0   | 38927 | 0.0023          | 0.6999    | 0.6748 | 0.6872 | 0.9514   |
  | 0.0019        | 8.0   | 44488 | 0.0024          | 0.6962    | 0.6820 | 0.6890 | 0.9513   |
  | 0.0019        | 9.0   | 50049 | 0.0023          | 0.7005    | 0.6775 | 0.6888 | 0.9516   |
  | 0.0018        | 10.0  | 55610 | 0.0023          | 0.6975    | 0.6822 | 0.6898 | 0.9515   |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.11.0+cu113
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  