readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: tiny_focal_ckpt
    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_ckpt
  
  This model was trained from scratch on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0561
  - Precision: 0.6529
  - Recall: 0.6366
  - F1: 0.6446
  - Accuracy: 0.9516
  
  ## 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | 0.058         | 1.0   | 5561  | 0.0583          | 0.6327    | 0.5945 | 0.6130 | 0.9484   |
  | 0.0566        | 2.0   | 11122 | 0.0570          | 0.6401    | 0.5985 | 0.6186 | 0.9492   |
  | 0.0564        | 3.0   | 16683 | 0.0567          | 0.6364    | 0.6241 | 0.6302 | 0.9496   |
  | 0.053         | 4.0   | 22244 | 0.0561          | 0.6416    | 0.6312 | 0.6364 | 0.9503   |
  | 0.052         | 5.0   | 27805 | 0.0558          | 0.6501    | 0.6239 | 0.6367 | 0.9510   |
  | 0.0507        | 6.0   | 33366 | 0.0555          | 0.6555    | 0.6208 | 0.6377 | 0.9514   |
  | 0.0497        | 7.0   | 38927 | 0.0552          | 0.6559    | 0.6256 | 0.6404 | 0.9515   |
  | 0.0485        | 8.0   | 44488 | 0.0561          | 0.6485    | 0.6397 | 0.6440 | 0.9513   |
  | 0.0481        | 9.0   | 50049 | 0.0558          | 0.6531    | 0.6344 | 0.6436 | 0.9515   |
  | 0.0469        | 10.0  | 55610 | 0.0561          | 0.6529    | 0.6366 | 0.6446 | 0.9516   |
  
  
  ### Framework versions
  
  - Transformers 4.20.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  