readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: tiny_focal_alpah
    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_alpah
  
  This model was trained from scratch on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0492
  - Precision: 0.6951
  - Recall: 0.6796
  - F1: 0.6873
  - Accuracy: 0.9512
  
  ## 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | 0.0588        | 1.0   | 5561  | 0.0548          | 0.6801    | 0.6235 | 0.6506 | 0.9453   |
  | 0.054         | 2.0   | 11122 | 0.0521          | 0.6850    | 0.6478 | 0.6659 | 0.9476   |
  | 0.0525        | 3.0   | 16683 | 0.0509          | 0.6834    | 0.6676 | 0.6754 | 0.9486   |
  | 0.0492        | 4.0   | 22244 | 0.0503          | 0.6829    | 0.6754 | 0.6791 | 0.9491   |
  | 0.0482        | 5.0   | 27805 | 0.0500          | 0.6917    | 0.6727 | 0.6820 | 0.9501   |
  | 0.0471        | 6.0   | 33366 | 0.0491          | 0.7085    | 0.6546 | 0.6805 | 0.9510   |
  | 0.0459        | 7.0   | 38927 | 0.0486          | 0.6964    | 0.6746 | 0.6853 | 0.9510   |
  | 0.0448        | 8.0   | 44488 | 0.0495          | 0.6922    | 0.6813 | 0.6867 | 0.9509   |
  | 0.044         | 9.0   | 50049 | 0.0491          | 0.6961    | 0.6755 | 0.6857 | 0.9511   |
  | 0.0433        | 10.0  | 55610 | 0.0492          | 0.6951    | 0.6796 | 0.6873 | 0.9512   |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.11.0+cu113
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  