readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: ak-pretrain-cls-model
    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. -->
  
  # ak-pretrain-cls-model
  
  This model is a fine-tuned version of [hfl/chinese-roberta-wwm-ext](https://huggingface.co/hfl/chinese-roberta-wwm-ext) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.0849
  - Accuracy: 0.7876
  
  ## 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: 5e-05
  - train_batch_size: 32
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 30.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step   | Accuracy | Validation Loss |
  |:-------------:|:-----:|:------:|:--------:|:---------------:|
  | 1.3351        | 1.0   | 30469  | 0.7496   | 1.2050          |
  | 1.1401        | 2.0   | 60938  | 0.7554   | 1.1823          |
  | 1.0411        | 3.0   | 91407  | 0.7609   | 1.1614          |
  | 0.9643        | 4.0   | 121876 | 0.7651   | 1.1544          |
  | 0.8659        | 5.0   | 152345 | 0.7704   | 1.1291          |
  | 0.8099        | 6.0   | 182814 | 0.7746   | 1.1237          |
  | 0.7301        | 7.0   | 213283 | 0.7777   | 1.1136          |
  | 0.6964        | 8.0   | 243752 | 0.7826   | 1.1106          |
  | 0.6616        | 9.0   | 274221 | 0.7853   | 1.0918          |
  | 0.6349        | 10.0  | 304690 | 0.7872   | 1.0876          |
  | 0.6349        | 20.0  | 304700 | 1.0813   | 0.7874          |
  | 0.6427        | 21.0  | 319935 | 1.1011   | 0.7841          |
  | 0.6096        | 22.0  | 335170 | 1.1013   | 0.7848          |
  | 0.6029        | 23.0  | 350405 | 1.1027   | 0.7859          |
  | 0.5762        | 24.0  | 365640 | 1.0980   | 0.7872          |
  | 0.5684        | 25.0  | 380875 | 1.1043   | 0.7873          |
  | 0.5385        | 26.0  | 396110 | 1.0954   | 0.7884          |
  | 0.5114        | 27.0  | 411345 | 1.0975   | 0.7897          |
  | 0.499         | 28.0  | 426580 | 1.1016   | 0.7897          |
  | 0.526         | 29.0  | 441815 | 1.0954   | 0.7909          |
  | 0.5002        | 30.0  | 457050 | 1.0963   | 0.7913          |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0
  - Datasets 2.3.1
  - Tokenizers 0.11.6
  