readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: kobert-finetuned-klue-v2
    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. -->
  
  # kobert-finetuned-klue-v2
  
  This model is a fine-tuned version of [monologg/kobert](https://huggingface.co/monologg/kobert) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 5.2678
  
  ## 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: 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: 20
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss |
  |:-------------:|:-----:|:----:|:---------------:|
  | 5.6289        | 0.54  | 500  | 5.3024          |
  | 5.3083        | 1.08  | 1000 | 5.3707          |
  | 5.3518        | 1.62  | 1500 | 5.3039          |
  | 5.2912        | 2.16  | 2000 | 5.2800          |
  | 5.2282        | 2.7   | 2500 | 5.2301          |
  | 5.1498        | 3.24  | 3000 | 5.2435          |
  | 5.079         | 3.78  | 3500 | 5.1997          |
  | 4.8886        | 4.32  | 4000 | 5.1350          |
  | 4.8166        | 4.86  | 4500 | 5.1441          |
  | 4.5615        | 5.4   | 5000 | 5.1485          |
  | 4.4183        | 5.94  | 5500 | 5.0775          |
  | 4.1282        | 6.48  | 6000 | 5.0402          |
  | 4.1214        | 7.02  | 6500 | 5.1331          |
  | 3.7792        | 7.56  | 7000 | 5.1314          |
  | 3.7455        | 8.1   | 7500 | 5.1936          |
  | 3.5369        | 8.64  | 8000 | 5.1931          |
  | 3.4832        | 9.18  | 8500 | 5.2678          |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.10.0+cu111
  - Datasets 2.0.0
  - Tokenizers 0.11.6
  