readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: ks-chungcheong-nmt-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. -->
  
  # ks-chungcheong-nmt-v2
  
  This model is a fine-tuned version of [smile3634/ks-chungcheong-nmt-v1](https://huggingface.co/smile3634/ks-chungcheong-nmt-v1) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2771
  
  ## 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
  - lr_scheduler_warmup_ratio: 0.1
  - num_epochs: 3
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss |
  |:-------------:|:-----:|:----:|:---------------:|
  | 1.8849        | 0.16  | 500  | 1.8573          |
  | 1.7337        | 0.32  | 1000 | 1.6565          |
  | 1.5085        | 0.49  | 1500 | 1.2008          |
  | 1.1849        | 0.65  | 2000 | 0.8869          |
  | 0.9535        | 0.81  | 2500 | 0.6806          |
  | 0.8032        | 0.97  | 3000 | 0.5774          |
  | 0.5472        | 1.13  | 3500 | 0.5094          |
  | 0.4656        | 1.29  | 4000 | 0.4570          |
  | 0.4269        | 1.46  | 4500 | 0.4286          |
  | 0.3916        | 1.62  | 5000 | 0.4011          |
  | 0.3564        | 1.78  | 5500 | 0.3676          |
  | 0.3259        | 1.94  | 6000 | 0.3422          |
  | 0.2513        | 2.1   | 6500 | 0.3312          |
  | 0.2101        | 2.26  | 7000 | 0.3111          |
  | 0.1991        | 2.43  | 7500 | 0.2985          |
  | 0.1893        | 2.59  | 8000 | 0.2960          |
  | 0.1774        | 2.75  | 8500 | 0.2823          |
  | 0.1687        | 2.91  | 9000 | 0.2771          |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.13.1+cu116
  - Tokenizers 0.13.2
  