readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: bert-base-finetuned-wellness
    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. -->
  
  # bert-base-finetuned-wellness
  
  This model is a fine-tuned version of [klue/bert-base](https://huggingface.co/klue/bert-base) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.3297
  
  ## 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: 4e-05
  - train_batch_size: 64
  - eval_batch_size: 64
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 10
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss |
  |:-------------:|:-----:|:----:|:---------------:|
  | 2.4206        | 1.0   | 32   | 1.6348          |
  | 1.6784        | 2.0   | 64   | 1.5117          |
  | 1.5398        | 3.0   | 96   | 1.4957          |
  | 1.4563        | 4.0   | 128  | 1.4255          |
  | 1.4111        | 5.0   | 160  | 1.4090          |
  | 1.3917        | 6.0   | 192  | 1.3566          |
  | 1.3816        | 7.0   | 224  | 1.3316          |
  | 1.3514        | 8.0   | 256  | 1.3519          |
  | 1.3412        | 9.0   | 288  | 1.2739          |
  | 1.3334        | 10.0  | 320  | 1.3000          |
  
  
  ### Framework versions
  
  - Transformers 4.22.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  