readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: bert-base-low_resource-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-low_resource-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: 1.0853
  
  ## 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: 8
  - eval_batch_size: 8
  - 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 |
  |:-------------:|:-----:|:----:|:---------------:|
  | 1.8441        | 1.0   | 285  | 1.5346          |
  | 1.5211        | 2.0   | 570  | 1.4483          |
  | 1.3907        | 3.0   | 855  | 1.3713          |
  | 1.3227        | 4.0   | 1140 | 1.2589          |
  | 1.2745        | 5.0   | 1425 | 1.2187          |
  | 1.2411        | 6.0   | 1710 | 1.2395          |
  | 1.1769        | 7.0   | 1995 | 1.1925          |
  | 1.1377        | 8.0   | 2280 | 1.1454          |
  | 1.1443        | 9.0   | 2565 | 1.1225          |
  | 1.11          | 10.0  | 2850 | 1.0843          |
  
  
  ### Framework versions
  
  - Transformers 4.23.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.5.2
  - Tokenizers 0.13.1
  