readme: ---
  license: apache-2.0
  tags:
  - text-classification
  - generated_from_trainer
  datasets:
  - paws-x
  metrics:
  - accuracy
  model-index:
  - name: paws_x_m_bert_only_ko
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: paws-x
        type: paws-x
        config: ko
        split: train
        args: ko
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.8215
  ---
  
  <!-- 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. -->
  
  # paws_x_m_bert_only_ko
  
  This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the paws-x dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.7649
  - Accuracy: 0.8215
  
  ## 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: 2e-05
  - train_batch_size: 128
  - eval_batch_size: 128
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 100
  - num_epochs: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.5446        | 1.0   | 386  | 0.4837          | 0.768    |
  | 0.3443        | 2.0   | 772  | 0.4530          | 0.8125   |
  | 0.258         | 3.0   | 1158 | 0.4496          | 0.8145   |
  | 0.2023        | 4.0   | 1544 | 0.4944          | 0.81     |
  | 0.1581        | 5.0   | 1930 | 0.5040          | 0.814    |
  | 0.1263        | 6.0   | 2316 | 0.5937          | 0.8145   |
  | 0.1041        | 7.0   | 2702 | 0.6578          | 0.8115   |
  | 0.0828        | 8.0   | 3088 | 0.6841          | 0.8215   |
  | 0.0697        | 9.0   | 3474 | 0.7239          | 0.82     |
  | 0.0596        | 10.0  | 3860 | 0.7649          | 0.8215   |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.13.0
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  