readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: korean_sentiment_analysis_dataset3_best
    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. -->
  
  # korean_sentiment_analysis_dataset3_best
  
  This model is a fine-tuned version of [klue/roberta-large](https://huggingface.co/klue/roberta-large) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.6989
  - Micro f1 score: 76.6383
  - Auprc: 81.5157
  - Accuracy: 0.7664
  
  ## 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: 1e-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: 3.0
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Micro f1 score | Auprc   | Accuracy |
  |:-------------:|:-----:|:-----:|:---------------:|:--------------:|:-------:|:--------:|
  | 0.7997        | 1.0   | 5080  | 0.6822          | 74.7769        | 79.4361 | 0.7478   |
  | 0.4544        | 2.0   | 10160 | 0.6608          | 76.7429        | 81.1265 | 0.7674   |
  | 0.5702        | 3.0   | 15240 | 0.6989          | 76.6383        | 81.5157 | 0.7664   |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.6.0
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  