readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: korean_sentiment_analysis_dataset3
    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
  
  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: 1.7614
  - Micro f1 score: 74.9024
  - Auprc: 75.3897
  - Accuracy: 0.7490
  
  ## 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: 10.0
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Micro f1 score | Auprc   | Accuracy |
  |:-------------:|:-----:|:-----:|:---------------:|:--------------:|:-------:|:--------:|
  | 0.8814        | 1.0   | 5080  | 0.7160          | 74.0798        | 78.1155 | 0.7408   |
  | 0.5153        | 2.0   | 10160 | 0.6638          | 76.1573        | 80.2492 | 0.7616   |
  | 0.6463        | 3.0   | 15240 | 0.6815          | 76.2897        | 80.6829 | 0.7629   |
  | 0.4697        | 4.0   | 20320 | 0.7243          | 76.0666        | 80.1682 | 0.7607   |
  | 0.2043        | 5.0   | 25400 | 0.9200          | 75.4810        | 79.2632 | 0.7548   |
  | 0.2452        | 6.0   | 30480 | 1.0875          | 74.9582        | 78.5166 | 0.7496   |
  | 0.1481        | 7.0   | 35560 | 1.3625          | 74.7769        | 76.5613 | 0.7478   |
  | 0.1974        | 8.0   | 40640 | 1.5593          | 75.0906        | 76.3100 | 0.7509   |
  | 0.1658        | 9.0   | 45720 | 1.6836          | 74.9651        | 75.6953 | 0.7497   |
  | 0.1392        | 10.0  | 50800 | 1.7614          | 74.9024        | 75.3897 | 0.7490   |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.6.0
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  