readme: ---
  license: cc-by-4.0
  tags:
  - generated_from_trainer
  datasets:
  - aihub_paper_summarization
  metrics:
  - rouge
  model-index:
  - name: pko-t5-small-finetuned-paper-4564652
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
      dataset:
        name: aihub_paper_summarization
        type: aihub_paper_summarization
        config: default
        split: train
        args: default
      metrics:
      - name: Rouge1
        type: rouge
        value: 4.874
  ---
  
  <!-- 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. -->
  
  # pko-t5-small-finetuned-paper-4564652
  
  This model is a fine-tuned version of [paust/pko-t5-small](https://huggingface.co/paust/pko-t5-small) on the aihub_paper_summarization dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4922
  - Rouge1: 4.874
  - Rouge2: 1.0497
  - Rougel: 4.8599
  - Rougelsum: 4.854
  - Gen Len: 18.9953
  
  ## 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: 16
  - eval_batch_size: 16
  - seed: 42
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 64
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 3
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.1
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  