readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: hyunwoongko-kobart-eb-finetuned-papers-meetings
    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. -->
  
  # hyunwoongko-kobart-eb-finetuned-papers-meetings
  
  This model is a fine-tuned version of [hyunwoongko/kobart](https://huggingface.co/hyunwoongko/kobart) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3136
  - Rouge1: 18.3166
  - Rouge2: 8.0509
  - Rougel: 18.3332
  - Rougelsum: 18.3146
  - Gen Len: 19.9143
  
  ## 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: 4
  - eval_batch_size: 4
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 5
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
  | 0.2118        | 1.0   | 7739  | 0.2951          | 18.0837 | 7.9585 | 18.0787 | 18.0784   | 19.896  |
  | 0.1598        | 2.0   | 15478 | 0.2812          | 18.529  | 7.9891 | 18.5421 | 18.5271   | 19.8977 |
  | 0.1289        | 3.0   | 23217 | 0.2807          | 18.0638 | 7.8086 | 18.0787 | 18.0583   | 19.9129 |
  | 0.0873        | 4.0   | 30956 | 0.2923          | 18.3483 | 8.0233 | 18.3716 | 18.3696   | 19.914  |
  | 0.0844        | 5.0   | 38695 | 0.3136          | 18.3166 | 8.0509 | 18.3332 | 18.3146   | 19.9143 |
  
  
  ### Framework versions
  
  - Transformers 4.19.4
  - Pytorch 1.11.0+cu113
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  