readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: KoT5-test-add-data-from5ep
    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. -->
  
  # KoT5-test-add-data-from5ep
  
  This model is a fine-tuned version of [hyorea1/KoT5-test](https://huggingface.co/hyorea1/KoT5-test) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.1737
  - Rouge1: 11.8294
  - Rouge2: 3.2314
  - Rougel: 11.7891
  - Rougelsum: 11.8237
  - Gen Len: 35.2824
  
  ## 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: 100
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 8
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: cosine
  - lr_scheduler_warmup_ratio: 0.1
  - num_epochs: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
  | 1.9029        | 0.16  | 400  | 1.1695          | 12.8243 | 3.2659 | 12.7542 | 12.8276   | 35.5743 |
  | 1.7971        | 0.32  | 800  | 1.1646          | 12.259  | 3.0668 | 12.1254 | 12.1927   | 35.2353 |
  | 1.4396        | 0.48  | 1200 | 1.1681          | 12.1151 | 3.1908 | 11.9507 | 12.0305   | 35.3125 |
  | 1.0945        | 0.64  | 1600 | 1.1703          | 12.0576 | 2.9688 | 11.9292 | 11.9792   | 35.0926 |
  | 1.1924        | 0.8   | 2000 | 1.1667          | 11.7835 | 2.9605 | 11.6755 | 11.7318   | 35.3596 |
  | 1.3711        | 0.97  | 2400 | 1.1668          | 11.9873 | 3.1107 | 11.9369 | 12.0207   | 34.5309 |
  | 1.6031        | 1.13  | 2800 | 1.1673          | 11.6049 | 3.1121 | 11.5527 | 11.5976   | 34.6551 |
  | 1.5254        | 1.29  | 3200 | 1.1693          | 11.6803 | 2.8527 | 11.6116 | 11.6829   | 34.8066 |
  | 1.641         | 1.45  | 3600 | 1.1737          | 11.8294 | 3.2314 | 11.7891 | 11.8237   | 35.2824 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  