readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: KoT5-test-add-data-from5ep-continue
    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-continue
  
  This model is a fine-tuned version of [hyorea1/KoT5-test-add-data-from5ep-continue](https://huggingface.co/hyorea1/KoT5-test-add-data-from5ep-continue) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.1881
  - Rouge1: 11.7784
  - Rouge2: 2.959
  - Rougel: 11.6648
  - Rougelsum: 11.6892
  - Gen Len: 34.7301
  
  ## 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: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Gen Len | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum |
  |:-------------:|:-----:|:-----:|:-------:|:---------------:|:-------:|:------:|:-------:|:---------:|
  | 1.4317        | 0.32  | 800   | 34.7618 | 1.2414          | 11.8765 | 3.2439 | 11.7982 | 11.8203   |
  | 0.9488        | 0.64  | 1600  | 35.1324 | 1.2255          | 11.5076 | 3.0739 | 11.394  | 11.4492   |
  | 1.1868        | 0.97  | 2400  | 34.2368 | 1.1983          | 10.7675 | 2.8679 | 10.7567 | 10.7806   |
  | 1.3349        | 1.29  | 3200  | 34.3772 | 1.2170          | 11.0853 | 2.8116 | 10.9947 | 11.0642   |
  | 1.3918        | 1.61  | 4000  | 34.7368 | 1.1845          | 11.6434 | 2.9694 | 11.5189 | 11.5525   |
  | 1.6205        | 1.93  | 4800  | 33.9897 | 1.1801          | 11.1446 | 2.9624 | 11.0259 | 11.0535   |
  | 1.1958        | 2.25  | 5600  | 34.6926 | 1.1845          | 11.3408 | 2.9759 | 11.2451 | 11.2685   |
  | 1.2391        | 2.58  | 6400  | 34.8382 | 1.1879          | 11.227  | 2.832  | 11.0999 | 11.12     |
  | 1.458         | 2.9   | 7200  | 34.8904 | 1.1869          | 11.4615 | 2.832  | 11.3029 | 11.3413   |
  | 1.0598        | 3.22  | 8000  | 1.1877  | 11.2705         | 2.8787  | 11.1582| 11.2173 | 34.8993   |
  | 1.3546        | 3.54  | 8800  | 1.1832  | 11.9647         | 2.9161  | 11.848 | 11.8769 | 34.5897   |
  | 1.5696        | 3.86  | 9600  | 1.1859  | 11.352          | 2.8466  | 11.2177| 11.2336 | 34.6441   |
  | 1.3378        | 4.19  | 10400 | 1.1873  | 11.9282         | 2.959   | 11.8205| 11.8427 | 34.7125   |
  | 1.063         | 4.51  | 11200 | 1.1877  | 11.8063         | 2.9284  | 11.6855| 11.7112 | 34.6426   |
  | 1.184         | 4.83  | 12000 | 1.1881  | 11.7784         | 2.959   | 11.6648| 11.6892 | 34.7301   |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu116
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  