readme: ---
  tags:
  - generated_from_trainer
  datasets:
  - squad_modified_for_t5_qg
  model-index:
  - name: t5-end2end-questions-generation
    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. -->
  
  # t5-end2end-questions-generation
  
  This model is a fine-tuned version of [digit82/kolang-t5-base](https://huggingface.co/digit82/kolang-t5-base) on the korquad_modified_for_t5_qg dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.1449
  
  ## Model description
  
  More information needed
  
  ## Training and evaluation data
  
  KorQuAD V1.0
  
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 0.0001
  - train_batch_size: 4
  - eval_batch_size: 4
  - seed: 42
  - gradient_accumulation_steps: 16
  - total_train_batch_size: 64
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 7
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss |
  |:-------------:|:-----:|:----:|:---------------:|
  | 3.6685        | 0.66  | 100  | 2.4355          |
  | 2.3957        | 1.32  | 200  | 2.2428          |
  | 2.1795        | 1.98  | 300  | 2.1664          |
  | 1.9408        | 2.65  | 400  | 2.1467          |
  | 1.8333        | 3.31  | 500  | 2.1470          |
  | 1.7319        | 3.97  | 600  | 2.1194          |
  | 1.6095        | 4.63  | 700  | 2.1348          |
  | 1.5662        | 5.3   | 800  | 2.1433          |
  | 1.5038        | 5.96  | 900  | 2.1319          |
  | 1.45          | 6.62  | 1000 | 2.1449          |
  
  
  ### Framework versions
  
  - Transformers 4.21.2
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  