readme: ---
  tags:
  - generated_from_trainer
  datasets:
  - hotpot_qa
  metrics:
  - rouge
  model-index:
  - name: t5-qg-finetuned-hotpotqa
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
      dataset:
        name: hotpot_qa
        type: hotpot_qa
        config: distractor
        split: train
        args: distractor
      metrics:
      - name: Rouge1
        type: rouge
        value: 44.4906
  ---
  
  <!-- 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-qg-finetuned-hotpotqa
  
  This model is a fine-tuned version of [p208p2002/t5-squad-qg-hl](https://huggingface.co/p208p2002/t5-squad-qg-hl) on the hotpot_qa dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.2046
  - Rouge1: 44.4906
  - Rouge2: 26.3193
  - Rougel: 39.9929
  - Rougelsum: 39.9879
  
  ## 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: 5.6e-05
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 3
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
  | 1.379         | 1.0   | 1875 | 1.2998          | 43.0766 | 24.8898 | 38.4029 | 38.4874   |
  | 1.2011        | 2.0   | 3750 | 1.2225          | 44.7538 | 26.1406 | 39.9817 | 39.9714   |
  | 1.1027        | 3.0   | 5625 | 1.2046          | 44.4906 | 26.3193 | 39.9929 | 39.9879   |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  