readme: ---
  tags:
  - generated_from_trainer
  datasets:
  - hotpot_qa
  metrics:
  - rouge
  model-index:
  - name: bart-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: 46.2814
  ---
  
  <!-- 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. -->
  
  # bart-qg-finetuned-hotpotqa
  
  This model is a fine-tuned version of [p208p2002/bart-squad-qg-hl](https://huggingface.co/p208p2002/bart-squad-qg-hl) on the hotpot_qa dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.0817
  - Rouge1: 46.2814
  - Rouge2: 30.4609
  - Rougel: 42.3385
  - Rougelsum: 42.3741
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
  | 1.3949        | 1.0   | 2500 | 1.1812          | 44.0967 | 28.022  | 40.0397 | 40.0403   |
  | 1.0883        | 2.0   | 5000 | 1.1141          | 44.9629 | 29.1863 | 41.1078 | 41.1684   |
  | 0.8677        | 3.0   | 7500 | 1.0817          | 46.2814 | 30.4609 | 42.3385 | 42.3741   |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  