README.md

metadata

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

bart-qg-finetuned-hotpotqa

This model is a fine-tuned version of 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