README.md

metadata

license: mit
tags:
  - generated_from_trainer
datasets:
  - scientific_papers
metrics:
  - rouge
model-index:
  - name: bart-large-cnn-pubmed1o3-pubmed2o3
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: scientific_papers
          type: scientific_papers
          args: pubmed
        metrics:
          - name: Rouge1
            type: rouge
            value: 37.4586

bart-large-cnn-pubmed1o3-pubmed2o3

This model is a fine-tuned version of theojolliffe/bart-large-cnn-pubmed1o3 on the scientific_papers dataset. It achieves the following results on the evaluation set:

• Loss: 1.8817
• Rouge1: 37.4586
• Rouge2: 15.5572
• Rougel: 23.0686
• Rougelsum: 34.1522
• Gen Len: 138.379

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: 2
• eval_batch_size: 2
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 1
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
1.9586	1.0	19988	1.8817	37.4586	15.5572	23.0686	34.1522	138.379

Framework versions

• Transformers 4.19.2
• Pytorch 1.11.0+cu113
• Datasets 2.2.2
• Tokenizers 0.12.1