README.md

metadata

license: mit
tags:
  - generated_from_trainer
datasets:
  - multi_news
metrics:
  - rouge
model-index:
  - name: bart_large_summarise_v3
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: multi_news
          type: multi_news
          config: default
          split: train
          args: default
        metrics:
          - name: Rouge1
            type: rouge
            value: 0.3914

bart_large_summarise_v3

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

• Loss: 4.1359
• Rouge1: 0.3914
• Rouge2: 0.1399
• Rougel: 0.2039
• Rougelsum: 0.3504
• Gen Len: 141.64

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: 5e-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
• lr_scheduler_warmup_steps: 500
• num_epochs: 10
• label_smoothing_factor: 0.1

Training results

Framework versions

• Transformers 4.23.1
• Pytorch 1.12.1+cu113
• Datasets 2.6.1
• Tokenizers 0.13.1