README.md

metadata

license: apache-2.0
tags:
  - summarization
datasets:
  - multi_news
metrics:
  - rouge
model-index:
  - name: distilbart-cnn-12-6-ftn-multi_news
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: summarization
        dataset:
          name: multi_news
          type: multi_news
          args: default
        metrics:
          - name: Rouge1
            type: rouge
            value: 39.9832

distilbart-cnn-12-6-ftn-multi_news

This model is a fine-tuned version of sshleifer/distilbart-cnn-12-6 on the multi_news dataset. It achieves the following results on the evaluation set:

• Loss: 4.0202
• Rouge1: 39.9832
• Rouge2: 13.0653
• Rougel: 22.1761
• Rougelsum: 34.5466
• Gen Len: 132.41

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: 4
• eval_batch_size: 4
• 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: 1
• mixed_precision_training: Native AMP
• label_smoothing_factor: 0.1

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
4.1427	0.89	400	4.0202	39.9832	13.0653	22.1761	34.5466	132.41

Framework versions

• Transformers 4.18.0
• Pytorch 1.11.0
• Datasets 2.1.0
• Tokenizers 0.12.1