README.md

metadata

license: mit
tags:
  - generated_from_trainer
datasets:
  - samsum
metrics:
  - rouge
model-index:
  - name: bart-large-cnn-samsum
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: samsum
          type: samsum
          config: samsum
          split: test
          args: samsum
        metrics:
          - name: Rouge1
            type: rouge
            value: 40.1703

bart-large-cnn-samsum

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

• Loss: 1.4821
• Rouge1: 40.1703
• Rouge2: 20.2613
• Rougel: 30.8068
• Rougelsum: 37.4968
• Gen Len: 60.0366

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: 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

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
1.1917	1.0	7366	1.4821	40.1703	20.2613	30.8068	37.4968	60.0366

Framework versions

• Transformers 4.30.2
• Pytorch 1.12.1
• Datasets 2.13.0
• Tokenizers 0.11.0