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bart-large-xsum-samsum
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metadata
license: mit
base_model: facebook/bart-large-xsum
tags:
  - generated_from_trainer
datasets:
  - samsum
metrics:
  - rouge
model-index:
  - name: bart-large-xsum-samsum
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: samsum
          type: samsum
          config: samsum
          split: validation
          args: samsum
        metrics:
          - name: Rouge1
            type: rouge
            value: 54.3742

bart-large-xsum-samsum

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

  • Loss: 0.4330
  • Rouge1: 54.3742
  • Rouge2: 29.1289
  • Rougel: 44.1238
  • Gen Len: 29.8973

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: 1e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Gen Len
No log 0.9989 460 0.4542 53.4662 28.4545 43.6636 29.6174
0.7083 2.0 921 0.4415 53.6674 28.8109 44.0343 29.2665
0.3748 2.9967 1380 0.4330 54.3742 29.1289 44.1238 29.8973

Framework versions

  • Transformers 4.42.4
  • Pytorch 2.3.0+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1