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metadata
license: mit
base_model: facebook/bart-large-xsum
tags:
  - generated_from_trainer
datasets:
  - samsum
metrics:
  - rouge
model-index:
  - name: summarization_fine_tuning
    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: 53.215

summarization_fine_tuning

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: 1.5474
  • Rouge1: 53.215
  • Rouge2: 28.4755
  • Rougel: 43.9337
  • Rougelsum: 48.5873
  • Gen Len: 27.2592

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: 1
  • eval_batch_size: 1
  • seed: 42
  • 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 Rougelsum Gen Len
1.3867 1.0 14732 1.6283 52.82 28.3657 43.6768 48.5632 27.1137
0.9705 2.0 29464 1.5474 53.215 28.4755 43.9337 48.5873 27.2592
0.5877 3.0 44196 1.7343 53.8648 28.8011 44.1837 49.2032 29.2225

Framework versions

  • Transformers 4.35.0
  • Pytorch 2.1.0+cu118
  • Datasets 2.14.6
  • Tokenizers 0.14.1