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pep_summarization

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

  • Loss: 0.1242
  • Rouge1: 75.3806
  • Rouge2: 74.6735
  • Rougel: 75.5866
  • Rougelsum: 75.5446
  • Gen Len: 85.3188

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: 4
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 5.0

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
No log 1.0 69 0.0957 72.6601 71.6824 72.6858 72.4668 95.4493
No log 2.0 138 0.1345 75.0063 74.0782 75.0597 74.8943 92.0145
No log 3.0 207 0.1412 75.3012 74.5492 75.4246 75.324 85.4638
No log 4.0 276 0.1089 74.8426 74.0317 74.8939 74.8128 85.0435
No log 5.0 345 0.1242 75.3806 74.6735 75.5866 75.5446 85.3188

Framework versions

  • Transformers 4.38.0.dev0
  • Pytorch 2.1.2+cu121
  • Datasets 2.16.1
  • Tokenizers 0.15.0
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Evaluation results