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cleaned_ds

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

  • Loss: 4.3404
  • Rouge1: 0.2705
  • Rouge2: 0.0363
  • Rougel: 0.1609
  • Rougelsum: 0.1609
  • Generated Length: 113.0

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: 16
  • eval_batch_size: 16
  • 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 Generated Length
No log 1.0 1 5.0242 0.2692 0.0362 0.1676 0.1676 83.5
No log 2.0 2 4.5239 0.2629 0.0251 0.1431 0.1431 96.5
No log 3.0 3 4.3404 0.2705 0.0363 0.1609 0.1609 113.0

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.1+cu121
  • Datasets 3.0.0
  • Tokenizers 0.19.1
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