distilbart-summarization-top

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: 1.0451

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
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 8
  • optimizer: Use OptimizerNames.ADAFACTOR and the args are: No additional optimizer arguments
  • lr_scheduler_type: linear
  • num_epochs: 2.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
1.1609 0.3765 2000 1.0716
1.155 0.7529 4000 1.0546
1.0795 1.1293 6000 1.0495
1.0429 1.5058 8000 1.0466
1.0584 1.8823 10000 1.0451

Framework versions

  • Transformers 4.48.2
  • Pytorch 2.5.1+cu124
  • Datasets 3.2.0
  • Tokenizers 0.21.0
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