模型:

Qiliang/bart-large-cnn-samsum-ElectrifAi_v14

中文

bart-large-cnn-samsum-ElectrifAi_v14

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

  • Loss: 2.1649
  • Rouge1: 52.2959
  • Rouge2: 19.0107
  • Rougel: 29.5199
  • Rougelsum: 47.2462
  • Gen Len: 115.75

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: 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: 3
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
No log 1.0 9 2.3430 44.7631 15.9376 23.8711 40.091 142.0
No log 2.0 18 2.1774 47.2025 17.7636 27.235 40.251 102.5
No log 3.0 27 2.1649 52.2959 19.0107 29.5199 47.2462 115.75

Framework versions

  • Transformers 4.28.1
  • Pytorch 2.0.0+cu118
  • Datasets 2.11.0
  • Tokenizers 0.13.3