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text_summarization-cnn

This model is a fine-tuned version of Falconsai/text_summarization on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.6120
  • Rouge1: 0.2483
  • Rouge2: 0.1203
  • Rougel: 0.2055
  • Rougelsum: 0.2344

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: 5.6e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 2

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum
1.8062 1.0 32691 1.6262 0.248 0.1198 0.2053 0.234
1.7563 2.0 65382 1.6120 0.2483 0.1203 0.2055 0.2344

Framework versions

  • Transformers 4.39.3
  • Pytorch 2.2.2+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2
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