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sumarize_model_pegasus_v2_original

This model is a fine-tuned version of google/pegasus-xsum on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 1.0660
  • Rouge1: 0.6881
  • Rouge2: 0.5187
  • Rougel: 0.6489
  • Rougelsum: 0.6488
  • Gen Len: 44.9812

Model description

This model has been trained with a large dataset with data in Spanish to summarize financial texts that are difficult to understand. For more information refer to the following paper https://arxiv.org/abs/2312.09897

Intended uses & limitations

This model is used to summarize financial text in Spanish.

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 3.419313942464226e-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: 10

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
No log 1.0 239 1.2247 0.687 0.5129 0.6465 0.646 44.2425
No log 2.0 478 1.1818 0.6865 0.5145 0.646 0.6458 44.4135
1.2142 3.0 717 1.1477 0.6853 0.5141 0.6459 0.6455 44.203
1.2142 4.0 956 1.1233 0.6863 0.5148 0.647 0.6466 44.2801
1.2426 5.0 1195 1.1101 0.6868 0.517 0.6473 0.6473 44.7425
1.2426 6.0 1434 1.0830 0.6889 0.5193 0.6495 0.6493 44.8064
1.1652 7.0 1673 1.0713 0.6874 0.5172 0.6468 0.6469 44.8252
1.1652 8.0 1912 1.0708 0.688 0.5189 0.649 0.6486 44.9962
1.1176 9.0 2151 1.0664 0.688 0.5186 0.6488 0.6485 45.0357
1.1176 10.0 2390 1.0660 0.6881 0.5187 0.6489 0.6488 44.9812

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2
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