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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Base model
google/pegasus-xsum