---
base_model: google/pegasus-xsum
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: sumarize_model_pegasus_v2_original
  results: []
language:
- es
pipeline_tag: summarization
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# sumarize_model_pegasus_v2_original

This model is a fine-tuned version of [google/pegasus-xsum](https://huggingface.co/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