---
license: mit
base_model: unicamp-dl/ptt5-base-portuguese-vocab
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: ptt5-cstnews
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# ptt5-cstnews

This model is a fine-tuned version of [unicamp-dl/ptt5-base-portuguese-vocab](https://huggingface.co/unicamp-dl/ptt5-base-portuguese-vocab) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2824
- Rouge1: 0.1798
- Rouge2: 0.1214
- Rougel: 0.1629
- Rougelsum: 0.1734
- Gen Len: 19.0

## 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 88   | 3.1376          | 0.1326 | 0.089  | 0.1198 | 0.1274    | 19.0    |
| No log        | 2.0   | 176  | 2.5907          | 0.1782 | 0.1106 | 0.1507 | 0.169     | 19.0    |
| 3.838         | 3.0   | 264  | 2.4840          | 0.1816 | 0.1192 | 0.1607 | 0.1747    | 19.0    |
| 3.838         | 4.0   | 352  | 2.4281          | 0.1784 | 0.117  | 0.1605 | 0.1725    | 19.0    |
| 2.4977        | 5.0   | 440  | 2.3860          | 0.1757 | 0.1138 | 0.158  | 0.1697    | 19.0    |
| 2.4977        | 6.0   | 528  | 2.3611          | 0.18   | 0.121  | 0.1628 | 0.1744    | 19.0    |
| 2.3101        | 7.0   | 616  | 2.3437          | 0.1792 | 0.1203 | 0.1625 | 0.1733    | 19.0    |
| 2.3101        | 8.0   | 704  | 2.3327          | 0.1791 | 0.121  | 0.1625 | 0.1734    | 19.0    |
| 2.3101        | 9.0   | 792  | 2.3165          | 0.1795 | 0.1217 | 0.1625 | 0.1741    | 19.0    |
| 2.1814        | 10.0  | 880  | 2.3109          | 0.1772 | 0.1186 | 0.1598 | 0.1711    | 19.0    |
| 2.1814        | 11.0  | 968  | 2.2978          | 0.1785 | 0.1201 | 0.1611 | 0.1726    | 19.0    |
| 2.1193        | 12.0  | 1056 | 2.2923          | 0.1792 | 0.1204 | 0.1618 | 0.1733    | 19.0    |
| 2.1193        | 13.0  | 1144 | 2.2958          | 0.1789 | 0.1204 | 0.1613 | 0.1729    | 19.0    |
| 2.0126        | 14.0  | 1232 | 2.2870          | 0.1785 | 0.1204 | 0.161  | 0.1725    | 19.0    |
| 2.0126        | 15.0  | 1320 | 2.2872          | 0.1789 | 0.1204 | 0.1613 | 0.1728    | 19.0    |
| 1.9237        | 16.0  | 1408 | 2.2799          | 0.1792 | 0.1204 | 0.1618 | 0.1733    | 19.0    |
| 1.9237        | 17.0  | 1496 | 2.2825          | 0.1787 | 0.1219 | 0.1626 | 0.1732    | 19.0    |
| 1.9237        | 18.0  | 1584 | 2.2788          | 0.1787 | 0.1219 | 0.1626 | 0.1729    | 19.0    |
| 1.9157        | 19.0  | 1672 | 2.2787          | 0.1784 | 0.1215 | 0.1622 | 0.1727    | 19.0    |
| 1.9157        | 20.0  | 1760 | 2.2835          | 0.1776 | 0.1211 | 0.1614 | 0.1721    | 19.0    |
| 1.8614        | 21.0  | 1848 | 2.2785          | 0.1808 | 0.1218 | 0.1636 | 0.1752    | 19.0    |
| 1.8614        | 22.0  | 1936 | 2.2823          | 0.1795 | 0.1214 | 0.1626 | 0.1732    | 19.0    |
| 1.8565        | 23.0  | 2024 | 2.2774          | 0.1798 | 0.1214 | 0.1629 | 0.1734    | 19.0    |
| 1.8565        | 24.0  | 2112 | 2.2797          | 0.1798 | 0.1214 | 0.1629 | 0.1734    | 19.0    |
| 1.8076        | 25.0  | 2200 | 2.2818          | 0.1798 | 0.1214 | 0.1629 | 0.1734    | 19.0    |
| 1.8076        | 26.0  | 2288 | 2.2825          | 0.1795 | 0.1214 | 0.1626 | 0.1732    | 19.0    |
| 1.8076        | 27.0  | 2376 | 2.2825          | 0.1795 | 0.1214 | 0.1626 | 0.1732    | 19.0    |
| 1.7745        | 28.0  | 2464 | 2.2823          | 0.1798 | 0.1214 | 0.1629 | 0.1734    | 19.0    |
| 1.7745        | 29.0  | 2552 | 2.2829          | 0.1795 | 0.1214 | 0.1626 | 0.1732    | 19.0    |
| 1.8083        | 30.0  | 2640 | 2.2824          | 0.1798 | 0.1214 | 0.1629 | 0.1734    | 19.0    |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.1