---
license: mit
base_model: unicamp-dl/ptt5-base-portuguese-vocab
tags:
- generated_from_trainer
datasets:
- xlsum
metrics:
- rouge
model-index:
- name: ptt5-xlsumm-30epochs
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: xlsum
      type: xlsum
      config: portuguese
      split: test
      args: portuguese
    metrics:
    - name: Rouge1
      type: rouge
      value: 0.3246
---

<!-- 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-xlsumm-30epochs

This model is a fine-tuned version of [unicamp-dl/ptt5-base-portuguese-vocab](https://huggingface.co./unicamp-dl/ptt5-base-portuguese-vocab) on the xlsum dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1787
- Rouge1: 0.3246
- Rouge2: 0.1471
- Rougel: 0.2617
- Rougelsum: 0.2641
- Gen Len: 18.7065

## 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 |
|:-------------:|:-----:|:------:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.5549        | 1.0   | 28701  | 2.2631          | 0.3049 | 0.1232 | 0.2416 | 0.2436    | 18.8318 |
| 2.4878        | 2.0   | 57402  | 2.2000          | 0.3134 | 0.1322 | 0.2497 | 0.2519    | 18.7965 |
| 2.3021        | 3.0   | 86103  | 2.1654          | 0.3161 | 0.1354 | 0.2528 | 0.255     | 18.732  |
| 2.2808        | 4.0   | 114804 | 2.1423          | 0.3179 | 0.1376 | 0.2544 | 0.2565    | 18.7217 |
| 2.2731        | 5.0   | 143505 | 2.1291          | 0.3202 | 0.1405 | 0.2567 | 0.259     | 18.7037 |
| 2.1654        | 6.0   | 172206 | 2.1209          | 0.3209 | 0.1417 | 0.2577 | 0.2598    | 18.6956 |
| 2.1716        | 7.0   | 200907 | 2.1173          | 0.3213 | 0.1423 | 0.2584 | 0.2606    | 18.7256 |
| 2.0696        | 8.0   | 229608 | 2.1136          | 0.3234 | 0.1441 | 0.2603 | 0.2627    | 18.7352 |
| 2.0492        | 9.0   | 258309 | 2.1123          | 0.3214 | 0.1425 | 0.2589 | 0.261     | 18.6357 |
| 2.0953        | 10.0  | 287010 | 2.1136          | 0.3244 | 0.146  | 0.2611 | 0.2634    | 18.7001 |
| 2.0358        | 11.0  | 315711 | 2.1180          | 0.3248 | 0.1466 | 0.2617 | 0.2639    | 18.6868 |
| 1.9475        | 12.0  | 344412 | 2.1191          | 0.3243 | 0.1463 | 0.2614 | 0.2637    | 18.6707 |
| 2.0194        | 13.0  | 373113 | 2.1181          | 0.3253 | 0.1466 | 0.2616 | 0.264     | 18.6939 |
| 1.925         | 14.0  | 401814 | 2.1236          | 0.3232 | 0.1454 | 0.2604 | 0.2629    | 18.6843 |
| 1.9194        | 15.0  | 430515 | 2.1294          | 0.3239 | 0.1464 | 0.2612 | 0.2636    | 18.6792 |
| 1.9163        | 16.0  | 459216 | 2.1301          | 0.3248 | 0.1464 | 0.261  | 0.2635    | 18.701  |
| 1.8482        | 17.0  | 487917 | 2.1366          | 0.325  | 0.1473 | 0.2619 | 0.2644    | 18.6786 |
| 1.8637        | 18.0  | 516618 | 2.1387          | 0.3263 | 0.1483 | 0.2624 | 0.2648    | 18.6811 |
| 1.8496        | 19.0  | 545319 | 2.1425          | 0.3244 | 0.1461 | 0.2613 | 0.2637    | 18.6934 |
| 1.8565        | 20.0  | 574020 | 2.1513          | 0.3257 | 0.1479 | 0.2626 | 0.2649    | 18.702  |
| 1.7683        | 21.0  | 602721 | 2.1559          | 0.3261 | 0.1482 | 0.2622 | 0.2646    | 18.718  |
| 1.7483        | 22.0  | 631422 | 2.1577          | 0.3254 | 0.1482 | 0.2625 | 0.2649    | 18.6939 |
| 1.7832        | 23.0  | 660123 | 2.1614          | 0.3234 | 0.147  | 0.2616 | 0.264     | 18.7033 |
| 1.8002        | 24.0  | 688824 | 2.1625          | 0.3246 | 0.1477 | 0.2626 | 0.2649    | 18.682  |
| 1.7381        | 25.0  | 717525 | 2.1689          | 0.3253 | 0.1473 | 0.2617 | 0.2641    | 18.7289 |
| 1.7367        | 26.0  | 746226 | 2.1677          | 0.3255 | 0.1475 | 0.2626 | 0.2649    | 18.7015 |
| 1.752         | 27.0  | 774927 | 2.1760          | 0.3255 | 0.1482 | 0.2631 | 0.2654    | 18.7146 |
| 1.7595        | 28.0  | 803628 | 2.1753          | 0.3241 | 0.1468 | 0.2616 | 0.264     | 18.7036 |
| 1.777         | 29.0  | 832329 | 2.1785          | 0.3246 | 0.1474 | 0.2618 | 0.2643    | 18.7089 |
| 1.7142        | 30.0  | 861030 | 2.1787          | 0.3246 | 0.1471 | 0.2617 | 0.2641    | 18.7065 |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3