---
license: mit
base_model: unicamp-dl/ptt5-base-portuguese-vocab
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: ptt5-temario
  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-temario

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: 2.4269
- Rouge1: 0.0857
- Rouge2: 0.0556
- Rougel: 0.0761
- Rougelsum: 0.0832
- 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   | 3.0796          | 0.0604 | 0.0379 | 0.0539 | 0.0583    | 19.0    |
| No log        | 2.0   | 176  | 2.7409          | 0.0841 | 0.0507 | 0.074  | 0.0814    | 19.0    |
| 3.8249        | 3.0   | 264  | 2.6518          | 0.0866 | 0.0508 | 0.0749 | 0.0831    | 19.0    |
| 3.8249        | 4.0   | 352  | 2.5961          | 0.0868 | 0.0528 | 0.0759 | 0.0837    | 19.0    |
| 2.7351        | 5.0   | 440  | 2.5584          | 0.0869 | 0.0541 | 0.0761 | 0.0838    | 19.0    |
| 2.7351        | 6.0   | 528  | 2.5364          | 0.0858 | 0.0524 | 0.0746 | 0.0824    | 19.0    |
| 2.5802        | 7.0   | 616  | 2.5092          | 0.0847 | 0.0518 | 0.0739 | 0.0812    | 19.0    |
| 2.5802        | 8.0   | 704  | 2.5026          | 0.0854 | 0.055  | 0.0754 | 0.0826    | 19.0    |
| 2.5802        | 9.0   | 792  | 2.4862          | 0.0849 | 0.0551 | 0.0753 | 0.0823    | 19.0    |
| 2.4864        | 10.0  | 880  | 2.4744          | 0.085  | 0.0553 | 0.0754 | 0.0824    | 19.0    |
| 2.4864        | 11.0  | 968  | 2.4676          | 0.0867 | 0.0561 | 0.0767 | 0.0842    | 19.0    |
| 2.4328        | 12.0  | 1056 | 2.4627          | 0.0862 | 0.0562 | 0.0766 | 0.0836    | 19.0    |
| 2.4328        | 13.0  | 1144 | 2.4566          | 0.0874 | 0.0563 | 0.0768 | 0.0845    | 19.0    |
| 2.3615        | 14.0  | 1232 | 2.4495          | 0.0866 | 0.0559 | 0.0765 | 0.084     | 19.0    |
| 2.3615        | 15.0  | 1320 | 2.4439          | 0.0866 | 0.0559 | 0.0765 | 0.084     | 19.0    |
| 2.2926        | 16.0  | 1408 | 2.4447          | 0.0866 | 0.0559 | 0.0765 | 0.084     | 19.0    |
| 2.2926        | 17.0  | 1496 | 2.4437          | 0.0863 | 0.0554 | 0.0762 | 0.0838    | 19.0    |
| 2.2926        | 18.0  | 1584 | 2.4345          | 0.0859 | 0.0557 | 0.0763 | 0.0834    | 19.0    |
| 2.2657        | 19.0  | 1672 | 2.4342          | 0.0868 | 0.0561 | 0.0766 | 0.0842    | 19.0    |
| 2.2657        | 20.0  | 1760 | 2.4328          | 0.0868 | 0.0561 | 0.0766 | 0.0842    | 19.0    |
| 2.2425        | 21.0  | 1848 | 2.4317          | 0.0861 | 0.0559 | 0.0764 | 0.0835    | 19.0    |
| 2.2425        | 22.0  | 1936 | 2.4311          | 0.0861 | 0.0559 | 0.0764 | 0.0835    | 19.0    |
| 2.2338        | 23.0  | 2024 | 2.4292          | 0.0861 | 0.0559 | 0.0764 | 0.0835    | 19.0    |
| 2.2338        | 24.0  | 2112 | 2.4268          | 0.0858 | 0.0561 | 0.0762 | 0.0835    | 19.0    |
| 2.203         | 25.0  | 2200 | 2.4270          | 0.0854 | 0.0558 | 0.0759 | 0.0832    | 19.0    |
| 2.203         | 26.0  | 2288 | 2.4290          | 0.0854 | 0.0556 | 0.0759 | 0.0832    | 19.0    |
| 2.203         | 27.0  | 2376 | 2.4272          | 0.0854 | 0.0556 | 0.0759 | 0.0832    | 19.0    |
| 2.1676        | 28.0  | 2464 | 2.4265          | 0.0854 | 0.0556 | 0.0759 | 0.0832    | 19.0    |
| 2.1676        | 29.0  | 2552 | 2.4273          | 0.0857 | 0.0556 | 0.0761 | 0.0832    | 19.0    |
| 2.1984        | 30.0  | 2640 | 2.4269          | 0.0857 | 0.0556 | 0.0761 | 0.0832    | 19.0    |


### Framework versions

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