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---
license: mit
base_model: unicamp-dl/ptt5-base-portuguese-vocab
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: ptt5-base-portuguese-vocab-finetuned-xlsum-pt
  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-base-portuguese-vocab-finetuned-xlsum-pt

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: 0.0394
- Rouge1: 17.6273
- Rouge2: 16.731
- Rougel: 17.6255
- Rougelsum: 17.629

## 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: 5.6e-05
- train_batch_size: 8
- eval_batch_size: 8
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 0.0596        | 1.0   | 125  | 0.0352          | 17.6273 | 16.731 | 17.6255 | 17.629    |
| 0.0314        | 2.0   | 250  | 0.0324          | 17.6273 | 16.731 | 17.6255 | 17.629    |
| 0.0248        | 3.0   | 375  | 0.0312          | 17.6273 | 16.731 | 17.6255 | 17.629    |
| 0.0213        | 4.0   | 500  | 0.0328          | 17.6273 | 16.731 | 17.6255 | 17.629    |
| 0.0177        | 5.0   | 625  | 0.0322          | 17.6273 | 16.731 | 17.6255 | 17.629    |
| 0.0153        | 6.0   | 750  | 0.0346          | 17.6273 | 16.731 | 17.6255 | 17.629    |
| 0.0139        | 7.0   | 875  | 0.0379          | 17.6273 | 16.731 | 17.6255 | 17.629    |
| 0.0125        | 8.0   | 1000 | 0.0360          | 17.6273 | 16.731 | 17.6255 | 17.629    |
| 0.0113        | 9.0   | 1125 | 0.0372          | 17.6273 | 16.731 | 17.6255 | 17.629    |
| 0.0112        | 10.0  | 1250 | 0.0394          | 17.6273 | 16.731 | 17.6255 | 17.629    |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2