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---
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
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