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---
license: mit
base_model: arthurmluz/ptt5-wikilingua-30epochs
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: ptt5-wikilingua-gptextsum
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-wikilingua-gptextsum
This model is a fine-tuned version of [arthurmluz/ptt5-wikilingua-30epochs](https://huggingface.co/arthurmluz/ptt5-wikilingua-30epochs) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1738
- Rouge1: 0.1741
- Rouge2: 0.0918
- Rougel: 0.1451
- Rougelsum: 0.1624
- 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 | 70 | 2.3792 | 0.1569 | 0.0643 | 0.1218 | 0.1443 | 19.0 |
| No log | 2.0 | 140 | 2.2867 | 0.1786 | 0.0801 | 0.1329 | 0.162 | 19.0 |
| 2.4042 | 3.0 | 210 | 2.2380 | 0.1653 | 0.0682 | 0.1244 | 0.152 | 19.0 |
| 2.4042 | 4.0 | 280 | 2.2055 | 0.1708 | 0.0744 | 0.1302 | 0.1575 | 19.0 |
| 2.4042 | 5.0 | 350 | 2.1882 | 0.173 | 0.0804 | 0.139 | 0.1609 | 19.0 |
| 2.0557 | 6.0 | 420 | 2.1724 | 0.1779 | 0.0846 | 0.1385 | 0.1636 | 19.0 |
| 2.0557 | 7.0 | 490 | 2.1614 | 0.175 | 0.0841 | 0.1359 | 0.1634 | 19.0 |
| 2.0557 | 8.0 | 560 | 2.1537 | 0.1729 | 0.0823 | 0.1348 | 0.1596 | 19.0 |
| 1.866 | 9.0 | 630 | 2.1512 | 0.1743 | 0.0863 | 0.1387 | 0.1637 | 19.0 |
| 1.866 | 10.0 | 700 | 2.1464 | 0.1735 | 0.0866 | 0.1382 | 0.1608 | 19.0 |
| 1.866 | 11.0 | 770 | 2.1398 | 0.1748 | 0.0876 | 0.1383 | 0.1616 | 19.0 |
| 1.7225 | 12.0 | 840 | 2.1424 | 0.1752 | 0.0881 | 0.1426 | 0.1611 | 19.0 |
| 1.7225 | 13.0 | 910 | 2.1431 | 0.173 | 0.0865 | 0.1414 | 0.1592 | 19.0 |
| 1.7225 | 14.0 | 980 | 2.1481 | 0.1713 | 0.0865 | 0.1413 | 0.1585 | 19.0 |
| 1.606 | 15.0 | 1050 | 2.1430 | 0.1694 | 0.0834 | 0.1384 | 0.1557 | 19.0 |
| 1.606 | 16.0 | 1120 | 2.1501 | 0.1676 | 0.0841 | 0.1365 | 0.1538 | 19.0 |
| 1.606 | 17.0 | 1190 | 2.1526 | 0.1698 | 0.0866 | 0.1398 | 0.1561 | 19.0 |
| 1.5257 | 18.0 | 1260 | 2.1536 | 0.1749 | 0.0925 | 0.1441 | 0.1607 | 19.0 |
| 1.5257 | 19.0 | 1330 | 2.1564 | 0.1756 | 0.0945 | 0.1451 | 0.162 | 19.0 |
| 1.4673 | 20.0 | 1400 | 2.1594 | 0.1758 | 0.0949 | 0.1451 | 0.1616 | 19.0 |
| 1.4673 | 21.0 | 1470 | 2.1623 | 0.1762 | 0.0943 | 0.1466 | 0.1624 | 19.0 |
| 1.4673 | 22.0 | 1540 | 2.1644 | 0.1762 | 0.0943 | 0.147 | 0.1627 | 19.0 |
| 1.4108 | 23.0 | 1610 | 2.1672 | 0.1768 | 0.0955 | 0.1473 | 0.1635 | 19.0 |
| 1.4108 | 24.0 | 1680 | 2.1689 | 0.1751 | 0.0933 | 0.1459 | 0.1633 | 19.0 |
| 1.4108 | 25.0 | 1750 | 2.1694 | 0.1751 | 0.0933 | 0.1459 | 0.1633 | 19.0 |
| 1.384 | 26.0 | 1820 | 2.1701 | 0.1751 | 0.0933 | 0.1459 | 0.1633 | 19.0 |
| 1.384 | 27.0 | 1890 | 2.1723 | 0.1747 | 0.0937 | 0.1449 | 0.1626 | 19.0 |
| 1.384 | 28.0 | 1960 | 2.1737 | 0.1743 | 0.0925 | 0.1445 | 0.1623 | 19.0 |
| 1.3507 | 29.0 | 2030 | 2.1738 | 0.1741 | 0.0918 | 0.1451 | 0.1624 | 19.0 |
| 1.3507 | 30.0 | 2100 | 2.1738 | 0.1741 | 0.0918 | 0.1451 | 0.1624 | 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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