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---
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
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