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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
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