---
language:
- multilingual
- pt
base_model: /content/opus-mt-en-mul
tags:
- generated_from_trainer
datasets:
- tiagoblima/translation-pt-indigenouns
metrics:
- bleu
model-index:
- name: tst-gun-gub-pt
  results:
  - task:
      name: Translation
      type: translation
    dataset:
      name: tiagoblima/translation-pt-indigenouns
      type: tiagoblima/translation-pt-indigenouns
    metrics:
    - name: Bleu
      type: bleu
      value: 8.5368
---

<!-- 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. -->

# tst-gun-gub-pt

This model is a fine-tuned version of [/content/opus-mt-en-mul](https://huggingface.co.//content/opus-mt-en-mul) on the tiagoblima/translation-pt-indigenouns dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8158
- Bleu: 8.5368
- Gen Len: 59.24

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Bleu   | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|
| 2.4421        | 0.29  | 4000  | 2.5285          | 3.3785 | 68.48   |
| 2.1667        | 0.59  | 8000  | 2.3018          | 4.5883 | 58.6    |
| 2.0255        | 0.88  | 12000 | 2.1290          | 5.1052 | 67.3    |
| 1.8995        | 1.18  | 16000 | 2.0535          | 7.8429 | 55.48   |
| 1.8322        | 1.47  | 20000 | 1.9960          | 7.2663 | 58.24   |
| 1.7868        | 1.77  | 24000 | 1.9224          | 7.0981 | 66.34   |
| 1.7012        | 2.06  | 28000 | 1.8869          | 7.5657 | 60.3    |
| 1.6773        | 2.36  | 32000 | 1.8613          | 7.9888 | 61.18   |
| 1.6631        | 2.65  | 36000 | 1.8354          | 8.0862 | 60.5    |
| 1.6379        | 2.94  | 40000 | 1.8158          | 8.4077 | 60.18   |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1