---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- mt_eng_vietnamese
metrics:
- bleu
model-index:
- name: opus-mt-en-vi-finetuned-en-to-vi
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: mt_eng_vietnamese
      type: mt_eng_vietnamese
      config: iwslt2015-vi-en
      split: validation
      args: iwslt2015-vi-en
    metrics:
    - name: Bleu
      type: bleu
      value: 35.8111
---

<!-- 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. -->

# opus-mt-en-vi-finetuned-en-to-vi

This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-vi](https://huggingface.co/Helsinki-NLP/opus-mt-en-vi) on the mt_eng_vietnamese dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2692
- Bleu: 35.8111
- Gen Len: 28.907

## 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: 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: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu    | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| 1.4895        | 1.0   | 8333 | 1.2692          | 35.8111 | 28.907  |


### Framework versions

- Transformers 4.27.3
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.13.2