---
license: mit
base_model: VietAI/vit5-base
tags:
- generated_from_trainer
datasets:
- mt_eng_vietnamese
metrics:
- bleu
model-index:
- name: my_translator_vi-en
  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: test[:2%]
      args: iwslt2015-vi-en
    metrics:
    - name: Bleu
      type: bleu
      value: 2.6085
---

<!-- 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. -->

# my_translator_vi-en

This model is a fine-tuned version of [VietAI/vit5-base](https://huggingface.co/VietAI/vit5-base) on the mt_eng_vietnamese dataset.
It achieves the following results on the evaluation set:
- Loss: 3.3819
- Bleu: 2.6085
- Gen Len: 18.36

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu   | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
| 3.9425        | 1.0   | 667  | 3.5155          | 2.3213 | 17.32   |
| 3.2655        | 2.0   | 1334 | 3.3819          | 2.6085 | 18.36   |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1