---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- mt_eng_vietnamese
metrics:
- rouge
- bleu
model-index:
- name: bart-base-translate-en-vi
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: mt_eng_vietnamese
      type: mt_eng_vietnamese
      config: iwslt2015-en-vi
      split: validation
      args: iwslt2015-en-vi
    metrics:
    - name: Rouge1
      type: rouge
      value: 8.5193
    - name: Bleu
      type: bleu
      value: 0.0
---

<!-- 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. -->

# bart-base-translate-en-vi

This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the mt_eng_vietnamese dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0211
- Rouge1: 8.5193
- Rouge2: 1.09
- Rougel: 7.7119
- Rougelsum: 7.7159
- Bleu: 0.0
- Gen Len: 20.0

## 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: 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: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Bleu | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:----:|:-------:|
| 0.0223        | 1.0   | 16665 | 0.0211          | 8.5193 | 1.09   | 7.7119 | 7.7159    | 0.0  | 20.0    |


### Framework versions

- Transformers 4.26.1
- Pytorch 2.1.0+cu118
- Datasets 2.10.1
- Tokenizers 0.13.3