---
license: apache-2.0
base_model: Helsinki-NLP/opus-mt-en-zh
tags:
- generated_from_trainer
datasets:
- wmt19
metrics:
- bleu
model-index:
- name: opus-mt-en-zh-finetuned-en-to-zh
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: wmt19
      type: wmt19
      config: zh-en
      split: train
      args: zh-en
    metrics:
    - name: Bleu
      type: bleu
      value: 22.4693
---

<!-- 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-zh-finetuned-en-to-zh

This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-zh](https://huggingface.co/Helsinki-NLP/opus-mt-en-zh) on the wmt19 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6765
- Bleu: 22.4693
- Gen Len: 19.699

## 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu    | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| 1.7238        | 1.0   | 6250 | 1.6765          | 22.4693 | 19.699  |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2