---
library_name: transformers
language:
- nan
license: apache-2.0
base_model: Helsinki-NLP/opus-mt-en-ZH
tags:
- generated_from_trainer
datasets:
- sarahwei/Taiwanese-Minnan-Sutiau
metrics:
- bleu
model-index:
- name: helsinki_new_ver5.2
  results: []
---

<!-- 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. -->

# helsinki_new_ver5.2

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 sarahwei/Taiwanese-Minnan-Sutiau dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2017
- Bleu: 2.0589
- Ter: 93.3806

## 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: 3e-06
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- training_steps: 14000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Bleu   | Ter      |
|:-------------:|:------:|:-----:|:---------------:|:------:|:--------:|
| 0.2448        | 0.4230 | 1000  | 0.2484          | 0.2369 | 95.6659  |
| 0.22          | 0.8460 | 2000  | 0.2238          | 0.4532 | 93.8534  |
| 0.1998        | 1.2690 | 3000  | 0.2154          | 0.5837 | 92.9078  |
| 0.1903        | 1.6920 | 4000  | 0.2099          | 0.8498 | 92.0410  |
| 0.175         | 2.1151 | 5000  | 0.2070          | 1.1658 | 93.2230  |
| 0.1675        | 2.5381 | 6000  | 0.2051          | 1.6545 | 93.2230  |
| 0.1684        | 2.9611 | 7000  | 0.2039          | 1.3913 | 92.1986  |
| 0.1573        | 3.3841 | 8000  | 0.2032          | 1.5844 | 92.0410  |
| 0.1564        | 3.8071 | 9000  | 0.2027          | 1.0087 | 104.3341 |
| 0.1532        | 4.2301 | 10000 | 0.2018          | 2.1594 | 92.9866  |
| 0.1486        | 4.6531 | 11000 | 0.2019          | 2.2898 | 93.8534  |
| 0.1576        | 5.0761 | 12000 | 0.2018          | 2.0100 | 92.4350  |
| 0.1439        | 5.4992 | 13000 | 0.2016          | 2.0117 | 93.3806  |
| 0.1486        | 5.9222 | 14000 | 0.2017          | 2.0589 | 93.3806  |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.1
- Tokenizers 0.21.1