---
library_name: transformers
language:
- nan
license: apache-2.0
base_model: Helsinki-NLP/opus-mt-en-ZH
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_12_0
metrics:
- bleu
model-index:
- name: helsinki_new_ver4
  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_ver4

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 mozilla-foundation/common_voice_12_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5400
- Bleu: 2.4304

## 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: 1e-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: 23000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step  | Validation Loss | Bleu    |
|:-------------:|:-------:|:-----:|:---------------:|:-------:|
| 0.7027        | 0.6418  | 1000  | 0.6716          | 2.8141  |
| 0.6767        | 1.2837  | 2000  | 0.6546          | 9.1063  |
| 0.6526        | 1.9255  | 3000  | 0.6394          | 1.9859  |
| 0.643         | 2.5674  | 4000  | 0.6252          | 12.4882 |
| 0.6445        | 3.2092  | 5000  | 0.6118          | 8.8121  |
| 0.6326        | 3.8511  | 6000  | 0.6010          | 12.7405 |
| 0.604         | 4.4929  | 7000  | 0.5926          | 1.4845  |
| 0.5877        | 5.1348  | 8000  | 0.5827          | 12.9972 |
| 0.5721        | 5.7766  | 9000  | 0.5753          | 1.5982  |
| 0.5826        | 6.4185  | 10000 | 0.5672          | 1.6842  |
| 0.5622        | 7.0603  | 11000 | 0.5619          | 14.0609 |
| 0.5486        | 7.7022  | 12000 | 0.5557          | 14.2992 |
| 0.5451        | 8.3440  | 13000 | 0.5507          | 15.4044 |
| 0.5571        | 8.9859  | 14000 | 0.5463          | 8.4964  |
| 0.5448        | 9.6277  | 15000 | 0.5422          | 8.8203  |
| 0.5306        | 10.2696 | 16000 | 0.5400          | 2.4304  |


### Framework versions

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