---
license: apache-2.0
base_model: Helsinki-NLP/opus-mt-en-zh
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: opus-mt-cantonese-v2
  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. -->

# opus-mt-cantonese-v2

This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-zh](https://huggingface.co./Helsinki-NLP/opus-mt-en-zh).
It achieves the following results on the evaluation set:
- Loss: 1.8948
- Bleu: 4.1931
- Gen Len: 12.2403

## Model description

This model translates English into Cantonese.

## Intended uses & limitations

Translations produced are for experimental purposes. Correctness is not guaranteed. Use at your own risk.

## Training and evaluation data

Trained with Cantonese sentences with English translations:
- 6280 from Tatoeba.
- 1232 from CantoDict.

## Training procedure

80% training / 20% validation. 20 epochs.

### 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: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu   | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
| No log        | 1.0   | 376  | 2.2222          | 1.4485 | 11.5939 |
| 2.5401        | 2.0   | 752  | 1.9855          | 1.9434 | 11.6465 |
| 1.7798        | 3.0   | 1128 | 1.8805          | 1.1681 | 11.9527 |
| 1.4633        | 4.0   | 1504 | 1.8257          | 4.4967 | 12.6944 |
| 1.4633        | 5.0   | 1880 | 1.7930          | 4.3143 | 12.4161 |
| 1.1973        | 6.0   | 2256 | 1.8002          | 4.3407 | 12.0053 |
| 1.0388        | 7.0   | 2632 | 1.7965          | 5.4944 | 12.4075 |
| 0.9027        | 8.0   | 3008 | 1.7912          | 4.1324 | 12.486  |
| 0.9027        | 9.0   | 3384 | 1.8020          | 4.5473 | 12.2044 |
| 0.7774        | 10.0  | 3760 | 1.8120          | 4.3802 | 12.2237 |
| 0.6928        | 11.0  | 4136 | 1.8218          | 5.683  | 12.484  |
| 0.6229        | 12.0  | 4512 | 1.8346          | 4.8839 | 12.229  |
| 0.6229        | 13.0  | 4888 | 1.8521          | 5.6593 | 12.2157 |
| 0.5645        | 14.0  | 5264 | 1.8634          | 4.2758 | 12.1684 |
| 0.5114        | 15.0  | 5640 | 1.8679          | 4.3432 | 12.2463 |
| 0.4809        | 16.0  | 6016 | 1.8734          | 4.7905 | 12.2224 |
| 0.4809        | 17.0  | 6392 | 1.8869          | 5.4113 | 12.2184 |
| 0.447         | 18.0  | 6768 | 1.8902          | 5.4278 | 12.2543 |
| 0.4278        | 19.0  | 7144 | 1.8943          | 4.2225 | 12.4095 |
| 0.4179        | 20.0  | 7520 | 1.8948          | 4.1931 | 12.2403 |


### Framework versions

- Transformers 4.39.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2