---
tags:
- generated_from_trainer
metrics:
- bleu
base_model: fnlp/bart-base-chinese
model-index:
- name: cantonese-chinese-translation
  results: []
datasets:
- raptorkwok/cantonese-traditional-chinese-parallel-corpus
pipeline_tag: translation
---

<!-- 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. -->

# cantonese-chinese-translation

This model is a fine-tuned version of [fnlp/bart-base-chinese](https://huggingface.co/fnlp/bart-base-chinese) on [raptorkwok/cantonese-traditional-chinese-parallel-corpus](https://huggingface.co/datasets/raptorkwok/cantonese-traditional-chinese-parallel-corpus) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2258
- Bleu: 62.1085
- Chrf: 60.1854
- Gen Len: 12.8755

## 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: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu    | Chrf    | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|
| 0.3606        | 0.48  | 1000 | 0.2592          | 60.9844 | 58.8851 | 12.8446 |
| 0.3059        | 0.96  | 2000 | 0.2291          | 61.9606 | 60.1201 | 12.8621 |
| 0.2296        | 1.44  | 3000 | 0.2254          | 61.9458 | 60.0434 | 12.8578 |
| 0.2231        | 1.92  | 4000 | 0.2176          | 61.9617 | 59.9299 | 12.8827 |
| 0.174         | 2.39  | 5000 | 0.2290          | 61.9661 | 59.8844 | 12.9068 |
| 0.171         | 2.87  | 6000 | 0.2258          | 62.1085 | 60.1854 | 12.8755 |
| 0.1346        | 3.35  | 7000 | 0.2334          | 61.4554 | 59.5055 | 12.8175 |
| 0.1285        | 3.83  | 8000 | 0.2408          | 61.3332 | 59.3276 | 12.8412 |
| 0.1061        | 4.31  | 9000 | 0.2530          | 61.6505 | 59.614  | 12.8566 |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.13.3