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--- |
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tags: |
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- generated_from_trainer |
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metrics: |
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- bleu |
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model-index: |
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- name: cantonese-chinese-translation-gen1 |
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results: [] |
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datasets: |
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- raptorkwok/cantonese-chinese-dataset-gen2 |
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--- |
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# Cantonese-Written Chinese Translation Model |
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This model is a fine-tuned version of [fnlp/bart-base-chinese](https://huggingface.co/fnlp/bart-base-chinese) on [Cantonese-Written Chinese Dataset Gen2](https://huggingface.co/raptorkwok/cantonese-chinese-dataset-gen2). |
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It achieves the following results on the evaluation set: |
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- Loss: 1.5413 |
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- Bleu: 40.7808 |
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- Chrf: 42.5628 |
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- Gen Len: 13.2556 |
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## Model description |
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The model is based on BART Chinese model, trained on 1M Cantonese-Written Chinese Parallel Corpus data. |
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## Intended uses & limitations |
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Its intended use is to translate Cantonese sentences to Written Chinese accurately. |
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## Training and evaluation data |
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Training and evaluation data is provided by the [Cantonese-Written Chinese Dataset Gen2](https://huggingface.co/raptorkwok/cantonese-chinese-dataset-gen2). |
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## Training procedure |
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The training was performed using `Seq2SeqTrainer`. |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 10 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Bleu | Chrf | Gen Len | |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:| |
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| 0.2275 | 0.05 | 5000 | 1.5256 | 40.6521 | 42.475 | 13.2277 | |
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| 0.1752 | 0.1 | 10000 | 1.5413 | 40.7808 | 42.5628 | 13.2556 | |
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| 0.1533 | 0.15 | 15000 | 1.5938 | 40.7698 | 42.5348 | 13.2678 | |
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| 0.1442 | 0.2 | 20000 | 1.6487 | 40.6062 | 42.353 | 13.2602 | |
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| 0.1317 | 0.24 | 25000 | 1.7148 | 40.569 | 42.2753 | 13.2798 | |
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### Framework versions |
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- Transformers 4.28.1 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.13.3 |