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--- |
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language: |
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- zh |
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- yue |
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- multilingual |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- x-tech/cantonese-mandarin-translations |
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base_model: google/mt5-base |
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model-index: |
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- name: output |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# output |
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This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on dataset [x-tech/cantonese-mandarin-translations](https://huggingface.co/datasets/x-tech/cantonese-mandarin-translations). |
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## Model description |
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The model translates Mandarin sentences to Cantonese. |
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## Intended uses & limitations |
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When you use the model, please make sure to add `translate mandarin to cantonese: <sentence>` (please note the space after colon) before the text you want to translate. |
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## Training and evaluation data |
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Training Dataset: [x-tech/cantonese-mandarin-translations](https://huggingface.co/datasets/x-tech/cantonese-mandarin-translations) |
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## Training procedure |
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Training is based on [example in transformers library](https://github.com/huggingface/transformers/tree/master/examples/pytorch/translation) |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 1 |
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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: 3.0 |
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### Training results |
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Since we still need to set up validation set, we do not have any training results yet. |
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### Framework versions |
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- Transformers 4.12.5 |
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- Pytorch 1.8.1 |
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- Datasets 1.15.1 |
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- Tokenizers 0.10.3 |
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