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@@ -5,18 +5,25 @@ tags:
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  model-index:
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  - name: bert-base-cantonese
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  results: []
 
 
 
 
 
 
 
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  ---
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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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  # bert-base-cantonese
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- This model is a fine-tuned version of [/notebooks/cantonese/bert-base-cantonese](https://huggingface.co//notebooks/cantonese/bert-base-cantonese) on an unknown dataset.
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  ## Model description
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- More information needed
 
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  ## Intended uses & limitations
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@@ -39,14 +46,9 @@ The following hyperparameters were used during training:
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  - total_train_batch_size: 192
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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: 15.0
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-
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  ### Training results
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-
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-
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-
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  ### Framework versions
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-
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  - Transformers 4.34.0.dev0
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  - Pytorch 2.0.1+cu117
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  - Datasets 2.14.5
 
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  model-index:
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  - name: bert-base-cantonese
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  results: []
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+ license: cc-by-4.0
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+ language:
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+ - yue
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+ pipeline_tag: fill-mask
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+ widget:
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+ - text: 香港原本[MASK]一個人煙稀少嘅漁港。
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+ example_title: 係
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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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  # bert-base-cantonese
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+ This model is a continue pre-train version of [bert-base-chinese](https://huggingface.co/bert-base-chinese) on [indiejoseph/wikipedia-zh-yue-filtered](https://huggingface.co/datasets/indiejoseph/wikipedia-zh-yue-filtered).
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  ## Model description
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+ This model has extended 500 more Chinese characters which very common in Cantonese, such as `冧`, `噉`, `麪`, `笪`, `冚`, `乸` etc, and continue pre-trained with [indiejoseph/wikipedia-zh-yue-filtered](https://huggingface.co/datasets/indiejoseph/wikipedia-zh-yue-filtered)
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+
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  ## Intended uses & limitations
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  - total_train_batch_size: 192
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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: 10.0
 
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  ### Training results
 
 
 
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  ### Framework versions
 
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  - Transformers 4.34.0.dev0
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  - Pytorch 2.0.1+cu117
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  - Datasets 2.14.5