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--- |
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language: yue |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: electra-hongkongese-base-hkt-ws |
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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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# electra-hongkongese-base-hkt-ws |
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This model is a fine-tuned version of [toastynews/electra-hongkongese-base-discriminator](https://huggingface.co/toastynews/electra-hongkongese-base-discriminator) on [HKCanCor](https://pycantonese.org/data.html#built-in-data), [CityU and AS](http://sighan.cs.uchicago.edu/bakeoff2005/) for word segmentation. |
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## Model description |
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Performs word segmentation on text from Hong Kong. |
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There are two versions; hk trained with only text from Hong Kong, and hkt trained with text from Hong Kong and Taiwan. Each version have base and small model sizes. |
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## Intended uses & limitations |
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Trained to handle both Hongkongese/Cantonese and Standard Chinese from Hong Kong. Text from other places and English do not work as well. |
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The easiest way is to use with the CKIP Transformers libary. |
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## Training and evaluation data |
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HKCanCor, CityU and AS are converted to BI-encoded word segmentation dataset in Hugging Face format using code from [finetune-ckip-transformers](https://github.com/toastynews/finetune-ckip-transformers). |
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## Training procedure |
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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: 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: 3.0 |
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### Training results |
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|dataset |token_f |token_p |token_r | |
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|:---------|--------|--------|--------| |
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|ud yue_hk | 0.9404| 0.9442| 0.9367| |
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|ud zh_hk | 0.9327| 0.9404| 0.9251| |
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|_hkcancor_|_0.9875_|_0.9868_|_0.9883_| |
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|cityu | 0.9766| 0.9756| 0.9777| |
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|as | 0.9652| 0.9601| 0.9704| |
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_Was trained on hkcancor. Reported for reference only._ |
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### Framework versions |
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- Transformers 4.27.0.dev0 |
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- Pytorch 1.10.0 |
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- Datasets 2.10.1 |
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- Tokenizers 0.13.2 |
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