File size: 1,705 Bytes
6f26459 998e451 6f26459 a473699 6f26459 a473699 af47443 6f26459 a473699 6f26459 a473699 6f26459 8876b51 ae8157c 6f26459 8876b51 6f26459 a473699 8876b51 6f26459 8876b51 6f26459 a473699 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 |
---
base_model: /notebooks/cantonese/bert-base-cantonese
tags:
- generated_from_trainer
- Cantonese
- bert
model-index:
- name: bert-base-cantonese
results: []
license: cc-by-4.0
language:
- yue
pipeline_tag: fill-mask
widget:
- text: "香港原本[MASK]一個人煙稀少嘅漁港。"
example_title: "係"
---
<!-- 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. -->
# bert-base-cantonese
This model is a continue pre-train version of [indiejoseph/cantonese/bert-base-cantonese](https://huggingface.co//notebooks/cantonese/bert-base-cantonese) on [indiejoseph/wikipedia-zh-yue-filtered](https://huggingface.co/datasets/indiejoseph/wikipedia-zh-yue-filtered).
## Model description
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)
## 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: 5e-05
- train_batch_size: 24
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 192
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
### Framework versions
- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0 |