| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: mt5_correct_puntuation_v3 |
| | results: [] |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # mt5_correct_puntuation |
| |
|
| | 本模型使用中文維基百科語料微調 [google/mt5-base](https://huggingface.co/google/mt5-base)預訓練模型之中文標點符號訂正器。目前之準確率為 0.794。 |
| |
|
| | This is a [google/mt5-base](https://huggingface.co/google/mt5-base) model trained on Mandarin Wikipedia corpus and finetuned for Mandarin punctuation correction. Currently the accuracy is 0.794. |
| |
|
| | ## Datasets |
| | 模型使用中文維基百科公開資料微調。將取得的文本以「。」或「，」切分為不超過100字的句子。因為逗號和句號數量壓倒性地多，為盡量平衡資料集，僅保留包含冒號、分號、驚嘆號、問號的句子，作為正確句。將正確句之「，。：；、！？」隨機以「，。：；、！？」，製作為不正確句。訓練用句子共有291,112句。 |
| |
|
| | ### Training hyperparameters |
| |
|
| | The following hyperparameters were used during training: |
| | - learning_rate: 5e-05 |
| | - train_batch_size: 4 |
| | - eval_batch_size: 4 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 1 |
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.20.1 |
| | - Pytorch 1.12.0+cu113 |
| | - Datasets 2.3.2 |
| | - Tokenizers 0.12.1 |
| |
|
