Create README.md

README.md

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+# Punctuator for Simplified Chinese
+
+The model is fine-tuned based on `DistilBertForTokenClassification` for adding punctuations to plain text (simplified Chinese). The model is fine-tuned based on distilled model `bert-base-chinese`.
+
+## Usage
+
+```python
+from transformers import DistilBertForTokenClassification, DistilBertTokenizerFast
+
+model = DistilBertForTokenClassification.from_pretrained("Qishuai/distilbert_punctuator_zh")
+tokenizer = DistilBertTokenizerFast.from_pretrained("Qishuai/distilbert_punctuator_zh")
+```
+
+## Model Overview
+
+### Training data
+Combination of following three dataset:
+
+- News articles of People's Daily 2014. [Reference](https://github.com/InsaneLife/ChineseNLPCorpus)
+
+### Model Performance
+- Validation with MSRA training dataset. [Reference](https://github.com/InsaneLife/ChineseNLPCorpus/tree/master/NER/MSRA)
+- Metrics Report:
+    |                  | precision | recall | f1-score | support |
+    |:----------------:|:---------:|:------:|:--------:|:-------:|
+    |      C_COMMA     |    0.67   |  0.59  |   0.63   |  91566  |
+    |     C_DUNHAO     |    0.50   |  0.37  |   0.42   |  21013  |
+    | C_EXLAMATIONMARK |    0.23   |  0.06  |   0.09   |   399   |
+    |     C_PERIOD     |    0.84   |  0.99  |   0.91   |  44258  |
+    |  C_QUESTIONMARK  |    0.00   |  1.00  |   0.00   |    0    |
+    |     micro avg    |    0.71   |  0.67  |   0.69   |  157236 |
+    |     macro avg    |    0.45   |  0.60  |   0.41   |  157236 |
+    |   weighted avg   |    0.69   |  0.67  |   0.68   |  157236 |
+
+