---
license: mit
language:
- ru
metrics:
- seqeval
tags:
- generated-from-trainer
- restore_punctuation
widget:
- text: почему она ушла несмотря на то что ей было хорошо
- text: привет как дела
- text: сколько денег нужно чтобы стать счастливым
- text: это было сильно смело но глупо
---

# ruBert-base for Punctuation Correction

The model is built upon the foundation of [ruBert-base](https://huggingface.co./ai-forever/ruBert-base) and has been fine-tuned to correctly place punctuation marks in Russian sentences (it predicts the mark after each word).

Some additional info about the model:

- **Fine-Tuning Source:** The model has undergone fine-tuning using a diverse dataset comprising over 20,000 paragraphs from Russian literary works.
  
- **Supported Classes:** The model is designed to predict classes following specific punctuation marks: ? ! . , : ... and space (as class O).

- **Input Format:** To achieve optimal results, input text should be provided without punctuation marks. The model does not process changes in letter case.


## Usage Guidelines

To use the model effectively, follow these guidelines:

1. **Input Text:** Feed the model with text excluding punctuation marks.
  
2. **Letter Case:** The model does not recognize changes in letter case. 


## Authors
- Mark Stolyarov