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 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:
Input Text: Feed the model with text excluding punctuation marks.
Letter Case: The model does not recognize changes in letter case.
Authors
- Mark Stolyarov