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About

The task is to restore punctuation for Russian language. To solve this, I finetuned RuBERT on Lenta dataset from Taiga corpus.

Demo

Evaluation and results are shown in Demo.ipynb notebook. To to re-run this notebook, put model.zip in the working directory and ensure that there is an internet connection from notebook runtime.

Model weights

Trained model weights are available from https://drive.google.com/file/d/1uenebpycXgj82WPGUUsL-SorvGg4YT8n/view?usp=sharing

Training

Model is trained with script

train_transformers.sh --data_dir=data/news/Lenta/ --output_dir=./models/Lenta_10epochs --num_train_epochs=10 --learning_rate=3e-5

Arguments:

--data_dir - directory with train/, test and dev/ subdirectories, each must contain raw .txt files to train or eval model on

All other arguments are passed into transformers.TrainingArguments

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Training BERT for punctuation task

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