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https://github.com/Felflare/rpunct

📝An easy-to-use package to restore punctuation of the text.
https://github.com/Felflare/rpunct

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📝An easy-to-use package to restore punctuation of the text.

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README 

        
# ✏️ rpunct - Restore Punctuation

[![forthebadge](https://forthebadge.com/images/badges/made-with-crayons.svg)]()



This repo contains code for Punctuation restoration.



This package is intended for direct use as a punctuation restoration model for the general English language. Alternatively, you can use this for further fine-tuning on domain-specific texts for punctuation restoration tasks.

It uses HuggingFace's `bert-base-uncased` model weights that have been fine-tuned for Punctuation restoration.



Punctuation restoration works on arbitrarily large text.

And uses GPU if it's available otherwise will default to CPU.



List of punctuations we restore:

* Upper-casing

* Period: **.**  

* Exclamation: **!** 

* Question Mark: **?** 

* Comma:  **,** 

* Colon:  **:** 

* Semi-colon: **;** 

* Apostrophe: **'** 

* Dash: **-** 



---------------------------

## 🚀 Usage

**Below is a quick way to get up and running with the model.**

1. First, install the package.

```bash

pip install rpunct

```

2. Sample python code.

```python

from rpunct import RestorePuncts

# The default language is 'english'

rpunct = RestorePuncts()

rpunct.punctuate("""in 2018 cornell researchers built a high-powered detector that in combination with an algorithm-driven process called ptychography set a world record

by tripling the resolution of a state-of-the-art electron microscope as successful as it was that approach had a weakness it only worked with ultrathin samples that were

a few atoms thick anything thicker would cause the electrons to scatter in ways that could not be disentangled now a team again led by david muller the samuel b eckert

professor of engineering has bested its own record by a factor of two with an electron microscope pixel array detector empad that incorporates even more sophisticated

3d reconstruction algorithms the resolution is so fine-tuned the only blurring that remains is the thermal jiggling of the atoms themselves""")

# Outputs the following:

# In 2018, Cornell researchers built a high-powered detector that, in combination with an algorithm-driven process called Ptychography, set a world record by tripling the

# resolution of a state-of-the-art electron microscope. As successful as it was, that approach had a weakness. It only worked with ultrathin samples that were a few atoms

# thick. Anything thicker would cause the electrons to scatter in ways that could not be disentangled. Now, a team again led by David Muller, the Samuel B. 

# Eckert Professor of Engineering, has bested its own record by a factor of two with an Electron microscope pixel array detector empad that incorporates even more

# sophisticated 3d reconstruction algorithms. The resolution is so fine-tuned the only blurring that remains is the thermal jiggling of the atoms themselves.

```



-----------------------------------------------

## 🎯 Accuracy

Here is the number of product reviews we used for finetuning the model:



| Language | Number of text samples|

| -------- | ----------------- |

| English  | 560,000           |



We found the best convergence around _**3 epochs**_, which is what presented here and available via a download.



-----------------------------------------------

The fine-tuned model obtained the following accuracy on 45,990 held-out text samples:



| Accuracy | Overall F1 | Eval Support |

| -------- | ---------------------- | ------------------- |

| 91%  | 90%                 | 45,990



-----------------------------------------------

## 💻🎯 Further Fine-Tuning



To start fine-tuning or training please look into `training/train.py` file.

Running `python training/train.py` will replicate the results of this model.



-----------------------------------------------

## ☕ Contact 

Contact [Daulet Nurmanbetov]([email protected]) for questions, feedback and/or requests for similar models.



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