# GreekSocialBERT

A greek pre-trained language model based on [GreekBERT](https://huggingface.co/nlpaueb/bert-base-greek-uncased-v1). This model is an updated version of [greeksocialbert-base-greek-uncased-v1](https://huggingface.co/gealexandri/greeksocialbert-base-greek-uncased-v1).

## Pre-training data

The pre-trained model GreekBERT is additionally trained on a corpus of 458,293 documents collected from greek social media (Twitter, Instagram, Facebook and YouTube), using GreekBERT's tokenizer.

The corpus has been provided by [Palo LTD](http://www.paloservices.com/).


## Requirements

```
pip install transformers
pip install torch

```

## Pre-processing details

In order to use this model, the text needs to be pre-processed as follows:

* remove all greek diacritics
* convert to lowercase

```python
import unicodedata

def preprocess(text):
  text = text.lower()
  text = unicodedata.normalize('NFD',text).translate({ord('\N{COMBINING ACUTE ACCENT}'):None})
  return text
```

## Load Model

```python
from transformers import AutoTokenizer, AutoModelForMaskedLM

tokenizer = AutoTokenizer.from_pretrained("pchatz/greeksocialbert-base-greek-social-media-v2")

model = AutoModelForMaskedLM.from_pretrained("pchatz/greeksocialbert-base-greek-social-media-v2")
```
You can use this model directly with a pipeline for masked language modeling:

```python
from transformers import pipeline

fill = pipeline('fill-mask', model=model, tokenizer=tokenizer)
fill(f'μεσα {fill.tokenizer.mask_token} δικτυωσης')
```

## Evaluation on MLM and Sentiment Analysis tasks

For detailed results refer to Thesis: ['Ανάλυση συναισθήματος κειμένου στα Ελληνικά με χρήση Δικτύων Μετασχηματιστών'](	http://artemis.cslab.ece.ntua.gr:8080/jspui/handle/123456789/18623)

## Author

[Pavlina Chatziantoniou](https://huggingface.co/pchatz), [Georgios Alexandridis](https://huggingface.co/gealexandri) and Athanasios Voulodimos

## BibTeX entry and citation info

http://artemis.cslab.ece.ntua.gr:8080/jspui/handle/123456789/18623

```bibtex

@Article{info12080331,
AUTHOR = {Alexandridis, Georgios and Varlamis, Iraklis and Korovesis, Konstantinos and Caridakis, George and Tsantilas, Panagiotis},
TITLE = {A Survey on Sentiment Analysis and Opinion Mining in Greek Social Media},
JOURNAL = {Information},
VOLUME = {12},
YEAR = {2021},
NUMBER = {8},
ARTICLE-NUMBER = {331},
URL = {https://www.mdpi.com/2078-2489/12/8/331},
ISSN = {2078-2489},
DOI = {10.3390/info12080331}
}
```
{"language": ["el"], "widget": [{"text": "\u03bc\u03b5\u03c3\u03b1 [MASK] \u03b4\u03b9\u03ba\u03c4\u03c5\u03c9\u03c3\u03b7\u03c2"}]}
transformers pytorch bert fill-mask el autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #fill-mask #el #autotrain_compatible #endpoints_compatible #region-us 

# GreekSocialBERT

A greek pre-trained language model based on GreekBERT. This model is an updated version of greeksocialbert-base-greek-uncased-v1.

## Pre-training data

The pre-trained model GreekBERT is additionally trained on a corpus of 458,293 documents collected from greek social media (Twitter, Instagram, Facebook and YouTube), using GreekBERT's tokenizer.

The corpus has been provided by Palo LTD.


## Requirements



## Pre-processing details

In order to use this model, the text needs to be pre-processed as follows:

* remove all greek diacritics
* convert to lowercase



## Load Model


You can use this model directly with a pipeline for masked language modeling:



## Evaluation on MLM and Sentiment Analysis tasks

For detailed results refer to Thesis: 'Ανάλυση συναισθήματος κειμένου στα Ελληνικά με χρήση Δικτύων Μετασχηματιστών'

## Author

Pavlina Chatziantoniou, Georgios Alexandridis and Athanasios Voulodimos

## BibTeX entry and citation info

URL


# GreekSocialBERT

A greek pre-trained language model based on GreekBERT. This model is an updated version of greeksocialbert-base-greek-uncased-v1. ## Pre-training data

The pre-trained model GreekBERT is additionally trained on a corpus of 458,293 documents collected from greek social media (Twitter, Instagram, Facebook and YouTube), using GreekBERT's tokenizer.

The corpus has been provided by Palo LTD. ## Requirements ## Pre-processing details

In order to use this model, the text needs to be pre-processed as follows:

* remove all greek diacritics
* convert to lowercase ## Load Model


You can use this model directly with a pipeline for masked language modeling: ## Evaluation on MLM and Sentiment Analysis tasks

For detailed results refer to Thesis: 'Ανάλυση συναισθήματος κειμένου στα Ελληνικά με χρήση Δικτύων Μετασχηματιστών' ## Author

Pavlina Chatziantoniou, Georgios Alexandridis and Athanasios Voulodimos ## BibTeX entry and citation info

URL
TAGS
#transformers #pytorch #bert #fill-mask #el #autotrain_compatible #endpoints_compatible #region-us 
 # GreekSocialBERT

A greek pre-trained language model based on GreekBERT. This model is an updated version of greeksocialbert-base-greek-uncased-v1. ## Pre-training data

The pre-trained model GreekBERT is additionally trained on a corpus of 458,293 documents collected from greek social media (Twitter, Instagram, Facebook and YouTube), using GreekBERT's tokenizer.

The corpus has been provided by Palo LTD. ## Requirements ## Pre-processing details

In order to use this model, the text needs to be pre-processed as follows:

* remove all greek diacritics
* convert to lowercase ## Load Model


You can use this model directly with a pipeline for masked language modeling: ## Evaluation on MLM and Sentiment Analysis tasks

For detailed results refer to Thesis: 'Ανάλυση συναισθήματος κειμένου στα Ελληνικά με χρήση Δικτύων Μετασχηματιστών' ## Author

Pavlina Chatziantoniou, Georgios Alexandridis and Athanasios Voulodimos ## BibTeX entry and citation info

URL
TAGS
#transformers #pytorch #bert #fill-mask #el #autotrain_compatible #endpoints_compatible #region-us 
# GreekSocialBERT

A greek pre-trained language model based on GreekBERT. This model is an updated version of greeksocialbert-base-greek-uncased-v1.## Pre-training data

The pre-trained model GreekBERT is additionally trained on a corpus of 458,293 documents collected from greek social media (Twitter, Instagram, Facebook and YouTube), using GreekBERT's tokenizer.

The corpus has been provided by Palo LTD.## Requirements## Pre-processing details

In order to use this model, the text needs to be pre-processed as follows:

* remove all greek diacritics
* convert to lowercase## Load Model


You can use this model directly with a pipeline for masked language modeling:## Evaluation on MLM and Sentiment Analysis tasks

For detailed results refer to Thesis: 'Ανάλυση συναισθήματος κειμένου στα Ελληνικά με χρήση Δικτύων Μετασχηματιστών'## Author

Pavlina Chatziantoniou, Georgios Alexandridis and Athanasios Voulodimos## BibTeX entry and citation info

URL