|
--- |
|
language: ar |
|
widget: |
|
- text: "للوقايه من عدم انتشار [MASK]" |
|
--- |
|
# arabert_c19: An Arabert model pretrained on 1.5 million COVID-19 multi-dialect Arabic tweets |
|
**ARABERT COVID-19** is a pretrained (fine-tuned) version of the AraBERT v2 model (https://huggingface.co/aubmindlab/bert-base-arabertv02). The pretraining was done using 1.5 million multi-dialect Arabic tweets regarding the COVID-19 pandemic from the “Large Arabic Twitter Dataset on COVID-19” (https://arxiv.org/abs/2004.04315). |
|
The model can achieve better results for the tasks that deal with multi-dialect Arabic tweets in relation to the COVID-19 pandemic. |
|
|
|
# Classification results for multiple tasks including fake-news and hate speech detection when using arabert_c19 and mbert_ar_c19: |
|
For more details refer to the paper (link) |
|
|
|
| | arabert | mbert | distilbert multi | arabert Covid-19 | mbert Covid-19 | |
|
|------------------------------------|----------|----------|------------------|------------------|----------------| |
|
| Contains hate (Binary) | 0.8346 | 0.6675 | 0.7145 | `0.8649` | 0.8492 | |
|
| Talk about a cure (Binary) | 0.8193 | 0.7406 | 0.7127 | 0.9055 | `0.9176` | |
|
| News or opinion (Binary) | 0.8987 | 0.8332 | 0.8099 | `0.9163` | 0.9116 | |
|
| Contains fake information (Binary) | 0.6415 | 0.5428 | 0.4743 | `0.7739` | 0.7228 | |
|
|
|
|
|
# Preprocessing |
|
|
|
```python |
|
from arabert.preprocess import ArabertPreprocessor |
|
model_name="moha/arabert_c19" |
|
arabert_prep = ArabertPreprocessor(model_name=model_name) |
|
text = "للوقايه من عدم انتشار كورونا عليك اولا غسل اليدين بالماء والصابون وتكون عملية الغسل دقيقه تشمل راحة اليد الأصابع التركيز على الإبهام" |
|
arabert_prep.preprocess(text) |
|
``` |
|
|
|
|
|
# Contacts |
|
**Hadj Ameur**: [Github](https://github.com/MohamedHadjAmeur) | <mohamedhadjameur@gmail.com> | <mhadjameur@cerist.dz> |
|
|
|
|
