metadata
license: apache-2.0
language: fa
widget:
- text: از هر دستی بگیری از همون [MASK] میدی
- text: این آخرین باره بهت [MASK] میگم
- text: چرا آن جوان بیچاره را به سخره [MASK]
- text: آخه محسن [MASK] هم شد خواننده؟
- text: پسر عجب [MASK] زد
tags:
- bert-fa
- bert-persian
model-index:
- name: dal-bert
results: []
DAL-BERT: Another pre-trained language model for Persian
DAL-BERT is a transformer-based model trained on more than 80 gigabytes of Persian text including both formal and informal (conversational) contexts. The architecture of this model follows the original BERT [Devlin et al.].
How to use the Model
from transformers import BertForMaskedLM, BertTokenizer, pipeline
model = BertForMaskedLM.from_pretrained('sharif-dal/dal-bert')
tokenizer = BertTokenizer.from_pretrained('sharif-dal/dal-bert')
fill_sentence = pipeline('fill-mask', model=model, tokenizer=tokenizer)
fill_sentence('اینجا جمله مورد نظر خود را بنویسید و کلمه موردنظر را [MASK] کنید')
The Training Data
The abovementioned model was trained on a bunch of newspapers, news agencies' websites, technology-related sources, people's comments, magazines, literary criticism, and some blogs.
Evaluation
| Training Loss | Epoch | Step |
|---|---|---|
| 2.1855 | 13 | 7649486 |
Contributors
- Arman Malekzadeh, PhD Student in AI @ Sharif University of Technology [Linkedin] [Github]
- Amirhossein Ramazani, Master's Student in AI @ Sharif University of Technology [Linkedin] [Github]