SI2M_DarijaBERTV1

Model Card for Fine-Tuned SI2M_DarijaBERT and CamelBERT

This model card outlines the fine-tuning of SI2M_DarijaBERT on a trunc of a large Moroccan Darija dataset scraped from youtube transcriptions and other websites that you can find here : https://huggingface.co/datasets/HANTIFARAH/combined_darija_dataset_cleaned . These transformer model were fine-tuned for the purpose embedding generation in Moroccan Darija, enhancing it performance on specific NLP tasks and tested it Embeddings on text Classification tasks.

Model Details

Model Description

The SI2M_DarijaBERT model have been fine-tuned on Moroccan Darija texts. the model is based on the BERT architecture and specialize in generating embeddings for text classification tasks in Moroccan Darija.

• Developed by: [BAGUENNA Mohammed-Amine]
• Model type: Transformer-based (BERT architecture)
• Language(s) (NLP): Moroccan Darija (Arabic dialect)
• Finetuned from model: SI2M_DarijaBERT

Recommendations

Users should take care to ensure their data falls within the domain of Moroccan Darija text. Further fine-tuning with more specialized data is recommended for domain-specific applications (e.g., medical language).

How to Get Started with the Model

You can use the models with the following code:

from transformers import AutoTokenizer, AutoModelForSequenceClassification

model = AutoModel.from_pretrained("bagamine/SI2M_DarijaBERTV1")
tokenizer = AutoTokenizer.from_pretrained("bagamine/SI2M_DarijaBERTV1")