Update README.md

README.md

@@ -1,50 +1,52 @@
 ---
-tags:
-- generated_from_trainer
-model-index:
-- name: ARBERTv2_ArLAMA
-  results: []
+datasets:
+- AfnanTS/Final_ArLAMA_DS_tokenized_for_ARBERTv2
+language:
+- ar
+base_model:
+- UBC-NLP/ARBERTv2
+pipeline_tag: fill-mask
 ---
 
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
 
-# ARBERTv2_ArLAMA
+<img src="./Arab_BERT2.jpeg" alt="Model Logo" width="30%" height="30%" align="right"/>
 
-This model is a fine-tuned version of [UBC-NLP/ARBERTv2](https://huggingface.co/UBC-NLP/ARBERTv2) on an unknown dataset.
+**ARBERTv2_ArLAMA** is a transformer-based Arabic language model fine-tuned on Masked Language Modeling (MLM) tasks. The model uses Knowledge Graphs (KGs) to enhance its understanding of semantic relations and improve its performance in various Arabic NLP tasks.
 
-## Model description
 
-More information needed
 
-## Intended uses & limitations
+## Uses
 
-More information needed
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
 
-## Training and evaluation data
+### Direct Use
 
-More information needed
 
-## Training procedure
+Filling masked tokens in Arabic text, particularly in contexts enriched with knowledge from KGs.
 
-### Training hyperparameters
 
-The following hyperparameters were used during training:
-- learning_rate: 2e-05
-- train_batch_size: 8
-- eval_batch_size: 8
-- seed: 42
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: linear
-- num_epochs: 5
+### Downstream Use
 
-### Training results
+Can be further fine-tuned for Arabic NLP tasks that require semantic understanding, such as text classification or question answering.
 
 
 
-### Framework versions
+## How to Get Started with the Model
 
-- Transformers 4.27.1
-- Pytorch 2.3.0+cu121
-- Datasets 2.19.1
-- Tokenizers 0.13.3
+```python
+from transformers import pipeline
+fill_mask = pipeline("fill-mask", model="AfnanTS/ARBERTv2_ArLAMA")
+fill_mask("اللغة [MASK] مهمة جدا."
+```
+
+## Training Details
+
+### Training Data
+
+Trained on the ArLAMA dataset, which is designed to represent Knowledge Graphs in natural language.
+
+
+
+### Training Procedure
+
+Continued pre-training of ArBERTv2 using Masked Language Modeling (MLM) tasks, integrating structured knowledge from Knowledge Graphs.