readme: ---
  language:
  - ar
  
  datasets:
   - ArSentD-LEV
  
  tags:
   - ArSentD-LEV
  
  
  widget:
  - text: "يهدي الله من يشاء"
  - text: "الاسلوب قذر وقمامه"
  
  ---
  
  # bert-arsentd-lev
  Arabic version bert model fine tuned on ArSentD-LEV dataset
  
  ## Data
  The model were fine-tuned on ~4000 sentence from twitter multiple dialect and five classes we used 3 out of 5 int the experiment.
  
           
  
  ## Results
  | class    | precision | recall | f1-score | Support |
  |----------|-----------|--------|----------|---------|
  | 0        | 0.8211    | 0.8080 | 0.8145   | 125     |
  | 1        | 0.7174    | 0.7857 | 0.7500   | 84      |
  | 2        | 0.6867    | 0.6404 | 0.6628   | 89      |
  | Accuracy |           |        | 0.7517   |  298    |
  
  
  ## How to use
  
  You can use these models by installing `torch` or `tensorflow` and Huggingface library `transformers`. And you can use it directly by initializing it like this:  
  
  ```python
  from transformers import AutoModelForSequenceClassification, AutoTokenizer
  
  model_name="mofawzy/bert-arsentd-lev"
  model = AutoModelForSequenceClassification.from_pretrained(model_name,num_labels=3)
  tokenizer = AutoTokenizer.from_pretrained(model_name)
  
  ```
  