readme: ---
  language:
  - ar
  
  datasets:
   - ASTD
  
  tags:
   - ASTD
  
  widget:
  - text: "العنف والقتل في محيط العالم في زياده يوميا"
  - text: "الصداقه تزرع الحياه ازهارا"
  
  ---
  
  # BERT-ASTD Balanced
  Arabic version bert model fine tuned on ASTD dataset balanced version to identify twitter sentiments in Arabic language MSA dialect .
  
  ## Data
  The model were fine-tuned on ~1330 tweet in Arabic language.
  
  
  ## Results
  | class    | precision | recall | f1-score | Support |
  |----------|-----------|--------|----------|---------|
  | 0        | 0.9328    | 0.9398 | 0.9363   | 133     |
  | 1        | 0.9394    | 0.9323 | 0.9358   | 133     |
  | Accuracy |           |        | 0.9361   | 266     |
  
  
  
  
  
  ## 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-ASTD"
  model = AutoModelForSequenceClassification.from_pretrained(model_name,num_labels=2)
  tokenizer = AutoTokenizer.from_pretrained(model_name)
  
  ```
  