Create README.md

README.md

@@ -0,0 +1,46 @@
+---
+language:
+- ar
+
+datasets:
+ - HARD
+
+tags:
+ - HARD
+
+widget:
+- text: "جيد. المكان جميل وهاديء. كل شي جيد ونظيف"
+- text: "استغرب تقييم الفندق كخمس نجوم”. لا شي. يستحق"
+
+---
+
+# BERT-ASTD Balanced
+Arabic version bert model fine tuned on Hotel Arabic Reviews dataset from booking.com (HARD)  dataset balanced version to identify sentiments opinion in Arabic language.
+
+## Data
+The model were fine-tuned on ~93000 book reviews in arabic using bert large arabic
+
+
+## Results
+| class    | precision | recall | f1-score | Support |
+|----------|-----------|--------|----------|---------|
+| 0        | 0.9655    | 0.9601 | 0.9628   | 10570   |
+| 1        | 0.9603    | 0.9657 | 0.9630   | 10570   |
+| Accuracy |           |        | 0.9629   | 21140   |
+
+
+
+
+
+## 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-hard-balanced"
+model = AutoModelForSequenceClassification.from_pretrained(model_name,num_labels=2)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+```