Update README.md

README.md

@@ -1,3 +1,61 @@
----
-license: apache-2.0
----
+---
+license: cc-by-nc-4.0
+language: he
+base_model: onlplab/alephbert-base
+tags:
+  - text-classification
+  - hebrew
+  - medical
+---
+
+# MedTextBERT
+
+A Hebrew medical document classifier fine-tuned on [AlephBERT](https://huggingface.co/onlplab/alephbert-base).  
+Classifies extracted text into 24 document categories covering a wide range of medical specialties.
+
+Built as part of a privacy-first Android app that performs 100% offline OCR on Hebrew medical documents.
+
+## Performance
+
+| Metric | Score |
+|--------|-------|
+| Accuracy | 93.8% |
+| F1 | 93.75% |
+
+Evaluated on a held-out test set after 20 epochs of fine-tuning.
+
+## Categories
+
+`family_medicine` `cardiology` `cardiology_procedures` `imaging`  
+`diabetes_endocrinology` `pathology` `pediatrics` `orthopedics`  
+`neurology` `psychiatry` `urology` `surgery` `gastroenterology`  
+`hematology` `pulmonology` `dermatology` `infections_inflammation`  
+`gynecology` `oncology` `pharmacy` `emergency_medicine`  
+`geriatrics_rehabilitation` `administration_general` `lab_results`
+
+## Training Data
+
+Fine-tuned on a synthetically generated dataset of 4,500+ labeled Hebrew medical documents,
+covering edge cases and category variations to improve generalization across real-world formats.
+
+## Usage
+
+```python
+from transformers import pipeline
+
+classifier = pipeline("text-classification", model="annaadar/MedTextBERT")
+result = classifier("לאחר בדיקת דם שגרתית, נמצאו ערכים תקינים")
+print(result)
+```
+
+## Limitations
+
+- Trained on synthetic data — performance on real-world clinical documents may vary
+- Designed for Hebrew text only
+- Not validated for clinical or diagnostic use
+
+## Intended Use
+
+Research and portfolio purposes only.  
+Not intended for clinical or commercial use.  
+License: CC BY-NC 4.0