Update README.md

README.md

@@ -13,3 +13,59 @@ tags:
   - gliner
   - groceries
 ---
+
+# Grocery Named Entity Recognition Model
+
+A fine-tuned GLiNER model for identifying grocery items and food categories in text.
+
+## Model Description
+
+This model is fine-tuned on the grocery-ner-dataset to identify 14 different categories of grocery items including fruits, vegetables, dairy products, and more.
+
+### Supported Entity Types
+
+- Fruits Vegetables
+- Lactose, Diary, Eggs, Cheese, Yoghurt
+- Meat, Fish, Seafood
+- Frozen, Prepared Meals
+- Baking, Cooking
+- Cereals, Grains, Canned, Seeds
+- Breads
+- Snacks, Pastries, Treats
+- Frozen Desserts
+- Hot Drinks, Chilled Drinks
+- Alcoholic Drinks
+- Spices, Sauces
+- World Foods
+- Dietary Restrictions, Health, Allergens, Lifestyle
+
+## Training Details
+
+- Base Model: gliner-community/gliner_medium-v2.5
+- Training Data: empathyai/grocery-ner-dataset
+- Batch Size: 8
+- Learning Rate: 5e-6
+- Weight Decay: 0.01
+- Focal Loss Parameters: alpha=0.75, gamma=2
+- Training Strategy: Linear learning rate with 10% warmup
+
+## Usage Example
+
+```python
+from gliner import GLiNER
+
+# Load model
+model = GLiNER.from_pretrained("empathyai/grocery-ner-model")
+
+# Example text
+text = "I need to buy milk, bread, and fresh apples"
+
+# Get predictions
+predictions = model.predict(text)
+print(predictions)
+```
+
+## Limitations
+- Optimized for English language text only
+- Best performance on grocery shopping and food-related contexts
+- May not recognize brand names or regional food items not present in training data