Update README.md

README.md

@@ -1,6 +1,38 @@
 ---
-library_name: transformers
+language: en
+license: cc-by-nc-4.0
+tags:
+- token-classification
+- ner
+- northeast-india
+- low-resource
+- xlm-roberta
+metrics:
+- f1
+- precision
+- recall
+model-index:
+- name: MWirelabs/NortheastNER
+  results:
+  - task:
+      type: token-classification
+      name: Named Entity Recognition
+    dataset:
+      name: Custom Northeast India Gazetteers + News Corpus
+      type: custom
+      split: dev
+    metrics:
+    - name: Overall F1
+      type: f1
+      value: 0.964
+    - name: Precision
+      type: precision
+      value: 0.962
+    - name: Recall
+      type: recall
+      value: 0.967
 ---
+
 # MWirelabs/NortheastNER
 
 **NortheastNER** is a Named Entity Recognition (NER) model fine-tuned by [MWirelabs](https://huggingface.co/MWirelabs) to recognize entities specific to **Northeast India**.
@@ -10,8 +42,6 @@ It is based on [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) and t
 
 ## 🔎 What it can recognize
 
-The model is trained to extract the following entity types:
-
 * **PLACES** → States, districts, villages, regions (e.g., *Shillong*, *Tura*, *Ri-Bhoi*)
 * **TRIBES** → Indigenous tribes & sub-tribes (e.g., *Khasi*, *Nyishi*, *Wancho*)
 * **FESTIVALS** → Local festivals (e.g., *Wangala*, *Losar*, *Nyokum Yullo*)
@@ -39,6 +69,28 @@ Evaluated on a 5k-sentence dev set:
 
 ---
 
+## ⚙️ Training Setup
+
+* **Base model**: `xlm-roberta-base`
+* **Max sequence length**: 256
+* **Batch size**: 16
+* **Learning rate**: 3e-5
+* **Epochs**: 3
+* **Weight decay**: 0.01
+* **Optimizer**: AdamW
+* **Framework**: HuggingFace Transformers Trainer API
+
+### 🔧 Environment
+
+* **Transformers**: 4.44.2
+* **Datasets**: 2.20.0
+* **Evaluate**: 0.4.2
+* **PyTorch**: 2.3.0+cu121
+* **Python**: 3.11
+* **Hardware**: Single NVIDIA A4500 GPU (20 GB VRAM), 62 GB RAM, 12 vCPU
+
+---
+
 ## 🚀 Usage
 
 ```python
@@ -65,11 +117,27 @@ Output:
 
 ---
 
-## 📌 Notes
+## 📜 License
 
-* Optimized for **Northeast India domain texts**: news, culture, tourism, indigenous knowledge.
-* Best performance on **PLACES** and **TRIBES**.
-* Model will be continuously improved with more curated datasets (flora, fauna, festivals).
+This model is licensed under the **Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)** license.
+
+You are free to use, share, and adapt the model for non-commercial purposes with attribution.
+
+---
+
+## 📖 Citation
+
+If you use this model in your research, please cite:
+
+```bibtex
+@misc{mwirelabs2025northeastner,
+  title        = {NortheastNER: A Domain-Specific Named Entity Recognition Model for Northeast India},
+  author       = {MWirelabs},
+  year         = {2025},
+  publisher    = {Hugging Face},
+  howpublished = {\url{https://huggingface.co/MWirelabs/NortheastNER}},
+}
+```
 
 ---