Add cross-language evaluation matrix (4-model × 4-language study)

README.md

@@ -173,4 +173,37 @@ If you use this model, please cite:
   publisher = {HuggingFace},
   url       = {https://huggingface.co/abhiprd20/hindi-sentiment-model}
 }
-```
+```
+
+---
+
+## 📊 Cross-Language Evaluation
+
+Each model was evaluated on all 4 languages (300 sentences per language, 100 per class).
+This shows how well models trained on one language transfer to others.
+
+### Accuracy Matrix
+
+| Model | English | Hindi | Maithili | Bhojpuri |
+|---|---|---|---|---|
+| **English model** | **79.5%** ✓ | 34.0% | 33.3% | 33.0% |
+| ⭐ **Hindi model** _(this model)_ | 60.0% | **68.0%** ✓ | 63.3% | 61.7% |
+| **Maithili model** | 63.0% | 59.0% | **90.3%** ✓ | 75.0% |
+| **Bhojpuri model** | 59.0% | 47.3% | 47.3% | **98.0%** ✓ |
+
+### F1 Matrix (macro)
+
+| Model | English | Hindi | Maithili | Bhojpuri |
+|---|---|---|---|---|
+| **English model** | **0.5424** ✓ | 0.1912 | 0.1667 | 0.1654 |
+| ⭐ **Hindi model** _(this model)_ | 0.4362 | **0.6778** ✓ | 0.6319 | 0.6042 |
+| **Maithili model** | 0.4443 | 0.5757 | **0.9035** ✓ | 0.7458 |
+| **Bhojpuri model** | 0.4250 | 0.4166 | 0.4114 | **0.9801** ✓ |
+
+### Key Findings
+
+- Hindi transfers significantly better than English to both Maithili (**63.3%**) and Bhojpuri (**61.7%**), nearly doubling English performance.
+- Supports the hypothesis that **linguistic proximity** (Hindi → Bihari languages) aids cross-lingual transfer.
+- Hindi model performs reasonably on English (60%), suggesting partial bidirectional transfer.
+
+> **Full paper:** This cross-evaluation is part of a research study on cross-lingual transfer for low-resource Bihari languages. See the companion datasets and models: [Maithili](https://huggingface.co/abhiprd20/maithili-sentiment-model) | [Bhojpuri](https://huggingface.co/abhiprd20/bhojpuri-sentiment-model) | [Hindi](https://huggingface.co/abhiprd20/hindi-sentiment-model) | [English](https://huggingface.co/abhiprd20/nlp-sentiment-model)