Add evaluation metrics to model card (exact match 0.525, avg tag F1 0.886)

README.md

@@ -13,6 +13,22 @@ tags:
 datasets:
   - LoveJesus/biblical-tutor-dataset-chirho
 pipeline_tag: text2text-generation
+model-index:
+  - name: biblical-parser-chirho
+    results:
+      - task:
+          type: text2text-generation
+          name: Morphological Parsing
+        dataset:
+          type: LoveJesus/biblical-tutor-dataset-chirho
+          name: Biblical Tutor Dataset (Chirho)
+        metrics:
+          - type: exact_match
+            value: 0.525
+            name: Exact Match
+          - type: f1
+            value: 0.886
+            name: Average Tag F1
 ---
 
 # Biblical Morphological Parser (mT5-small)
@@ -85,6 +101,43 @@ class:{pos} | stem:{stem} | lemma:{lemma} | morph:{code} | person:{p} | gender:{
 - Handles individual words, not full syntactic analysis
 - Performance may vary on words not well-represented in training data
 
+## Evaluation Results
+
+Evaluated on a held-out test set of ~20K word-level parsing examples.
+
+### Overall Metrics
+
+| Metric | Score |
+|--------|-------|
+| **Exact Match** (all tags correct) | **0.525** |
+| **Average Tag F1** (across all tags) | **0.886** |
+
+### Per-Tag F1
+
+| Tag | F1 |
+|-----|-----|
+| class (POS) | 0.963 |
+| number | 0.966 |
+| POS | 0.958 |
+| lemma | 0.935 |
+| person | 0.933 |
+| gender | 0.928 |
+| type | 0.900 |
+| morph | 0.890 |
+| state | 0.878 |
+| stem | 0.859 |
+| gloss | 0.539 |
+
+### Per-Language Exact Match
+
+| Language | Exact Match |
+|----------|-------------|
+| Hebrew | 0.514 |
+| Greek | 0.559 |
+
+> The `gloss` tag (English translation) is the hardest to predict exactly, pulling down the overall exact match rate. The model achieves strong F1 on structural/morphological tags (class, number, POS, person, gender all > 0.92).
+
+
 ---
 
 Built with love for Jesus. Published by [LoveJesus](https://huggingface.co/LoveJesus).