Update README.md

README.md

@@ -35,15 +35,35 @@ This model is designed to digitize and preserve texts written in Mexico's indige
 - Academic research
 - Community documentation efforts
 
-### Model Variants
-
-- **Best Model** (`Tachiwin_best.traineddata`): Higher accuracy, slower processing (floating-point)
-- **Fast Model** (`Tachiwin_fast.traineddata`): Faster processing, slightly lower accuracy (integer-based)
-
 ### Languages Covered
 
 This model supports all 68 indigenous languages of Mexico and hundreths of variants.
 
+### Sample Text Examples
+
+The model excels at recognizing complex diacritics and special characters found in indigenous Mexican languages:
+
+```
+Latin OCR: (raw tesseract untrained)
+Séli kie' ja sei Wa i ai sé ne ard néi jeu yéi pei la. Jau sét ma kid kota. Anii la a ngéi jeu jud pa la. Wai ai sgt la t& jau sét ma kid kota. Jau sé, ajo ikd anii la jau set, ma kid kotd .
+
+Tachiwin OCR: (trained by Tachiwin)
+Sëü kie’ jä sɇɨ Wa̱ i aɨ śɨ ne̱ aṟö nëi jeu yëi pei la̱. Jau sɇ́ɨ m̱a̱ kiä kötä. Añii Ia̱ a ngʉ́ɨ jeu juö poa̱̱ la̱. Wa̱ i aɨ sʉ́ɨ la̱ tä̱ jau sɇɨ ma̱ kiä kötä̱. Jau sɇ́ɨ, ajö̱ ikö añii Ia̱ jau sɇ́ɨ, ma̱ kiä kötä̱ .
+
+Fragment of "Libro de literatura en lengua chinanteca de Usila, Oaxaca" Lorenzo-Isidrio A, SEP 1999
+```
+
+## Performance
+
+- **Word Error Rate (WER)**: 1.04% on evaluation dataset
+- **Character Error Rate (CER)**: ~1% on evaluation dataset
+- **Accuracy**: 95% word-level accuracy
+
+### Model Variants
+
+- **Best Model** (`Tachiwin.traineddata`): Higher accuracy, slower processing (floating-point)
+- **Fast Model** (`Tachiwin_fast.traineddata`): Faster processing, slightly lower accuracy (integer-based)
+
 ## Usage
 
 ### Requirements