Update adding evaluation

README.md

@@ -31,7 +31,12 @@ More information needed
 
 ## Training and evaluation data
 
-More information needed
+The model was trained using the Common Voice 17.0 dataset - spanish subset (mozilla-foundation/common_voice_17_0). Both the base model, whisper-large-v3-turbo, and the fine-tuned model, whisper-large-v3-turbo-es, were evaluated using Word Error Rate (WER) on the test split of the same dataset. The results are as follows:
+
+- WER for whisper-large-v3-turbo (base): 10.18%
+- WER for whisper-large-v3-turbo-es (fine-tuned): 2.69%
+
+This significant reduction in WER shows that fine-tuning the model for spanish audio led to improved transcription accuracy compared to the original base model.
 
 ## Training procedure