Updated training

README.md

@@ -26,7 +26,7 @@ model-index:
           split: test
         metrics:
           - type: wer
-            value: 19.49
+            value: 13.85
             name: Test WER
       - task:
           type: automatic-speech-recognition
@@ -37,7 +37,7 @@ model-index:
           split: test
         metrics:
           - type: wer
-            value: 34.47
+            value: 28.21
             name: Test WER
 ---
 
@@ -45,14 +45,14 @@ model-index:
 
 Tajik automatic speech recognition (ASR) model for [sherpa-onnx](https://github.com/k2-fsa/sherpa-onnx). Architecture is non-streaming Zipformer2.
 
-Version 0.60
+Version 0.61
 
 ## Word Error Rate (WER)
 
 | Dataset | WER |
 |---------|-----|
-| [FLEURS Tajik](https://huggingface.co/datasets/google/fleurs) | 19.49 |
-| [Peacockery/tajik-asr-corpus-v3](https://huggingface.co/datasets/Peacockery/tajik-asr-corpus-v3) (test split) | 34.47 |
+| [FLEURS Tajik](https://huggingface.co/datasets/google/fleurs) | 13.85 |
+| [Peacockery/tajik-asr-corpus-v3](https://huggingface.co/datasets/Peacockery/tajik-asr-corpus-v3) (test split) | 28.21 |
 
 ## Training Data
 

am-onnx/decoder.onnx

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am-onnx/encoder.onnx

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am-onnx/joiner.onnx

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