Update README.md

README.md

@@ -26,6 +26,20 @@ model-index:
     - type: cer
       value: 6.462501%
       name: Test CER
+  - task:
+      name: Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Reazonspeech
+      type: custom
+      args: ja
+    metrics:
+    - name: Test WER
+      type: wer
+      value: 40.864413
+    - name: Test CER
+      type: cer
+      value: 29.367348
 ---
 
 # wav2vec2-base-asr
@@ -40,6 +54,15 @@ This model's fine-tuning approach was inspired by and references the training me
 
 Fine-tuning on the common_voice_11_0 dataset led to the following results:
 
+| Step  | Training Loss | Validation Loss | WER      |
+|-------|---------------|-----------------|----------|
+| 1000  | 6.088100      | 3.452597        | 1.000000 |
+| 2000  | 2.816600      | 0.756278        | 0.263624 |
+| 3000  | 0.837600      | 0.471486        | 0.185915 |
+| 4000  | 0.624900      | 0.420854        | 0.159801 |
+| 5000  | 0.533300      | 0.392494        | 0.149141 |
+| 6000  | 0.490000      | 0.394669        | 0.144826 |
+| 7000  | 0.441600      | 0.379999        | 0.141807 |
 
 ### Training hyperparameters
 
@@ -144,7 +167,10 @@ The final model was evaluated as follows:
 On common_voice_11_0:
 - WER: 14.177284%
 - CER: 6.462501%
-  
+
+On reazonspeech(tiny):
+- WER: 40.864413%
+- CER: 29.367348%
 ### Framework versions
 
 - Transformers 4.39.1