Add common_voice_15_0 WER

README.md

@@ -13,6 +13,31 @@ tags:
 metrics:
 - cer
 - wer
+model-index:
+- name: Whisper Small Pruned for Russian
+  results:
+  - task:
+      name: Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Common Voice 15.0 (Russian part, test)
+      type: mozilla-foundation/common_voice_15_0
+      args: ru
+    metrics:
+    - name: WER
+      type: wer
+      value: 24.98
+  - task:
+      name: Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Common Voice 15.0 (Russian part, test)
+      type: mozilla-foundation/common_voice_15_0
+      args: ru
+    metrics:
+    - name: WER (without punctuation)
+      type: wer
+      value: 17.48
 ---
 
 # Whisper-small-ru-pruned
@@ -62,11 +87,13 @@ The context tokens can be removed from the start of the transcription by setting
 * [waveletdeboshir/whisper-base-ru-pruned](https://huggingface.co/waveletdeboshir/whisper-base-ru-pruned)
 
 ## Metrics
-|  | openai/whisper-small | waveletdeboshir/whisper-small-ru-pruned |
-| :------ | :------ | :------ |
-| WER* golos-test-crowd | 0.3358 | 0.3471 |
-| CER* golos-test-crowd | 0.1561 | 0.1444 |
-*Metrics were measured after text normalization
+| metric | dataset | openai/whisper-small | waveletdeboshir/whisper-small-ru-pruned |
+| :------ | :------ | :------ | :------ |
+| WER* | golos-test-crowd | 0.3358 | 0.3471 |
+| CER* | golos-test-crowd | 0.1561 | 0.1444 |
+| WER* | common_voice_15_0_test | 0.1749 | 0.1748 |
+| WER | common_voice_15_0_test | 0.2492 | 0.2498 |
+*Metrics were computed after text normalization
 
 You can fine-tune this model on your data to achive better performance.