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Add common_voice_15_0 WER

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  1. README.md +32 -5
README.md CHANGED
@@ -13,6 +13,31 @@ tags:
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  metrics:
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  - cer
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  - wer
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  # Whisper-small-ru-pruned
@@ -62,11 +87,13 @@ The context tokens can be removed from the start of the transcription by setting
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  * [waveletdeboshir/whisper-base-ru-pruned](https://huggingface.co/waveletdeboshir/whisper-base-ru-pruned)
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  ## Metrics
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- | | openai/whisper-small | waveletdeboshir/whisper-small-ru-pruned |
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- | :------ | :------ | :------ |
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- | WER* golos-test-crowd | 0.3358 | 0.3471 |
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- | CER* golos-test-crowd | 0.1561 | 0.1444 |
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- *Metrics were measured after text normalization
 
 
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  You can fine-tune this model on your data to achive better performance.
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  metrics:
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  - cer
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  - wer
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+ model-index:
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+ - name: Whisper Small Pruned for Russian
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+ results:
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+ - task:
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+ name: Speech Recognition
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+ type: automatic-speech-recognition
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+ dataset:
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+ name: Common Voice 15.0 (Russian part, test)
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+ type: mozilla-foundation/common_voice_15_0
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+ args: ru
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+ metrics:
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+ - name: WER
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+ type: wer
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+ value: 24.98
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+ - task:
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+ name: Speech Recognition
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+ type: automatic-speech-recognition
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+ dataset:
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+ name: Common Voice 15.0 (Russian part, test)
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+ type: mozilla-foundation/common_voice_15_0
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+ args: ru
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+ metrics:
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+ - name: WER (without punctuation)
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+ type: wer
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+ value: 17.48
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  ---
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  # Whisper-small-ru-pruned
 
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  * [waveletdeboshir/whisper-base-ru-pruned](https://huggingface.co/waveletdeboshir/whisper-base-ru-pruned)
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  ## Metrics
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+ | metric | dataset | openai/whisper-small | waveletdeboshir/whisper-small-ru-pruned |
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+ | :------ | :------ | :------ | :------ |
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+ | WER* | golos-test-crowd | 0.3358 | 0.3471 |
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+ | CER* | golos-test-crowd | 0.1561 | 0.1444 |
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+ | WER* | common_voice_15_0_test | 0.1749 | 0.1748 |
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+ | WER | common_voice_15_0_test | 0.2492 | 0.2498 |
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+ *Metrics were computed after text normalization
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  You can fine-tune this model on your data to achive better performance.
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