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--- |
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language: |
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- fi |
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license: apache-2.0 |
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tags: |
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- whisper-event |
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- finnish |
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- speech-recognition |
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datasets: |
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- mozilla-foundation/common_voice_11_0 |
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- google/fleurs |
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metrics: |
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- wer |
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- cer |
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model-index: |
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- name: Whisper Large V3 Finnish |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: Common Voice 11.0 |
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type: mozilla-foundation/common_voice_11_0 |
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config: fi |
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split: test |
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args: fi |
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metrics: |
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- name: Wer |
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type: wer |
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value: 8.23 |
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- name: Cer |
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type: cer |
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value: 1.43 |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: FLEURS |
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type: google/fleurs |
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config: fi_fi |
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split: test |
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args: fi_fi |
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metrics: |
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- name: Wer |
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type: wer |
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value: 8.21 |
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- name: Cer |
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type: cer |
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value: 3.23 |
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library_name: transformers |
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pipeline_tag: automatic-speech-recognition |
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--- |
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# This is a conversion of [Finnish-NLP/whisper-large-finnish-v3](https://huggingface.co/Finnish-NLP/whisper-large-finnish-v3) into faster-whisper format. |
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<h3>This is our improved Whisper v3 model that is now finetuned from OpenAI Whisper Large V3 </h3> |
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<p>We improve from our previously finetuned Whisper V2 model in the following manner<a>https://huggingface.co/Finnish-NLP/whisper-large-v2-finnish</a> </p> |
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<p>CV11 (Common Voice 11 test set) WER (Word error rate) 10.42 --> 8.23</p> |
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<p>Fleurs (A speech recognition test set by Google) WER (Word error rate) 10.20 --> 8.21</p> |
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<p>Model was trained on Nvidia RTX4080 for 32k steps with batch size 8, gradient accumulation 2</p> |
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<br> |
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<h3> Original OpenAI Whisper Large V3</h3> |
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- CV11 |
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- WER: 14.81 |
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- WER NORMALIZED: 10.82 |
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- CER: 2.7 |
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- CER NORMALIZED: 2.07 |
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- Fleurs |
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- WER: 12.04 |
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- WER NORMALIZED: 9.63 |
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- CER: 2.48 |
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- CER NORMALIZED: 3.64 |
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<h3> After Finetuning with Finnish data our V3 got these scores on the test set:</h3> |
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- @14000 finetuning steps |
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- CV11 |
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- WER: 11.36 |
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- WER NORMALIZED: 8.31 |
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- CER: 1.93 |
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- CER NORMALIZED: 1.48 |
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- Fleurs |
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- WER: 10.2 |
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- WER NORMALIZED: 8.56 |
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- CER: 2.26 |
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- CER NORMALIZED: 3.54 |
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- @32000 finetuning steps |
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- CV11 |
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- WER: 11.47 |
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- WER NORMALIZED: 8.23 |
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- CER: 1.91 |
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- CER NORMALIZED: 1.43 |
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- Fleurs |
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- WER: 10.1 |
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- WER NORMALIZED: 8.21 |
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- CER: 2.2 |
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- CER NORMALIZED: 3.23 |
