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README.md
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- name: Cer
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type: cer
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value: 3.1561
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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- Loss: 0.2599
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- Wer: 11.2278
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## Model description
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More information needed
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- name: Cer
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type: cer
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value: 3.1561
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- task:
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type: Automatic Speech Recognition
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name: speech-recognition
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dataset:
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name: VoxPopuli
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type: facebook/voxpopuli
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config: fr
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split: test
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args:
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language: fr
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metrics:
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- name: WER
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type: wer
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value: 10.0653
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- name: Cer
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type: cer
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value: 6.5456
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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- Loss: 0.2599
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- Wer: 11.2278
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Using the [evalutaion script](https://github.com/huggingface/community-events/blob/main/whisper-fine-tuning-event/run_eval_whisper_streaming.py) provided in the Whisper Sprint the model achieves these results on the test sets (WER):
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- **google/fleurs: 9.3526 %**
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(python run_eval_whisper_streaming.py --model_id="deepdml/whisper-medium-mix-fr" --dataset="google/fleurs" --config="fr_fr" --device=0 --language="fr")
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- **facebook/multilingual_librispeech: 6.3468 %**
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(python run_eval_whisper_streaming.py --model_id="deepdml/whisper-medium-mix-fr" --dataset="facebook/multilingual_librispeech" --config="french" --device=0 --language="fr")
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- **facebook/voxpopuli: 10.0653 %**
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(python run_eval_whisper_streaming.py --model_id="deepdml/whisper-medium-mix-fr" --dataset="facebook/voxpopuli" --config="fr" --device=0 --language="fr")
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## Model description
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More information needed
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