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            ---
         
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            language:
         
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            - pt
         
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            license: apache-2.0
         
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            tags:
         
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            - whisper-event
         
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            - generated_from_trainer
         
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            datasets:
         
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            - mozilla-foundation/common_voice_11_0
         
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            metrics:
         
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            - wer
         
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            model-index:
         
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            - name:  
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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: mozilla-foundation/common_voice_11_0 
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                  type: mozilla-foundation/common_voice_11_0
         
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                  config: pt
         
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                  split: test
         
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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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            should probably proofread and complete it, then remove this comment. -->
         
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            #  
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            This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the  
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            It achieves the following results on the evaluation set:
         
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            - Loss: 0.2628
         
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            - Wer: 6.5987
         
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            ##  
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            ##  
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            ## Training procedure
         
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            - Transformers 4.26.0.dev0
         
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            - Pytorch 1.13.0+cu117
         
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            - Datasets 2.7.1.dev0
         
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            - Tokenizers 0.13.2
         
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            ---
         
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            language: pt
         
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            license: apache-2.0
         
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            tags:
         
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            - generated_from_trainer
         
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            - whisper-event
         
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            datasets:
         
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            - mozilla-foundation/common_voice_11_0
         
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            metrics:
         
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            - wer
         
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            model-index:
         
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            - name: openai/whisper-medium
         
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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: mozilla-foundation/common_voice_11_0
         
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                  type: mozilla-foundation/common_voice_11_0
         
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                  config: pt
         
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                  split: test
         
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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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            should probably proofread and complete it, then remove this comment. -->
         
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            # Portuguese Medium Whisper
         
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            This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the common_voice_11_0 dataset.
         
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            It achieves the following results on the evaluation set:
         
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            - Loss: 0.2628
         
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            - Wer: 6.5987
         
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            ## Blog post
         
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            All information about this model in this blog post: [Speech-to-Text & IA | Transcreva qualquer áudio para o português com o Whisper (OpenAI)... sem nenhum custo!](https://medium.com/@pierre_guillou/speech-to-text-ia-transcreva-qualquer-%C3%A1udio-para-o-portugu%C3%AAs-com-o-whisper-openai-sem-ad0c17384681).
         
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            ## New SOTA
         
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            The Normalized WER in the [OpenAI Whisper article](https://cdn.openai.com/papers/whisper.pdf) with the [Common Voice 9.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_9_0) test dataset is 8.1. 
         
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            As this test dataset is similar to the [Common Voice 11.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_11_0) test dataset used to evaluate our model (WER and WER Norm), it means that **our Portuguese Medium Whisper is better than the [Medium Whisper](https://huggingface.co/openai/whisper-medium) model at transcribing audios Portuguese in text** (and even better than the [Whisper Large](https://huggingface.co/openai/whisper-large) that has a WER Norm of 7.1!).
         
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            ## Training procedure
         
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            - Transformers 4.26.0.dev0
         
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            - Pytorch 1.13.0+cu117
         
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            - Datasets 2.7.1.dev0
         
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            - Tokenizers 0.13.2
         
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