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--- |
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language: |
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- multilingual |
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license: apache-2.0 |
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base_model: openai/whisper-medium |
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tags: |
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- hf-asr-leaderboard |
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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: model trenovan na en_de_en simi setu, nastaveni jazyka en overeni3 |
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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: odpovidajici nazvu modelu |
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type: mozilla-foundation/common_voice_11_0 |
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args: 'config: ende, split: train' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 31.315296008572197 |
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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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should probably proofread and complete it, then remove this comment. --> |
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# model trenovan na en_de_en simi setu, nastaveni jazyka en overeni3 |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the odpovidajici nazvu modelu dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2841 |
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- Wer: 31.3153 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.15.2 |
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