update model card README.md
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README.md
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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datasets:
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- 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: common_voice_11_0
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type: common_voice_11_0
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config: be
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split: validation
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args: be
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metrics:
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- name: Wer
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type: wer
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value:
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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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#
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) 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.
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- Wer:
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## Model description
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---
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language:
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- be
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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: Whisper Tiny Belarusian
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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 be
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type: mozilla-foundation/common_voice_11_0
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config: be
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split: validation
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args: be
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metrics:
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- name: Wer
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type: wer
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value: 52.197802197802204
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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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# Whisper Tiny Belarusian
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the mozilla-foundation/common_voice_11_0 be dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5074
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- Wer: 52.1978
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## Model description
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train.log
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train_runtime = 0:13:53.60
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train_samples_per_second = 11.516
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train_steps_per_second = 0.36
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train_runtime = 0:13:53.60
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train_samples_per_second = 11.516
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train_steps_per_second = 0.36
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***** eval metrics *****
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epoch = 0.33
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eval_loss = 0.5074
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eval_runtime = 0:00:16.82
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eval_samples = 64
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eval_samples_per_second = 3.804
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eval_steps_per_second = 0.119
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eval_wer = 52.1978
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