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update model card README.md

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  1. README.md +12 -9
  2. train.log +8 -0
README.md CHANGED
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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: whisper-tiny-be-test
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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: 53.11355311355312
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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-be-test
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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: 0.5046
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- - Wer: 53.1136
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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 CHANGED
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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