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README.md CHANGED
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1
  ---
 
 
2
  license: apache-2.0
3
  base_model: openai/whisper-base
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  tags:
 
5
  - generated_from_trainer
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  datasets:
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- - common_voice_16_0
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  metrics:
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  - wer
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  model-index:
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- - name: openai/whisper-base
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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_16_0
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- type: common_voice_16_0
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  config: ar
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  split: test
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  args: ar
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  metrics:
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  - name: Wer
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  type: wer
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- value: 80.66956686211462
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  ---
27
 
28
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
29
  should probably proofread and complete it, then remove this comment. -->
30
 
31
- # openai/whisper-base
32
 
33
- This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the common_voice_16_0 dataset.
34
  It achieves the following results on the evaluation set:
35
- - Loss: 0.5848
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- - Wer: 80.6696
37
 
38
  ## Model description
39
 
 
1
  ---
2
+ language:
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+ - ar
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  license: apache-2.0
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  base_model: openai/whisper-base
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  tags:
7
+ - whisper-event
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  - generated_from_trainer
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  datasets:
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+ - mozilla-foundation/common_voice_16_0
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  metrics:
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  - wer
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  model-index:
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+ - name: Whisper Base Arabic
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  results:
16
  - 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_16_0 ar
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+ type: mozilla-foundation/common_voice_16_0
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  config: ar
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  split: test
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  args: ar
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  metrics:
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  - name: Wer
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  type: wer
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+ value: 80.47772163527792
29
  ---
30
 
31
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
32
  should probably proofread and complete it, then remove this comment. -->
33
 
34
+ # Whisper Base Arabic
35
 
36
+ This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the mozilla-foundation/common_voice_16_0 ar dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5856
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+ - Wer: 80.4777
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  ## Model description
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