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README.md
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---
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base_model: openai/whisper-large-v3
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datasets:
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- bn
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language: bn
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library_name: transformers
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license: apache-2.0
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model-index:
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- name: Finetuned openai/whisper-large-v3 on Bengali
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results:
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- task:
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type: automatic-speech-recognition
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name: Speech-to-Text
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dataset:
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name: Common Voice (Bengali)
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type: common_voice
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metrics:
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- type: wer
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value: 9.651
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---
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# Finetuned openai/whisper-large-v3 on 21409 Bengali training audio samples from cv-corpus-21.0-2025-03-14/bn.
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This model was created from the Mozilla.ai Blueprint:
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[speech-to-text-finetune](https://github.com/mozilla-ai/speech-to-text-finetune).
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## Evaluation results on 9363 audio samples of Bengali:
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### Baseline model (before finetuning) on Bengali
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- Word Error Rate (Normalized): 55.463
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- Word Error Rate (Orthographic): 83.344
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- Character Error Rate (Normalized): 35.66
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- Character Error Rate (Orthographic): 40.754
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- Loss: 0.567
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### Finetuned model (after finetuning) on Bengali
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- Word Error Rate (Normalized): 9.651
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- Word Error Rate (Orthographic): 24.288
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- Character Error Rate (Normalized): 4.876
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- Character Error Rate (Orthographic): 6.312
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- Loss: 0.092
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