---
base_model: openai/whisper-large-v3-turbo
datasets:
- bn
language: bn
library_name: transformers
license: apache-2.0
model-index:
- name: Finetuned openai/whisper-large-v3-turbo on Bengali
  results:
  - task:
      type: automatic-speech-recognition
      name: Speech-to-Text
    dataset:
      name: Common Voice (Bengali)
      type: common_voice
    metrics:
    - type: wer
      value: 11.053
---

# Finetuned openai/whisper-large-v3-turbo on 21409 Bengali training audio samples from cv-corpus-21.0-2025-03-14/bn.

This model was created from the Mozilla.ai Blueprint:
[speech-to-text-finetune](https://github.com/mozilla-ai/speech-to-text-finetune).

## Evaluation results on 9363 audio samples of Bengali:

### Baseline model (before finetuning) on Bengali
- Word Error Rate (Normalized): 78.843
- Word Error Rate (Orthographic): 107.027
- Character Error Rate (Normalized): 62.521
- Character Error Rate (Orthographic): 72.012
- Loss: 1.074

### Finetuned model (after finetuning) on Bengali
- Word Error Rate (Normalized): 11.053
- Word Error Rate (Orthographic): 26.436
- Character Error Rate (Normalized): 6.059
- Character Error Rate (Orthographic): 7.537
- Loss: 0.109