---
base_model: openai/whisper-small
datasets:
- mozilla-foundation/common_voice_17_0
language: sw
library_name: transformers
license: apache-2.0
model-index:
- name: Finetuned openai/whisper-small on Swahili
  results:
  - task:
      type: automatic-speech-recognition
      name: Speech-to-Text
    dataset:
      name: Common Voice (Swahili)
      type: common_voice
    metrics:
    - type: wer
      value: 43.876
---

# Finetuned openai/whisper-small on 58000 Swahili training audio samples from mozilla-foundation/common_voice_17_0.

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 12253 audio samples of Swahili:

### Baseline model (before finetuning) on Swahili
- Word Error Rate: 133.795
- Loss: 2.459

### Finetuned model (after finetuning) on Swahili
- Word Error Rate: 43.876
- Loss: 0.653