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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
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