metadata

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.

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