whisper-small-rw / README.md
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metadata
base_model: mbazaNLP/Whisper-Small-Kinyarwanda
tags:
  - generated_from_trainer
datasets:
  - common_voice_11_0
metrics:
  - wer
model-index:
  - name: whisper-small-rw
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: common_voice_11_0
          type: common_voice_11_0
          config: rw
          split: None
          args: rw
        metrics:
          - name: Wer
            type: wer
            value: 33.420365535248045

whisper-small-rw

This model is a fine-tuned version of mbazaNLP/Whisper-Small-Kinyarwanda on the common_voice_11_0 dataset. It achieves the following results on the evaluation set:

  • Loss: 2.0954
  • Wer: 33.4204

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 1e-05
  • train_batch_size: 16
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 5
  • training_steps: 100
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
No log 1.4286 10 2.3900 34.2037
No log 2.8571 20 2.3111 34.5953
2.1422 4.2857 30 2.2492 34.2037
2.1422 5.7143 40 2.2022 33.9426
1.8742 7.1429 50 2.1669 33.8120
1.8742 8.5714 60 2.1406 33.6815
1.8742 10.0 70 2.1216 33.4204
1.7608 11.4286 80 2.1077 33.2898
1.7608 12.8571 90 2.0994 33.5509
1.6573 14.2857 100 2.0954 33.4204

Framework versions

  • Transformers 4.44.0
  • Pytorch 2.3.1+cu121
  • Datasets 2.21.0
  • Tokenizers 0.19.1