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metadata
language:
  - multilingual
license: apache-2.0
base_model: serge-wilson/whisper-small-wolof
tags:
  - generated_from_trainer
datasets:
  - audiofolder
metrics:
  - wer
model-index:
  - name: Whisper Wolof Lengo AI V5
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: audiofolder
          type: audiofolder
          config: default
          split: None
          args: default
        metrics:
          - name: Wer
            type: wer
            value: 39.312847261594285

Whisper Wolof Lengo AI V5

This model is a fine-tuned version of serge-wilson/whisper-small-wolof on the audiofolder dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3500
  • Wer: 39.3128
  • Cer: 26.3187

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: 0.0005
  • train_batch_size: 8
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-05
  • lr_scheduler_type: polynomial
  • lr_scheduler_warmup_steps: 50
  • training_steps: 1990
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Cer
1.3022 1.0 208 1.2112 146.8307 105.1707
0.8551 2.0 416 0.9020 90.5318 83.8833
0.5754 3.0 624 0.7127 118.9704 102.1064
0.3739 4.0 832 0.5951 63.1591 45.8295
0.2459 5.0 1040 0.4929 63.5446 50.1286
0.1579 6.0 1248 0.4524 51.6158 35.0170
0.0884 7.0 1456 0.4204 46.9554 30.6374
0.0498 8.0 1664 0.3817 51.6158 33.7194
0.0268 9.0 1872 0.3490 40.8550 27.1844
0.012 9.57 1990 0.3500 39.3128 26.3187

Framework versions

  • Transformers 4.39.3
  • Pytorch 2.2.2+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2