Whisper Medium ig

This model is a fine-tuned version of openai/whisper-medium on the google/fleurs dataset. It achieves the following results on the evaluation set:

  • Loss: 1.5395
  • Wer: 36.6214

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: 32
  • 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: 500
  • training_steps: 5000

Training results

Training Loss Epoch Step Validation Loss Wer
0.1362 0.2 1000 1.2088 40.5087
0.0549 0.4 2000 1.3555 39.1381
0.0268 0.6 3000 1.4718 38.2932
0.0085 1.163 4000 1.5330 36.7742
0.0166 1.363 5000 1.5395 36.6214

Framework versions

  • Transformers 4.42.0.dev0
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1

Citation

@misc{deepdml/whisper-medium-ig-mix,
      title={Fine-tuned Whisper medium ASR model for speech recognition in Igbo},
      author={Jimenez, David},
      howpublished={\url{https://huggingface.co/deepdml/whisper-medium-ig-mix}},
      year={2025}
    }
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