Whisper Base ta

This model is a fine-tuned version of openai/whisper-base on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2168
  • Wer: 44.3470
  • Cer: 9.3419

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: 64
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.04
  • training_steps: 8000

Training results

Training Loss Epoch Step Validation Loss Wer Cer
0.1907 0.125 1000 0.2800 54.7140 12.3286
0.1294 0.25 2000 0.2466 50.1204 10.8475
0.1125 0.375 3000 0.2416 48.2552 10.6527
0.0839 0.5 4000 0.2322 46.5587 10.0303
0.0965 0.625 5000 0.2219 45.3337 9.5889
0.0719 0.75 6000 0.2191 44.6793 9.3874
0.0753 0.875 7000 0.2155 44.4101 9.2483
0.0883 1.0 8000 0.2168 44.3470 9.3419

Framework versions

  • Transformers 4.48.0.dev0
  • Pytorch 2.5.1+cu121
  • Datasets 3.6.0
  • Tokenizers 0.21.0

Citation

Please cite the model using the following BibTeX entry:

@misc{deepdml/whisper-base-ta-mix-norm,
      title={Fine-tuned Whisper base ASR model for speech recognition in Tamil},
      author={Jimenez, David},
      howpublished={\url{https://huggingface.co/deepdml/whisper-base-ta-mix-norm}},
      year={2026}
    }
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