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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Model tree for deepdml/whisper-base-ta-mix-norm
Base model
openai/whisper-baseDatasets used to train deepdml/whisper-base-ta-mix-norm
Evaluation results
- Wer on Common Voice 17.0self-reported44.347