Whisper Small ta - Sp03
This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 3.6056
- Wer: 100.0
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: 0.001
- train_batch_size: 4
- eval_batch_size: 1
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.4066 | 1.0 | 4 | 9.3832 | 100.0 |
| 21.3162 | 2.0 | 8 | 21.2056 | 100.0 |
| 11.2822 | 3.0 | 12 | 7.6851 | 100.0 |
| 6.0345 | 4.0 | 16 | 4.8468 | 100.0 |
| 3.8909 | 5.0 | 20 | 3.6056 | 100.0 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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openai/whisper-small