Whisper Small Ori vi
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: 1.2003
- Wer: 31.8158
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: 0.0001
- train_batch_size: 16
- eval_batch_size: 8
- 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_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2733 | 2.2222 | 1000 | 1.0770 | 38.2958 |
| 0.081 | 4.4444 | 2000 | 1.2118 | 36.3836 |
| 0.0172 | 6.6667 | 3000 | 1.2445 | 34.6916 |
| 0.0023 | 8.8889 | 4000 | 1.2003 | 31.8158 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.4.0
- Datasets 3.0.2
- Tokenizers 0.20.0
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Base model
openai/whisper-small