whisper-small-ml
This model is a fine-tuned version of openai/whisper-tiny on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0159
- Wer: 10.5437
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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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 |
|---|---|---|---|---|
| 0.2000 | 3.3784 | 1000 | 0.2324 | 81.7581 |
| 0.0773 | 6.7568 | 2000 | 0.0902 | 53.6331 |
| 0.0214 | 10.1351 | 3000 | 0.0310 | 19.7663 |
| 0.0110 | 13.5135 | 4000 | 0.0159 | 10.5437 |
Framework versions
- Transformers 5.22.1
- Pytorch 2.11.0+cu130
- Datasets 5.1.0
- Tokenizers 0.23.3