whisper-small-de-finetuned
This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1801
- Wer: 10.0733
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: 16
- 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: 300
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2107 | 0.2962 | 500 | 0.2104 | 12.7071 |
| 0.2122 | 0.5924 | 1000 | 0.1997 | 11.8993 |
| 0.1820 | 0.8886 | 1500 | 0.1885 | 11.2831 |
| 0.0833 | 1.1848 | 2000 | 0.1840 | 10.9938 |
| 0.0812 | 1.4810 | 2500 | 0.1822 | 10.6481 |
| 0.0723 | 1.7773 | 3000 | 0.1795 | 10.3588 |
| 0.0293 | 2.0735 | 3500 | 0.1825 | 10.4828 |
| 0.0279 | 2.3697 | 4000 | 0.1818 | 10.3513 |
| 0.0285 | 2.6659 | 4500 | 0.1805 | 10.1822 |
| 0.0265 | 2.9621 | 5000 | 0.1801 | 10.0958 |
| 0.0267 | 3.0 | 5064 | 0.1801 | 10.0733 |
Framework versions
- Transformers 5.7.0
- Pytorch 2.10.0+cu128
- Datasets 4.8.5
- Tokenizers 0.22.2