whisper-large-v3-turbo-nope
This model is a fine-tuned version of openai/whisper-large-v3-turbo on the common_voice_16_1 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4736
- Wer: 15.5497
- Cer: 8.5462
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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: 5000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| No log | 0 | 0 | 8.8537 | 1137.9325 | 452.8176 |
| 1.0467 | 0.1 | 500 | 1.6165 | 59.5707 | 44.0850 |
| 0.5278 | 0.2 | 1000 | 0.9622 | 29.9606 | 18.2843 |
| 0.3648 | 0.3 | 1500 | 0.7630 | 24.7043 | 14.1328 |
| 0.346 | 0.4 | 2000 | 0.6770 | 21.1126 | 11.6111 |
| 0.2755 | 0.5 | 2500 | 0.6325 | 21.1564 | 12.0409 |
| 0.3617 | 0.6 | 3000 | 0.5587 | 22.8208 | 11.4895 |
| 0.2343 | 0.7 | 3500 | 0.5154 | 16.8200 | 12.4625 |
| 0.2468 | 0.8 | 4000 | 0.4874 | 18.5721 | 13.8733 |
| 0.2459 | 0.9 | 4500 | 0.4765 | 15.5497 | 8.3516 |
| 0.2776 | 1.0 | 5000 | 0.4736 | 15.5497 | 8.5462 |
Framework versions
- Transformers 4.54.1
- Pytorch 2.8.0.dev20250319+cu128
- Datasets 3.6.0
- Tokenizers 0.21.4