whisper-large-v3-turbo-16e-20000u
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: 0.6263
- Wer: 20.9247
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: 0.0002
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- 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: 2000
- training_steps: 20000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| No log | 0 | 0 | 8.8155 | 100.0 |
| 0.6438 | 0.1 | 2000 | 1.1388 | 50.2930 |
| 0.5006 | 0.2 | 4000 | 0.9544 | 42.9781 |
| 0.3766 | 0.3 | 6000 | 0.8654 | 32.7328 |
| 0.3788 | 0.4 | 8000 | 0.7993 | 29.0862 |
| 0.3314 | 0.5 | 10000 | 0.7550 | 31.1048 |
| 0.2993 | 0.6 | 12000 | 0.7117 | 24.2240 |
| 0.3074 | 0.7 | 14000 | 0.6822 | 26.6768 |
| 0.3779 | 0.8 | 16000 | 0.6472 | 27.6319 |
| 0.3094 | 0.9 | 18000 | 0.6297 | 20.5774 |
| 0.3768 | 1.0 | 20000 | 0.6263 | 20.9247 |
Framework versions
- Transformers 4.54.0
- Pytorch 2.8.0.dev20250319+cu128
- Datasets 3.6.0
- Tokenizers 0.21.2