whisper-large-v3-turbo-nope-en
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: 3.6282
- Wer: 109.3298
- Cer: 76.3723
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 |
| 4.2788 | 0.1 | 500 | 4.0872 | 160.9724 | 102.4893 |
| 4.1267 | 0.2 | 1000 | 3.8964 | 106.7017 | 73.6642 |
| 4.0032 | 0.3 | 1500 | 3.8182 | 110.0745 | 73.1695 |
| 3.8969 | 0.4 | 2000 | 3.8130 | 108.3224 | 77.8156 |
| 3.8894 | 0.5 | 2500 | 3.6948 | 109.8117 | 75.5939 |
| 3.9464 | 0.6 | 3000 | 3.6782 | 111.5637 | 76.2183 |
| 3.8295 | 0.7 | 3500 | 3.6481 | 133.2457 | 100.4784 |
| 3.75 | 0.8 | 4000 | 3.6358 | 112.1770 | 78.8859 |
| 3.7714 | 0.9 | 4500 | 3.6292 | 110.1183 | 77.8480 |
| 3.8284 | 1.0 | 5000 | 3.6282 | 109.3298 | 76.3723 |
Framework versions
- Transformers 4.54.1
- Pytorch 2.8.0.dev20250319+cu128
- Datasets 3.6.0
- Tokenizers 0.21.4