openai/whisper-base
This model is a fine-tuned version of openai/whisper-base on the common_voice_22_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.5965
- Wer: 14.1271
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: 3.75e-05
- train_batch_size: 128
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH 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: 100000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0041 | 21.6450 | 5000 | 0.3770 | 16.8402 |
| 0.0025 | 43.2900 | 10000 | 0.4045 | 16.4480 |
| 0.0034 | 64.9351 | 15000 | 0.4193 | 16.2587 |
| 0.0014 | 86.5801 | 20000 | 0.4449 | 15.8953 |
| 0.0012 | 108.2251 | 25000 | 0.4490 | 15.8251 |
| 0.0 | 129.8701 | 30000 | 0.4585 | 14.3882 |
| 0.0 | 151.5152 | 35000 | 0.4865 | 13.9656 |
| 0.0 | 173.1602 | 40000 | 0.5256 | 13.7763 |
| 0.0 | 194.8052 | 45000 | 0.5518 | 13.6419 |
| 0.0 | 216.4502 | 50000 | 0.5558 | 13.6461 |
| 0.0 | 238.0952 | 55000 | 0.5683 | 13.7171 |
| 0.0 | 259.7403 | 60000 | 0.5801 | 13.9259 |
| 0.0 | 281.3853 | 65000 | 0.5886 | 13.9631 |
| 0.0 | 303.0303 | 70000 | 0.5965 | 14.1271 |
Framework versions
- Transformers 4.52.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1