whisper-medium-sorani-v1
This model is a fine-tuned version of openai/whisper-medium on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2531
- Wer: 18.9917
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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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: 1250
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2868 | 0.3365 | 500 | 0.3089 | 43.5663 |
| 0.2449 | 0.6729 | 1000 | 0.2722 | 41.1446 |
| 0.2169 | 1.0094 | 1500 | 0.2523 | 37.0698 |
| 0.1657 | 1.3459 | 2000 | 0.2198 | 33.5799 |
| 0.1622 | 1.6824 | 2500 | 0.2001 | 30.5878 |
| 0.0903 | 2.0188 | 3000 | 0.1891 | 28.5673 |
| 0.0997 | 2.3553 | 3500 | 0.1959 | 29.2150 |
| 0.1011 | 2.6918 | 4000 | 0.1738 | 27.6682 |
| 0.0605 | 3.0283 | 4500 | 0.1892 | 27.4459 |
| 0.0538 | 3.3647 | 5000 | 0.1953 | 27.0495 |
| 0.0662 | 3.7012 | 5500 | 0.1816 | 25.2417 |
| 0.0337 | 4.0377 | 6000 | 0.1968 | 25.4060 |
| 0.0372 | 4.3742 | 6500 | 0.1978 | 24.5698 |
| 0.0335 | 4.7106 | 7000 | 0.1993 | 23.8012 |
| 0.0225 | 5.0471 | 7500 | 0.2147 | 24.2556 |
| 0.0305 | 5.3836 | 8000 | 0.2007 | 23.8592 |
| 0.0279 | 5.7201 | 8500 | 0.2105 | 24.2846 |
| 0.0156 | 6.0565 | 9000 | 0.2077 | 22.9988 |
| 0.0173 | 6.3930 | 9500 | 0.2177 | 23.0278 |
| 0.0167 | 6.7295 | 10000 | 0.2148 | 22.7523 |
| 0.0118 | 7.0659 | 10500 | 0.2232 | 22.7523 |
| 0.0132 | 7.4024 | 11000 | 0.2185 | 23.2502 |
| 0.0171 | 7.7389 | 11500 | 0.2167 | 23.2115 |
| 0.0096 | 8.0754 | 12000 | 0.2233 | 22.6363 |
| 0.0106 | 8.4118 | 12500 | 0.2167 | 21.8581 |
| 0.0116 | 8.7483 | 13000 | 0.2227 | 22.4188 |
| 0.0074 | 9.0848 | 13500 | 0.2265 | 21.6067 |
| 0.0085 | 9.4213 | 14000 | 0.2305 | 22.0998 |
| 0.0107 | 9.7577 | 14500 | 0.2409 | 21.9499 |
| 0.0065 | 10.0942 | 15000 | 0.2258 | 21.1959 |
| 0.0058 | 10.4307 | 15500 | 0.2295 | 21.5922 |
| 0.0044 | 10.7672 | 16000 | 0.2343 | 21.5052 |
| 0.0041 | 11.1036 | 16500 | 0.2345 | 21.3312 |
| 0.0055 | 11.4401 | 17000 | 0.2276 | 21.3844 |
| 0.0035 | 11.7766 | 17500 | 0.2366 | 20.9735 |
| 0.0026 | 12.1131 | 18000 | 0.2387 | 20.4853 |
| 0.0036 | 12.4495 | 18500 | 0.2277 | 20.6255 |
| 0.0018 | 12.7860 | 19000 | 0.2396 | 20.5191 |
| 0.0025 | 13.1225 | 19500 | 0.2292 | 20.3258 |
| 0.0017 | 13.4590 | 20000 | 0.2385 | 20.3113 |
| 0.0017 | 13.7954 | 20500 | 0.2388 | 20.2533 |
| 0.0009 | 14.1319 | 21000 | 0.2399 | 20.0454 |
| 0.0017 | 14.4684 | 21500 | 0.2424 | 19.8231 |
| 0.0016 | 14.8048 | 22000 | 0.2437 | 20.1373 |
| 0.0005 | 15.1413 | 22500 | 0.2417 | 19.9923 |
| 0.0019 | 15.4778 | 23000 | 0.2399 | 19.3010 |
| 0.0006 | 15.8143 | 23500 | 0.2449 | 19.1899 |
| 0.0003 | 16.1507 | 24000 | 0.2518 | 19.1850 |
| 0.0006 | 16.4872 | 24500 | 0.2555 | 19.4026 |
| 0.0009 | 16.8237 | 25000 | 0.2468 | 19.3010 |
| 0.0011 | 17.1602 | 25500 | 0.2461 | 19.2769 |
| 0.0004 | 17.4966 | 26000 | 0.2418 | 19.2624 |
| 0.0001 | 17.8331 | 26500 | 0.2525 | 19.1125 |
| 0.0001 | 18.1696 | 27000 | 0.2509 | 19.0594 |
| 0.0 | 18.5061 | 27500 | 0.2520 | 19.0690 |
| 0.0001 | 18.8425 | 28000 | 0.2516 | 19.0497 |
| 0.0 | 19.1790 | 28500 | 0.2521 | 19.0449 |
| 0.0 | 19.5155 | 29000 | 0.2526 | 18.9869 |
| 0.0 | 19.8520 | 29500 | 0.2531 | 18.9917 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.2