Whisper Small Hre 5.2, train/test split, ASR for male & female Hre voice
This model is a fine-tuned version of openai/whisper-small on the Hre audio dataset 8 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4342
- Cer Ortho: 19.1894
- Cer: 17.1849
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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- 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: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer Ortho | Cer |
|---|---|---|---|---|---|
| 1.1862 | 0.9174 | 100 | 0.8429 | 36.8006 | 33.5051 |
| 0.3688 | 1.8349 | 200 | 0.5354 | 26.6679 | 24.2686 |
| 0.2010 | 2.7523 | 300 | 0.4394 | 24.7669 | 22.4655 |
| 0.1148 | 3.6697 | 400 | 0.3768 | 21.1980 | 19.2824 |
| 0.0712 | 4.5872 | 500 | 0.3922 | 22.0409 | 20.0368 |
| 0.0395 | 5.5046 | 600 | 0.4029 | 22.2561 | 19.8896 |
| 0.0281 | 6.4220 | 700 | 0.4333 | 22.5430 | 19.8344 |
| 0.0158 | 7.3394 | 800 | 0.3824 | 25.5918 | 23.5695 |
| 0.0167 | 8.2569 | 900 | 0.4228 | 20.6062 | 18.5465 |
| 0.0159 | 9.1743 | 1000 | 0.4062 | 20.4448 | 18.3257 |
| 0.0115 | 10.0917 | 1100 | 0.4105 | 23.8702 | 21.9687 |
| 0.0091 | 11.0092 | 1200 | 0.4257 | 24.3006 | 22.4655 |
| 0.0070 | 11.9266 | 1300 | 0.4210 | 21.0725 | 19.2456 |
| 0.0051 | 12.8440 | 1400 | 0.4185 | 19.6198 | 17.6633 |
| 0.0071 | 13.7615 | 1500 | 0.3942 | 19.9426 | 17.5529 |
| 0.0060 | 14.6789 | 1600 | 0.4541 | 21.0904 | 18.3993 |
| 0.0045 | 15.5963 | 1700 | 0.4144 | 19.1714 | 17.1481 |
| 0.0042 | 16.5138 | 1800 | 0.4424 | 19.9785 | 17.5345 |
| 0.0019 | 17.4312 | 1900 | 0.4293 | 19.4584 | 17.4057 |
| 0.0041 | 18.3486 | 2000 | 0.4049 | 18.5796 | 16.7065 |
| 0.0012 | 19.2661 | 2100 | 0.4143 | 18.6514 | 16.6329 |
| 0.0013 | 20.0 | 2180 | 0.4342 | 19.1894 | 17.1849 |
Framework versions
- Transformers 5.13.1
- Pytorch 2.11.0+cu128
- Datasets 2.18.0
- Tokenizers 0.22.2