throatmic_subvocalization_whisper_tiny
This model is a fine-tuned version of openai/whisper-tiny on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.3807
- Wer: 0.6449
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-06
- train_batch_size: 16
- eval_batch_size: 64
- seed: 42
- optimizer: Use 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: 50
- training_steps: 800
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 7.2094 | 0.4464 | 25 | 5.9584 | 1.7658 |
| 4.7209 | 0.8929 | 50 | 3.3913 | 1.1397 |
| 2.5229 | 1.3393 | 75 | 2.1995 | 0.9069 |
| 1.8454 | 1.7857 | 100 | 1.8676 | 0.8454 |
| 1.6015 | 2.2321 | 125 | 1.7199 | 0.7794 |
| 1.3786 | 2.6786 | 150 | 1.6296 | 0.7574 |
| 1.2147 | 3.125 | 175 | 1.5654 | 0.7432 |
| 1.0976 | 3.5714 | 200 | 1.5200 | 0.7135 |
| 1.0156 | 4.0179 | 225 | 1.4829 | 0.6759 |
| 0.8611 | 4.4643 | 250 | 1.4689 | 0.7050 |
| 0.8818 | 4.9107 | 275 | 1.4394 | 0.6585 |
| 0.7822 | 5.3571 | 300 | 1.4273 | 0.6669 |
| 0.6969 | 5.8036 | 325 | 1.4159 | 0.6481 |
| 0.7037 | 6.25 | 350 | 1.4057 | 0.6533 |
| 0.6555 | 6.6964 | 375 | 1.3991 | 0.6475 |
| 0.5759 | 7.1429 | 400 | 1.3927 | 0.6546 |
| 0.5217 | 7.5893 | 425 | 1.3936 | 0.6397 |
| 0.5731 | 8.0357 | 450 | 1.3849 | 0.6436 |
| 0.4753 | 8.4821 | 475 | 1.3839 | 0.6345 |
| 0.4799 | 8.9286 | 500 | 1.3816 | 0.6546 |
| 0.4369 | 9.375 | 525 | 1.3824 | 0.6429 |
| 0.4424 | 9.8214 | 550 | 1.3828 | 0.6404 |
| 0.4206 | 10.2679 | 575 | 1.3888 | 0.6371 |
| 0.3735 | 10.7143 | 600 | 1.3807 | 0.6449 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0