throatmic_subvocalization_whisper_small
This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8621
- Wer: 0.3855
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 |
|---|---|---|---|---|
| 5.1486 | 0.4464 | 25 | 3.9859 | 0.8564 |
| 3.0886 | 0.8929 | 50 | 2.1745 | 0.7057 |
| 1.7689 | 1.3393 | 75 | 1.7727 | 0.4748 |
| 1.4945 | 1.7857 | 100 | 1.5883 | 0.4243 |
| 1.3174 | 2.2321 | 125 | 1.4747 | 0.3946 |
| 1.082 | 2.6786 | 150 | 1.4101 | 0.3816 |
| 0.967 | 3.125 | 175 | 1.3374 | 0.3797 |
| 0.7866 | 3.5714 | 200 | 1.2746 | 0.3700 |
| 0.6628 | 4.0179 | 225 | 1.0417 | 0.3784 |
| 0.2359 | 4.4643 | 250 | 0.7904 | 0.3577 |
| 0.1835 | 4.9107 | 275 | 0.7902 | 0.3571 |
| 0.1051 | 5.3571 | 300 | 0.8173 | 0.3726 |
| 0.1088 | 5.8036 | 325 | 0.8255 | 0.3674 |
| 0.0894 | 6.25 | 350 | 0.8310 | 0.3603 |
| 0.0683 | 6.6964 | 375 | 0.8385 | 0.3726 |
| 0.051 | 7.1429 | 400 | 0.8621 | 0.3855 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0