throatmic_subvocalization_whisper_distil-large-v3
This model is a fine-tuned version of distil-whisper/distil-large-v3 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8634
- Wer: 0.3202
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 |
|---|---|---|---|---|
| 4.8931 | 0.4464 | 25 | 3.3920 | 0.7749 |
| 2.3126 | 0.8929 | 50 | 1.2760 | 0.4554 |
| 0.8156 | 1.3393 | 75 | 0.9349 | 0.3648 |
| 0.7011 | 1.7857 | 100 | 0.7822 | 0.3040 |
| 0.5483 | 2.2321 | 125 | 0.7531 | 0.2969 |
| 0.3743 | 2.6786 | 150 | 0.7529 | 0.3525 |
| 0.2984 | 3.125 | 175 | 0.7249 | 0.3402 |
| 0.1953 | 3.5714 | 200 | 0.7531 | 0.3182 |
| 0.1811 | 4.0179 | 225 | 0.7380 | 0.2788 |
| 0.0976 | 4.4643 | 250 | 0.7636 | 0.3234 |
| 0.1152 | 4.9107 | 275 | 0.7868 | 0.2962 |
| 0.0694 | 5.3571 | 300 | 0.8141 | 0.3072 |
| 0.0489 | 5.8036 | 325 | 0.8237 | 0.3279 |
| 0.0459 | 6.25 | 350 | 0.8634 | 0.3202 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0