throatmic_subvocalization_whisper
This model is a fine-tuned version of openai/whisper-large-v3 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5656
- Wer: 0.2044
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 |
|---|---|---|---|---|
| 3.7651 | 0.4464 | 25 | 2.5976 | 0.5201 |
| 2.0527 | 0.8929 | 50 | 1.5234 | 0.3053 |
| 0.7656 | 1.3393 | 75 | 0.5719 | 0.2620 |
| 0.3496 | 1.7857 | 100 | 0.4706 | 0.2322 |
| 0.2532 | 2.2321 | 125 | 0.4426 | 0.2199 |
| 0.1385 | 2.6786 | 150 | 0.4657 | 0.2290 |
| 0.1041 | 3.125 | 175 | 0.4639 | 0.2096 |
| 0.0541 | 3.5714 | 200 | 0.4846 | 0.2083 |
| 0.0453 | 4.0179 | 225 | 0.4711 | 0.1973 |
| 0.0182 | 4.4643 | 250 | 0.5187 | 0.2154 |
| 0.0257 | 4.9107 | 275 | 0.5158 | 0.2128 |
| 0.0113 | 5.3571 | 300 | 0.5966 | 0.2141 |
| 0.0067 | 5.8036 | 325 | 0.5647 | 0.2109 |
| 0.0086 | 6.25 | 350 | 0.5656 | 0.2044 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0