Whisper Small
This model is a fine-tuned version of openai/whisper-small on the Speechocean762_CMUkids_Myst dataset. It achieves the following results on the evaluation set:
- Loss: 0.4057
- Wer: 18.0848
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: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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: 2048
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 5.2459 | 1.6734 | 500 | 3.0174 | 17.7129 |
| 3.2713 | 3.3451 | 1000 | 1.8842 | 17.5214 |
| 1.7679 | 5.0168 | 1500 | 1.0173 | 17.6885 |
| 0.8126 | 6.6901 | 2000 | 0.4594 | 18.5570 |
| 0.6499 | 8.3618 | 2500 | 0.4213 | 19.0870 |
| 0.6065 | 10.0335 | 3000 | 0.4108 | 18.5881 |
| 0.5906 | 11.7069 | 3500 | 0.4070 | 17.6083 |
| 0.5759 | 13.3786 | 4000 | 0.4057 | 18.0848 |
Framework versions
- Transformers 5.8.1
- Pytorch 2.5.1+cu121
- Datasets 4.8.5
- Tokenizers 0.22.2