whisper-tiny-minds14-enUS
This model is a fine-tuned version of openai/whisper-tiny on the PolyAI/minds14 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4681
- Wer: 0.3634
- Wer Ortho: 0.3504
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Wer Ortho |
|---|---|---|---|---|---|
| 6.0096 | 1.0 | 29 | 1.9128 | 0.4941 | 0.3942 |
| 1.3392 | 2.0 | 58 | 0.5142 | 0.3961 | 0.3806 |
| 0.6757 | 3.0 | 87 | 0.4752 | 0.3732 | 0.3566 |
| 0.5135 | 4.0 | 116 | 0.4672 | 0.3775 | 0.3652 |
| 0.4573 | 5.0 | 145 | 0.4681 | 0.3634 | 0.3504 |
Framework versions
- Transformers 5.16.1
- Pytorch 2.11.0+cu128
- Datasets 5.0.1
- Tokenizers 0.23.1