Whisper tiny Hi - v1
This model is a fine-tuned version of openai/whisper-tiny on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.5045
- Wer: 56.2682
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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.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: 500
- training_steps: 2500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.4841 | 1.1236 | 500 | 0.6430 | 68.6439 |
| 0.3069 | 2.2472 | 1000 | 0.5336 | 61.4432 |
| 0.2537 | 3.3708 | 1500 | 0.5145 | 58.1104 |
| 0.2111 | 4.4944 | 2000 | 0.5054 | 56.4325 |
| 0.191 | 5.6180 | 2500 | 0.5045 | 56.2682 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.1
- Tokenizers 0.21.0