Whisper Small Pulaar
This model is a fine-tuned version of openai/whisper-small on the ASR Pulaar Dataset dataset. It achieves the following results on the evaluation set:
- Loss: 1.1167
- Wer: 120.9982
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: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.9523 | 1.0373 | 1000 | 1.2430 | 132.9187 |
| 0.649 | 2.0747 | 2000 | 1.1308 | 113.6540 |
| 0.5278 | 3.1120 | 3000 | 1.1119 | 113.9935 |
| 0.4196 | 4.1494 | 4000 | 1.1167 | 120.9982 |
Framework versions
- Transformers 4.50.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.2