Punjabi Whisper large-v3 - Swayangjit
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: 0.3908
- Wer: 71.4286
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: 0.0001
- 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: 50
- training_steps: 50
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.4502 | 0.0133 | 10 | 0.6460 | 91.9414 |
| 0.7124 | 0.0266 | 20 | 0.4013 | 72.8205 |
| 0.6185 | 0.0399 | 30 | 0.4096 | 79.7436 |
| 0.5898 | 0.0533 | 40 | 0.4439 | 124.3590 |
| 0.5579 | 0.0666 | 50 | 0.3908 | 71.4286 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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Base model
openai/whisper-large-v3