Whisper Medium Ur - Jalandhary ASR Fine-Tuned
This model is a fine-tuned version of GogetaBlueMUI/whisper-medium-ur-jalandhary on the Jalandhary ASR dataset. It achieves the following results on the evaluation set:
- Loss: 0.1012
- Wer: 19.8078
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-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- 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: 300
- training_steps: 2400
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1097 | 0.5831 | 600 | 0.1066 | 18.6509 |
| 0.0664 | 1.1662 | 1200 | 0.1020 | 19.1575 |
| 0.0821 | 1.7493 | 1800 | 0.1016 | 19.2725 |
| 0.0567 | 2.3324 | 2400 | 0.1012 | 19.8078 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.2
- Tokenizers 0.21.0
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