exp_004_base_multistage_urdu
This model is a fine-tuned version of sharjeel103/whisper-base-urdu on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3947
- Wer: 65.7765
- Wer Ortho: 68.6697
- Cer: 21.6281
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: 5e-06
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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: 1000
- training_steps: 10000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Wer Ortho | Cer |
|---|---|---|---|---|---|---|
| 5.0263 | 0.6410 | 500 | 1.5195 | 95.4066 | 95.7445 | 33.6187 |
| 3.5885 | 1.2821 | 1000 | 0.9330 | 89.3228 | 90.2797 | 30.3680 |
| 3.0302 | 1.9231 | 1500 | 0.7431 | 82.6594 | 84.2995 | 27.0128 |
| 2.6802 | 2.5641 | 2000 | 0.6501 | 79.3803 | 81.3448 | 26.0944 |
| 2.4353 | 3.2051 | 2500 | 0.5907 | 76.0507 | 78.3277 | 24.5965 |
| 2.2853 | 3.8462 | 3000 | 0.5492 | 74.3293 | 76.6987 | 24.3492 |
| 2.1399 | 4.4872 | 3500 | 0.5184 | 72.7590 | 75.1236 | 23.5756 |
| 2.0097 | 5.1282 | 4000 | 0.4915 | 70.1810 | 72.8504 | 22.8648 |
| 1.9407 | 5.7692 | 4500 | 0.4697 | 69.6855 | 72.3975 | 22.6328 |
| 1.8625 | 6.4103 | 5000 | 0.4527 | 68.6736 | 71.3502 | 22.4363 |
| 1.7877 | 7.0513 | 5500 | 0.4359 | 68.1740 | 70.8474 | 22.0212 |
| 1.7349 | 7.6923 | 6000 | 0.4235 | 68.3125 | 71.0136 | 22.4257 |
| 1.6679 | 8.3333 | 6500 | 0.4130 | 66.2846 | 69.0105 | 21.4575 |
| 1.6108 | 8.9744 | 7000 | 0.4019 | 66.2804 | 69.1560 | 21.8611 |
| 1.5329 | 9.6154 | 7500 | 0.3947 | 65.7765 | 68.6697 | 21.6281 |
| 1.5234 | 10.2564 | 8000 | 0.3889 | 66.0621 | 68.8651 | 21.4800 |
| 1.5123 | 10.8974 | 8500 | 0.3841 | 66.1796 | 69.0396 | 21.5778 |
| 1.4779 | 11.5385 | 9000 | 0.3809 | 65.9949 | 68.8900 | 21.5524 |
| 1.4631 | 12.1795 | 9500 | 0.3787 | 65.9739 | 68.8277 | 21.4915 |
| 1.4256 | 12.8205 | 10000 | 0.3778 | 65.8857 | 68.7238 | 21.5002 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 3.6.0
- Tokenizers 0.22.2
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