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urdu-speecht5-finetuned
ahmedjaved812/urdu-speecht5-finetuned
urdu-speecht5-finetuned is a text-to-audio model from ahmedjaved812. Use it for the text-to-audio task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text-to-Audio
- Library
- transformers
- License
- mit
- Model type
- speecht5
- Access
- Public
- Created
- Apr 7, 2026
- Updated
- Apr 9, 2026
- SHA
- 16f92cb7
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
urdu-speecht5-finetuned
This model is a fine-tuned version of microsoft/speecht5_tts on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8700
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: 6
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 4
- total_train_batch_size: 48
- total_eval_batch_size: 4
- 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: 500
- num_epochs: 70
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 4.6416 | 1.5198 | 500 | 1.0342 |
| 4.2408 | 3.0395 | 1000 | 0.9665 |
| 4.0776 | 4.5593 | 1500 | 0.9377 |
| 4.0257 | 6.0790 | 2000 | 0.9284 |
| 3.9388 | 7.5988 | 2500 | 0.9060 |
| 3.8638 | 9.1185 | 3000 | 0.9002 |
| 3.8240 | 10.6383 | 3500 | 0.8884 |
| 3.7701 | 12.1581 | 4000 | 0.8894 |
| 3.7587 | 13.6778 | 4500 | 0.8772 |
| 3.7120 | 15.1976 | 5000 | 0.8787 |
| 3.6871 | 16.7173 | 5500 | 0.8724 |
| 3.6936 | 18.2371 | 6000 | 0.8732 |
| 3.6681 | 19.7568 | 6500 | 0.8782 |
| 3.6397 | 21.2766 | 7000 | 0.8798 |
| 3.6289 | 22.7964 | 7500 | 0.8654 |
| 3.6120 | 24.3161 | 8000 | 0.8669 |
| 3.6059 | 25.8359 | 8500 | 0.8608 |
| 3.5933 | 27.3556 | 9000 | 0.8610 |
| 3.5507 | 28.8754 | 9500 | 0.8674 |
| 3.5522 | 30.3951 | 10000 | 0.8633 |
| 3.5674 | 31.9149 | 10500 | 0.8654 |
| 3.5469 | 33.4347 | 11000 | 0.8605 |
| 3.5538 | 34.9544 | 11500 | 0.8577 |
| 3.5262 | 36.4742 | 12000 | 0.8677 |
| 3.5307 | 37.9939 | 12500 | 0.8621 |
| 3.5248 | 39.5137 | 13000 | 0.8601 |
| 3.5209 | 41.0334 | 13500 | 0.8564 |
| 3.5113 | 42.5532 | 14000 | 0.8597 |
| 3.5083 | 44.0729 | 14500 | 0.8650 |
| 3.5342 | 45.5927 | 15000 | 0.8595 |
| 3.4962 | 47.1125 | 15500 | 0.8660 |
| 3.4923 | 48.6322 | 16000 | 0.8640 |
| 3.4882 | 50.1520 | 16500 | 0.8669 |
| 3.4894 | 51.6717 | 17000 | 0.8677 |
| 3.4748 | 53.1915 | 17500 | 0.8645 |
| 3.4710 | 54.7112 | 18000 | 0.8662 |
| 3.4755 | 56.2310 | 18500 | 0.8673 |
| 3.4795 | 57.7508 | 19000 | 0.8628 |
| 3.4528 | 59.2705 | 19500 | 0.8697 |
| 3.4802 | 60.7903 | 20000 | 0.8746 |
| 3.4582 | 62.3100 | 20500 | 0.8695 |
| 3.4559 | 63.8298 | 21000 | 0.8697 |
| 3.4333 | 65.3495 | 21500 | 0.8690 |
| 3.4699 | 66.8693 | 22000 | 0.8696 |
| 3.4595 | 68.3891 | 22500 | 0.8700 |
| 3.4625 | 69.9088 | 23000 | 0.8700 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.8.3
- Tokenizers 0.22.2
- Task
- Text-to-Audio
- Library
- transformers
- Type
- speecht5
- License
- mit
- Created
- Apr 7, 2026
- Updated
- Apr 9, 2026