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---
library_name: transformers
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
datasets:
- m-aliabbas/common_voice_urdu1
model-index:
- name: TTS urdu
results: []
---
<!-- 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. -->
# TTS urdu
This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the common_voice_urdu1 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4753
## 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
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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: 10500
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-------:|:-----:|:---------------:|
| 0.5698 | 4.3103 | 500 | 0.5020 |
| 0.528 | 8.6207 | 1000 | 0.4814 |
| 0.5092 | 12.9310 | 1500 | 0.4693 |
| 0.502 | 17.2414 | 2000 | 0.4720 |
| 0.4944 | 21.5517 | 2500 | 0.4665 |
| 0.4922 | 25.8621 | 3000 | 0.4635 |
| 0.4793 | 30.1724 | 3500 | 0.4653 |
| 0.4851 | 34.4828 | 4000 | 0.4684 |
| 0.4726 | 38.7931 | 4500 | 0.4651 |
| 0.4614 | 43.1034 | 5000 | 0.4660 |
| 0.4734 | 47.4138 | 5500 | 0.4652 |
| 0.4621 | 51.7241 | 6000 | 0.4688 |
| 0.4689 | 56.0345 | 6500 | 0.4730 |
| 0.4589 | 60.3448 | 7000 | 0.4663 |
| 0.4658 | 64.6552 | 7500 | 0.4725 |
| 0.4552 | 68.9655 | 8000 | 0.4742 |
| 0.4549 | 73.2759 | 8500 | 0.4763 |
| 0.4599 | 77.5862 | 9000 | 0.4726 |
| 0.4559 | 81.8966 | 9500 | 0.4738 |
| 0.4605 | 86.2069 | 10000 | 0.4764 |
| 0.4482 | 90.5172 | 10500 | 0.4753 |
### Framework versions
- Transformers 4.46.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0
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