|
--- |
|
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 |
|
|
