---
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