---
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: urdu_text_to_speech_tts
  results: []
datasets:
- mozilla-foundation/common_voice_17_0
language:
- ur
metrics:
- accuracy
pipeline_tag: text-to-speech
---

<!-- 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_text_to_speech_tts

This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co./microsoft/speecht5_tts) on an common_voice_17_0 urdu dataset with very small amount. It's trained using only 4200 sentences, for business use model need to be trained on large datasets.
It achieves the following results on the evaluation set:
- Loss: 0.4936

## 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: 8
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.6365        | 1.0   | 486  | 0.5707          |
| 0.6045        | 2.0   | 972  | 0.5319          |
| 0.591         | 3.0   | 1458 | 0.5265          |
| 0.5711        | 4.0   | 1944 | 0.5178          |
| 0.5528        | 5.0   | 2430 | 0.5142          |
| 0.5335        | 6.0   | 2916 | 0.5073          |
| 0.5316        | 7.0   | 3402 | 0.5015          |
| 0.5308        | 8.0   | 3888 | 0.4992          |
| 0.5381        | 9.0   | 4374 | 0.5022          |
| 0.5292        | 10.0  | 4860 | 0.4977          |
| 0.5242        | 11.0  | 5346 | 0.4975          |
| 0.5129        | 12.0  | 5832 | 0.4970          |
| 0.5122        | 13.0  | 6318 | 0.4937          |
| 0.5329        | 14.0  | 6804 | 0.4943          |
| 0.5189        | 15.0  | 7290 | 0.4921          |
| 0.5164        | 16.0  | 7776 | 0.4946          |
| 0.5097        | 17.0  | 8262 | 0.4931          |
| 0.5858        | 18.0  | 8748 | 0.4948          |
| 0.5128        | 19.0  | 9234 | 0.4936          |
| 0.5203        | 20.0  | 9720 | 0.4936          |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1