---
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
datasets:
- m-aliabbas/common_voice_urdu1
model-index:
- name: SpeechT5 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. -->

# SpeechT5 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: 0.4796

## Model description

trianed using roman urdu, using a transliteration function normal urdu was  mapped to roman urdu. 

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- 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 |
|:-------------:|:-------:|:-----:|:---------------:|
| 0.5782        | 4.3103  | 500   | 0.5071          |
| 0.5248        | 8.6207  | 1000  | 0.4863          |
| 0.5125        | 12.9310 | 1500  | 0.4746          |
| 0.5081        | 17.2414 | 2000  | 0.4727          |
| 0.4967        | 21.5517 | 2500  | 0.4683          |
| 0.4905        | 25.8621 | 3000  | 0.4645          |
| 0.4794        | 30.1724 | 3500  | 0.4668          |
| 0.4829        | 34.4828 | 4000  | 0.4647          |
| 0.477         | 38.7931 | 4500  | 0.4645          |
| 0.4637        | 43.1034 | 5000  | 0.4710          |
| 0.4743        | 47.4138 | 5500  | 0.4683          |
| 0.4595        | 51.7241 | 6000  | 0.4695          |
| 0.4735        | 56.0345 | 6500  | 0.4684          |
| 0.4613        | 60.3448 | 7000  | 0.4724          |
| 0.4678        | 64.6552 | 7500  | 0.4732          |
| 0.4538        | 68.9655 | 8000  | 0.4723          |
| 0.4536        | 73.2759 | 8500  | 0.4747          |
| 0.4587        | 77.5862 | 9000  | 0.4740          |
| 0.4536        | 81.8966 | 9500  | 0.4762          |
| 0.4606        | 86.2069 | 10000 | 0.4768          |
| 0.4528        | 90.5172 | 10500 | 0.4796          |


### Framework versions

- Transformers 4.43.0.dev0
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1