---
library_name: transformers
license: mit
base_model: Sana1207/Hindi_SpeechT5_finetuned
tags:
- generated_from_trainer
model-index:
- name: Sindhi-TTS
  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. -->

# Sindhi-TTS

This model is a fine-tuned version of [Sana1207/Hindi_SpeechT5_finetuned](https://huggingface.co/Sana1207/Hindi_SpeechT5_finetuned) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4887

## 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: 0.0001
- train_batch_size: 16
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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: 100
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 0.5769        | 0.3992  | 100  | 0.5673          |
| 0.5602        | 0.7984  | 200  | 0.5603          |
| 0.553         | 1.1986  | 300  | 0.5489          |
| 0.5413        | 1.5978  | 400  | 0.5433          |
| 0.5361        | 1.9970  | 500  | 0.5336          |
| 0.5391        | 2.3972  | 600  | 0.5414          |
| 0.524         | 2.7964  | 700  | 0.5290          |
| 0.5253        | 3.1966  | 800  | 0.5317          |
| 0.5272        | 3.5958  | 900  | 0.5234          |
| 0.5258        | 3.9950  | 1000 | 0.5280          |
| 0.5173        | 4.3952  | 1100 | 0.5180          |
| 0.518         | 4.7944  | 1200 | 0.5207          |
| 0.5119        | 5.1946  | 1300 | 0.5157          |
| 0.5114        | 5.5938  | 1400 | 0.5169          |
| 0.5138        | 5.9930  | 1500 | 0.5140          |
| 0.5048        | 6.3932  | 1600 | 0.5122          |
| 0.5059        | 6.7924  | 1700 | 0.5173          |
| 0.4991        | 7.1926  | 1800 | 0.5057          |
| 0.5038        | 7.5918  | 1900 | 0.5053          |
| 0.4994        | 7.9910  | 2000 | 0.5071          |
| 0.4989        | 8.3912  | 2100 | 0.5080          |
| 0.4951        | 8.7904  | 2200 | 0.5099          |
| 0.4941        | 9.1906  | 2300 | 0.5022          |
| 0.493         | 9.5898  | 2400 | 0.5039          |
| 0.4915        | 9.9890  | 2500 | 0.5014          |
| 0.4911        | 10.3892 | 2600 | 0.5066          |
| 0.4861        | 10.7884 | 2700 | 0.4987          |
| 0.4875        | 11.1886 | 2800 | 0.5042          |
| 0.4892        | 11.5878 | 2900 | 0.4980          |
| 0.4909        | 11.9870 | 3000 | 0.5007          |
| 0.4886        | 12.3872 | 3100 | 0.4980          |
| 0.4857        | 12.7864 | 3200 | 0.4952          |
| 0.4868        | 13.1866 | 3300 | 0.4972          |
| 0.482         | 13.5858 | 3400 | 0.4957          |
| 0.479         | 13.9850 | 3500 | 0.5029          |
| 0.48          | 14.3852 | 3600 | 0.4954          |
| 0.4819        | 14.7844 | 3700 | 0.4982          |
| 0.4791        | 15.1846 | 3800 | 0.4936          |
| 0.4776        | 15.5838 | 3900 | 0.4947          |
| 0.4736        | 15.9830 | 4000 | 0.4930          |
| 0.4744        | 16.3832 | 4100 | 0.4937          |
| 0.4735        | 16.7824 | 4200 | 0.4895          |
| 0.4789        | 17.1826 | 4300 | 0.4936          |
| 0.4729        | 17.5818 | 4400 | 0.4920          |
| 0.4742        | 17.9810 | 4500 | 0.4915          |
| 0.4721        | 18.3812 | 4600 | 0.4887          |
| 0.4733        | 18.7804 | 4700 | 0.4933          |
| 0.4849        | 19.1806 | 4800 | 0.4879          |
| 0.4692        | 19.5798 | 4900 | 0.4889          |
| 0.4747        | 19.9790 | 5000 | 0.4887          |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3