---
language:
- sd
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
datasets:
- facebook/voxpopuli
model-index:
- name: SpeechT5 TTS sindhi
  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 sindhi

This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the google/fleurs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3386

## 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: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.3716        | 0.2703 | 50   | 0.3473          |
| 0.3764        | 0.5405 | 100  | 0.3442          |
| 0.3736        | 0.8108 | 150  | 0.3438          |
| 0.3707        | 1.0811 | 200  | 0.3438          |
| 0.3736        | 1.3514 | 250  | 0.3427          |
| 0.3717        | 1.6216 | 300  | 0.3414          |
| 0.3614        | 1.8919 | 350  | 0.3401          |
| 0.3641        | 2.1622 | 400  | 0.3393          |
| 0.3679        | 2.4324 | 450  | 0.3394          |
| 0.3644        | 2.7027 | 500  | 0.3386          |


### Framework versions

- Transformers 4.45.0.dev0
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1