---
language:
- pt
license: mit
base_model: microsoft/speecht5_tts
tags:
- text-to-speech
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
model-index:
- name: speecht5_pt_full
  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_pt_full

This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the mozilla-foundation/common_voice_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5021

> *DISCLAIMER*: This model is trained for the sole purpose of finishing the HuggingFace [Audio course](https://huggingface.co/learn/audio-course/chapter0/introduction). It doesn't have any usability and outputs pure noise. If you have an idea of how to improve the model, feel free to create a post in the Community tab of this model. Thank you!

## 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: 4
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- 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: 2000

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.8882        | 0.18  | 100  | 0.7494          |
| 0.7726        | 0.36  | 200  | 0.6657          |
| 0.642         | 0.54  | 300  | 0.5767          |
| 0.6042        | 0.71  | 400  | 0.5545          |
| 0.5972        | 0.89  | 500  | 0.5342          |
| 0.5832        | 1.07  | 600  | 0.5337          |
| 0.5851        | 1.25  | 700  | 0.5291          |
| 0.5744        | 1.43  | 800  | 0.5245          |
| 0.5638        | 1.61  | 900  | 0.5186          |
| 0.5562        | 1.78  | 1000 | 0.5174          |
| 0.56          | 1.96  | 1100 | 0.5133          |
| 0.5446        | 2.14  | 1200 | 0.5113          |
| 0.5556        | 2.32  | 1300 | 0.5099          |
| 0.5457        | 2.5   | 1400 | 0.5071          |
| 0.5504        | 2.68  | 1500 | 0.5087          |
| 0.5497        | 2.85  | 1600 | 0.5039          |
| 0.545         | 3.03  | 1700 | 0.5034          |
| 0.5503        | 3.21  | 1800 | 0.5051          |
| 0.5621        | 3.39  | 1900 | 0.5040          |
| 0.5347        | 3.57  | 2000 | 0.5021          |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1