---
language:
- sk
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
datasets:
- facebook/voxpopuli
model-index:
- name: SpeechT5 TTS Slovak v3
  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 Slovak v3

This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the VoxPopuli dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4046

## 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: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step  | Validation Loss |
|:-------------:|:-------:|:-----:|:---------------:|
| 0.5259        | 3.2258  | 500   | 0.4625          |
| 0.4823        | 6.4516  | 1000  | 0.4345          |
| 0.4702        | 9.6774  | 1500  | 0.4258          |
| 0.4502        | 12.9032 | 2000  | 0.4189          |
| 0.4579        | 16.1290 | 2500  | 0.4173          |
| 0.4418        | 19.3548 | 3000  | 0.4134          |
| 0.448         | 22.5806 | 3500  | 0.4117          |
| 0.4467        | 25.8065 | 4000  | 0.4094          |
| 0.4388        | 29.0323 | 4500  | 0.4084          |
| 0.4327        | 32.2581 | 5000  | 0.4071          |
| 0.4398        | 35.4839 | 5500  | 0.4069          |
| 0.4381        | 38.7097 | 6000  | 0.4065          |
| 0.4357        | 41.9355 | 6500  | 0.4053          |
| 0.4352        | 45.1613 | 7000  | 0.4059          |
| 0.4298        | 48.3871 | 7500  | 0.4050          |
| 0.4293        | 51.6129 | 8000  | 0.4043          |
| 0.4342        | 54.8387 | 8500  | 0.4050          |
| 0.4309        | 58.0645 | 9000  | 0.4045          |
| 0.4277        | 61.2903 | 9500  | 0.4047          |
| 0.4319        | 64.5161 | 10000 | 0.4046          |


### Framework versions

- Transformers 4.42.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1