---
tags:
- generated_from_trainer
model-index:
- name: speecht5_tts_common_voice_uk
  results: []
widget:
- text: >-
    Держава-агресор росія закуповує комунікаційне обладнання, зокрема
    супутникові інтернет-термінали Starlink, для використання у війні в
    арабських країнах
license: mit
datasets:
- mozilla-foundation/common_voice_16_1
language:
- uk
pipeline_tag: text-to-speech
---

<!-- 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_common_voice_uk

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4015

## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.4646        | 1.0   | 146  | 0.4160          |
| 0.468         | 2.0   | 292  | 0.4173          |
| 0.4623        | 3.0   | 438  | 0.4177          |
| 0.4637        | 4.0   | 584  | 0.4116          |
| 0.4584        | 5.0   | 730  | 0.4074          |
| 0.4525        | 6.0   | 876  | 0.4074          |
| 0.4438        | 7.0   | 1022 | 0.4054          |
| 0.4433        | 8.0   | 1168 | 0.4020          |
| 0.4401        | 9.0   | 1314 | 0.4018          |
| 0.4401        | 10.0  | 1460 | 0.4015          |


### Framework versions

- Transformers 4.37.2
- Pytorch 1.12.1+cu116
- Datasets 2.4.0
- Tokenizers 0.15.2