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---
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 |