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--- |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: speecht5_tts_common_voice_uk |
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results: [] |
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widget: |
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- text: >- |
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Держава-агресор росія закуповує комунікаційне обладнання, зокрема |
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супутникові інтернет-термінали Starlink, для використання у війні в |
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арабських країнах |
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license: mit |
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datasets: |
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- mozilla-foundation/common_voice_16_1 |
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language: |
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- uk |
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pipeline_tag: text-to-speech |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# speecht5_tts_common_voice_uk |
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This model was trained from scratch on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4015 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 10 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 0.4646 | 1.0 | 146 | 0.4160 | |
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| 0.468 | 2.0 | 292 | 0.4173 | |
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| 0.4623 | 3.0 | 438 | 0.4177 | |
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| 0.4637 | 4.0 | 584 | 0.4116 | |
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| 0.4584 | 5.0 | 730 | 0.4074 | |
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| 0.4525 | 6.0 | 876 | 0.4074 | |
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| 0.4438 | 7.0 | 1022 | 0.4054 | |
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| 0.4433 | 8.0 | 1168 | 0.4020 | |
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| 0.4401 | 9.0 | 1314 | 0.4018 | |
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| 0.4401 | 10.0 | 1460 | 0.4015 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 1.12.1+cu116 |
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- Datasets 2.4.0 |
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- Tokenizers 0.15.2 |
