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speecht5_finetuned_voxpopuli_es
ptah23/speecht5_finetuned_voxpopuli_es
speecht5_finetuned_voxpopuli_es is a text-to-speech model from ptah23. Use it when you need text read aloud. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text-to-Speech
- Library
- transformers
- License
- mit
- Model type
- speecht5
- Access
- Public
- Created
- Jul 12, 2023
- Updated
- Sep 14, 2023
- SHA
- a490e74a
Base models
Datasets
Model card
From the Hugging Face model README
<!-- 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. -->
speec T5 ES - Peter Gelderbloem
This model is a fine-tuned version of microsoft/speecht5_tts on the Vox Populi ES dataset. It achieves the following results on the evaluation set:
- Loss: 0.4400
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: 4
- 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: 500
- training_steps: 4000
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.6709 | 0.14 | 100 | 0.6107 |
| 0.624 | 0.28 | 200 | 0.5773 |
| 0.5921 | 0.43 | 300 | 0.5397 |
| 0.5504 | 0.57 | 400 | 0.4941 |
| 0.5289 | 0.71 | 500 | 0.4807 |
| 0.5236 | 0.85 | 600 | 0.4732 |
| 0.5194 | 0.99 | 700 | 0.4672 |
| 0.5095 | 1.13 | 800 | 0.4650 |
| 0.508 | 1.28 | 900 | 0.4608 |
| 0.5029 | 1.42 | 1000 | 0.4580 |
| 0.5029 | 1.56 | 1100 | 0.4569 |
| 0.4952 | 1.7 | 1200 | 0.4540 |
| 0.4939 | 1.84 | 1300 | 0.4540 |
| 0.4924 | 1.99 | 1400 | 0.4523 |
| 0.4902 | 2.13 | 1500 | 0.4519 |
| 0.492 | 2.27 | 1600 | 0.4491 |
| 0.4896 | 2.41 | 1700 | 0.4497 |
| 0.4874 | 2.55 | 1800 | 0.4482 |
| 0.4889 | 2.7 | 1900 | 0.4473 |
| 0.4888 | 2.84 | 2000 | 0.4471 |
| 0.4902 | 2.98 | 2100 | 0.4461 |
| 0.4818 | 3.12 | 2200 | 0.4457 |
| 0.4854 | 3.26 | 2300 | 0.4451 |
| 0.4886 | 3.4 | 2400 | 0.4429 |
| 0.4799 | 3.55 | 2500 | 0.4429 |
| 0.4806 | 3.69 | 2600 | 0.4429 |
| 0.4777 | 3.83 | 2700 | 0.4416 |
| 0.4787 | 3.98 | 2800 | 0.4423 |
| 0.4823 | 4.12 | 2900 | 0.4419 |
| 0.4822 | 4.26 | 3000 | 0.4409 |
| 0.4796 | 4.4 | 3100 | 0.4404 |
| 0.4805 | 4.54 | 3200 | 0.4418 |
| 0.4795 | 4.69 | 3300 | 0.4409 |
| 0.4784 | 4.83 | 3400 | 0.4411 |
| 0.4812 | 4.97 | 3500 | 0.4406 |
| 0.478 | 5.11 | 3600 | 0.4399 |
| 0.4766 | 5.25 | 3700 | 0.4396 |
| 0.4821 | 5.39 | 3800 | 0.4407 |
| 0.48 | 5.54 | 3900 | 0.4396 |
| 0.4795 | 5.68 | 4000 | 0.4400 |
Framework versions
- Transformers 4.30.2
- Pytorch 1.12.1+cu116
- Datasets 2.4.0
- Tokenizers 0.12.1
- Task
- Text-to-Speech
- Library
- transformers
- Type
- speecht5
- License
- mit
- Languages
- es
- Created
- Jul 12, 2023
- Updated
- Sep 14, 2023