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speecht5_finetuned_voxpopuli_es
sfedar/speecht5_finetuned_voxpopuli_es
speecht5_finetuned_voxpopuli_es is a text-to-speech model from sfedar. 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
- Sep 11, 2024
- Updated
- Sep 11, 2024
- SHA
- 9274d779
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. -->
speecht5_finetuned_voxpopuli_es
This model is a fine-tuned version of microsoft/speecht5_tts on the voxpopuli dataset. It achieves the following results on the evaluation set:
- Loss: 0.4625
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: 2
- 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: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.5118 | 2.3419 | 250 | 0.4745 |
| 0.501 | 4.6838 | 500 | 0.4680 |
| 0.4988 | 7.0258 | 750 | 0.4645 |
| 0.4945 | 9.3677 | 1000 | 0.4625 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Tokenizers 0.19.1
- Task
- Text-to-Speech
- Library
- transformers
- Type
- speecht5
- License
- mit
- Created
- Sep 11, 2024
- Updated
- Sep 11, 2024