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speecht5_finetuned_voxpopuli_de
ahk-d/speecht5_finetuned_voxpopuli_de
speecht5_finetuned_voxpopuli_de is a text-to-speech model from ahk-d. 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
- Nov 16, 2024
- Updated
- Nov 16, 2024
- SHA
- ccc01ea7
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_de
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: 0.4708
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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.5265 | 11.6110 | 1000 | 0.4860 |
| 0.5029 | 23.2221 | 2000 | 0.4740 |
| 0.4984 | 34.8331 | 3000 | 0.4721 |
| 0.4965 | 46.4441 | 4000 | 0.4708 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
- Task
- Text-to-Speech
- Library
- transformers
- Type
- speecht5
- License
- mit
- Created
- Nov 16, 2024
- Updated
- Nov 16, 2024