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speecht5_finetuned_voxpopuli_hr
derek-thomas/speecht5_finetuned_voxpopuli_hr
speecht5_finetuned_voxpopuli_hr is a text-to-speech model from derek-thomas. 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
- Jan 2, 2024
- Updated
- Jan 3, 2024
- SHA
- ff905a35
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_it
This model is a fine-tuned version of microsoft/speecht5_tts on the voxpopuli/it dataset. It achieves the following results on the evaluation set:
- Loss: 0.4497
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: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.4773 | 32.52 | 1000 | 0.4502 |
| 0.4545 | 65.04 | 2000 | 0.4462 |
| 0.4488 | 97.56 | 3000 | 0.4502 |
| 0.4517 | 130.08 | 4000 | 0.4497 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
- Task
- Text-to-Speech
- Library
- transformers
- Type
- speecht5
- License
- mit
- Languages
- hr
- Created
- Jan 2, 2024
- Updated
- Jan 3, 2024