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speecht5_finetuned_voxpopuli_et
Terps/speecht5_finetuned_voxpopuli_et
speecht5_finetuned_voxpopuli_et is a text-to-speech model from Terps. 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
- Oct 9, 2023
- Updated
- Oct 10, 2023
- SHA
- 88497af4
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_et
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: 0.4735
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
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.4603 | 105.26 | 1000 | 0.4698 |
| 0.4375 | 210.53 | 2000 | 0.4742 |
| 0.4264 | 315.79 | 3000 | 0.4737 |
| 0.4226 | 421.05 | 4000 | 0.4735 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
- Task
- Text-to-Speech
- Library
- transformers
- Type
- speecht5
- License
- mit
- Created
- Oct 9, 2023
- Updated
- Oct 10, 2023