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speecht5_mahinda_work1
kavinda123321/speecht5_mahinda_work1
speecht5_mahinda_work1 is a text-to-audio model from kavinda123321. Use it for the text-to-audio task on the model card, and read the license before you ship it in a product. 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-Audio
- Library
- transformers
- License
- mit
- Model type
- speecht5
- Access
- Public
- Created
- May 31, 2025
- Updated
- May 31, 2025
- SHA
- 945590a6
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_mahinda_work1
This model is a fine-tuned version of kavinda123321/speecht5_mahinda_work1 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5641
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: 0.0001
- train_batch_size: 4
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.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: 100
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.3723 | 1.0 | 4 | 0.5814 |
| 0.36 | 2.0 | 8 | 0.5864 |
| 0.3733 | 3.0 | 12 | 0.6023 |
| 0.3594 | 4.0 | 16 | 0.5922 |
| 0.3623 | 5.0 | 20 | 0.5641 |
Framework versions
- Transformers 4.52.2
- Pytorch 2.6.0+cu124
- Datasets 2.14.4
- Tokenizers 0.21.1
- Task
- Text-to-Audio
- Library
- transformers
- Type
- speecht5
- License
- mit
- Created
- May 31, 2025
- Updated
- May 31, 2025