SpeechT5 TTS Igb0 Yoruba
This model is a fine-tuned version of microsoft/speecht5_tts on the naija_tts_concatenated dataset. It achieves the following results on the evaluation set:
- Loss: 0.4441
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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- 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 |
|---|---|---|---|
| 1.5732 | 0.1576 | 100 | 0.7186 |
| 1.4622 | 0.3152 | 200 | 0.6618 |
| 1.3725 | 0.4728 | 300 | 0.5930 |
| 1.19 | 0.6304 | 400 | 0.5175 |
| 1.1514 | 0.7880 | 500 | 0.5009 |
| 1.0837 | 0.9456 | 600 | 0.4875 |
| 1.0747 | 1.1024 | 700 | 0.4842 |
| 1.102 | 1.2600 | 800 | 0.4790 |
| 1.0613 | 1.4177 | 900 | 0.4723 |
| 1.0619 | 1.5753 | 1000 | 0.4685 |
| 1.0256 | 1.7329 | 1100 | 0.4646 |
| 1.0282 | 1.8905 | 1200 | 0.4637 |
| 1.0212 | 2.0473 | 1300 | 0.4633 |
| 1.001 | 2.2049 | 1400 | 0.4606 |
| 1.0224 | 2.3625 | 1500 | 0.4573 |
| 0.9996 | 2.5201 | 1600 | 0.4551 |
| 0.9838 | 2.6777 | 1700 | 0.4553 |
| 0.978 | 2.8353 | 1800 | 0.4547 |
| 0.9915 | 2.9929 | 1900 | 0.4525 |
| 0.9887 | 3.1497 | 2000 | 0.4526 |
| 1.0082 | 3.3073 | 2100 | 0.4523 |
| 0.9833 | 3.4649 | 2200 | 0.4485 |
| 0.9776 | 3.6225 | 2300 | 0.4484 |
| 0.9854 | 3.7801 | 2400 | 0.4492 |
| 0.9959 | 3.9377 | 2500 | 0.4493 |
| 0.9612 | 4.0946 | 2600 | 0.4467 |
| 0.9797 | 4.2522 | 2700 | 0.4467 |
| 0.9482 | 4.4098 | 2800 | 0.4458 |
| 0.9651 | 4.5674 | 2900 | 0.4443 |
| 0.9519 | 4.7250 | 3000 | 0.4455 |
| 0.9695 | 4.8826 | 3100 | 0.4446 |
| 0.9726 | 5.0394 | 3200 | 0.4439 |
| 0.9644 | 5.1970 | 3300 | 0.4454 |
| 0.9719 | 5.3546 | 3400 | 0.4440 |
| 0.9711 | 5.5122 | 3500 | 0.4437 |
| 0.9367 | 5.6698 | 3600 | 0.4437 |
| 0.961 | 5.8274 | 3700 | 0.4424 |
| 0.9524 | 5.9850 | 3800 | 0.4435 |
| 0.9732 | 6.1418 | 3900 | 0.4432 |
| 0.9854 | 6.2994 | 4000 | 0.4441 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0