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: 0.4370
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: 6
- eval_batch_size: 6
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 12
- 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: 500
- training_steps: 6000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.5354 | 0.1339 | 500 | 0.4752 |
| 0.5157 | 0.2679 | 1000 | 0.4604 |
| 0.5028 | 0.4018 | 1500 | 0.4537 |
| 0.4872 | 0.5358 | 2000 | 0.4489 |
| 0.4892 | 0.6697 | 2500 | 0.4453 |
| 0.4813 | 0.8036 | 3000 | 0.4436 |
| 0.483 | 0.9376 | 3500 | 0.4421 |
| 0.4763 | 1.0715 | 4000 | 0.4401 |
| 0.4786 | 1.2055 | 4500 | 0.4400 |
| 0.481 | 1.3394 | 5000 | 0.4379 |
| 0.4811 | 1.4733 | 5500 | 0.4393 |
| 0.4846 | 1.6073 | 6000 | 0.4370 |
Framework versions
- Transformers 4.48.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0