SpeechT5 TTS Npontu Twi
This model is a fine-tuned version of microsoft/speecht5_tts on the FsicoliTwi dataset. It achieves the following results on the evaluation set:
- Loss: 0.3824
Model description
Npontu Twi is designed to synthesize Twi-language speech with a focus on Ghanaian accents and cultural nuances. Leveraging pure language modeling, Npontu Twi offers high-quality, natural, and culturally relevant speech synthesis for diverse applications, including education, entertainment, and communication in Ghana and beyond.
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 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: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.4207 | 14.4928 | 1000 | 0.3869 |
| 0.41 | 28.9855 | 2000 | 0.3824 |
Framework versions
- Transformers 4.49.0.dev0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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Model tree for chuksDev/speecht5_tts_npontu_twi
Base model
microsoft/speecht5_tts