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

Framework versions

• Transformers 4.49.0.dev0
• Pytorch 2.5.1+cu121
• Datasets 3.2.0
• Tokenizers 0.21.0