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---
library_name: transformers
language:
- twi
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
datasets:
- fsicoli/twi
model-index:
- name: SpeechT5 TTS Npontu Twi
results: []
---
<!-- 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 TTS Npontu Twi
This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/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
|