---
library_name: transformers
language:
- yo
license: mit
base_model: microsoft/speecht5_tts
tags:
- Nigeria
- generated_from_trainer
datasets:
- ccibeekeoc42/naija_tts_concatenated
model-index:
- name: SpeechT5 TTS Igb0 Yoruba
  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 Igb0 Yoruba

This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/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