---
language:
- tw
license: mit
base_model: microsoft/speecht5_tts
tags:
- GhanaNLP
- generated_from_trainer
datasets:
- lagyamfi/Akan_Twi_Bible
model-index:
- name: SpeechT5 TTS Twi_v6
  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 Twi_v6

This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the lagyamfi/Akan dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3921

## 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: 0.0001
- train_batch_size: 40
- eval_batch_size: 40
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 80
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 269  | 0.4005          |
| 0.433         | 2.0   | 538  | 0.3988          |
| 0.433         | 3.0   | 807  | 0.4027          |
| 0.4353        | 4.0   | 1076 | 0.4052          |
| 0.4353        | 5.0   | 1345 | 0.4040          |
| 0.4356        | 6.0   | 1614 | 0.3986          |
| 0.4356        | 7.0   | 1883 | 0.3979          |
| 0.4314        | 8.0   | 2152 | 0.3988          |
| 0.4314        | 9.0   | 2421 | 0.3967          |
| 0.4283        | 10.0  | 2690 | 0.3960          |
| 0.4283        | 11.0  | 2959 | 0.3956          |
| 0.4221        | 12.0  | 3228 | 0.3945          |
| 0.4221        | 13.0  | 3497 | 0.3942          |
| 0.4185        | 14.0  | 3766 | 0.3943          |
| 0.4161        | 15.0  | 4035 | 0.3933          |
| 0.4161        | 16.0  | 4304 | 0.3950          |
| 0.4193        | 17.0  | 4573 | 0.3971          |
| 0.4193        | 18.0  | 4842 | 0.3952          |
| 0.4171        | 19.0  | 5111 | 0.3942          |
| 0.4171        | 20.0  | 5380 | 0.3937          |
| 0.4146        | 21.0  | 5649 | 0.3949          |
| 0.4146        | 22.0  | 5918 | 0.3948          |
| 0.4126        | 23.0  | 6187 | 0.3920          |
| 0.4126        | 24.0  | 6456 | 0.3920          |
| 0.41          | 25.0  | 6725 | 0.3953          |
| 0.41          | 26.0  | 6994 | 0.3927          |
| 0.4091        | 27.0  | 7263 | 0.3922          |
| 0.4065        | 28.0  | 7532 | 0.3910          |
| 0.4065        | 29.0  | 7801 | 0.3930          |
| 0.4057        | 30.0  | 8070 | 0.3921          |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1