---
language:
- en
license: mit
base_model: microsoft/speecht5_tts
tags:
- Trinidadian TTS
- generated_from_trainer
datasets:
- MK_TandT
model-index:
- name: SpeechT5_Trini_female_6000
  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_Trini_female_6000

This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the TandT dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3725

## 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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 6000

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.4357        | 4.78  | 1000 | 0.3908          |
| 0.4196        | 9.57  | 2000 | 0.3805          |
| 0.4029        | 14.35 | 3000 | 0.3749          |
| 0.4041        | 19.14 | 4000 | 0.3745          |
| 0.3916        | 23.92 | 5000 | 0.3727          |
| 0.3966        | 28.71 | 6000 | 0.3725          |


### Framework versions

- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3