---
language:
- en
license: mit
base_model: microsoft/speecht5_tts
tags:
- .
- generated_from_trainer
datasets:
- speecht5_imda_nsc_p1
model-index:
- name: Speech T5 TTS English
  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. -->

# Speech T5 TTS English

This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the IMDA National Speech Corpus dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3968

## 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: 32
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.4693        | 0.91  | 1000  | 0.4240          |
| 0.4524        | 1.82  | 2000  | 0.4132          |
| 0.4405        | 2.72  | 3000  | 0.4079          |
| 0.4416        | 3.63  | 4000  | 0.4056          |
| 0.4298        | 4.54  | 5000  | 0.4009          |
| 0.4363        | 5.45  | 6000  | 0.4002          |
| 0.4301        | 6.35  | 7000  | 0.3989          |
| 0.4376        | 7.26  | 8000  | 0.3978          |
| 0.4308        | 8.17  | 9000  | 0.3984          |
| 0.4363        | 9.08  | 10000 | 0.3971          |
| 0.4341        | 9.99  | 11000 | 0.3968          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0