---
language:
- en
license: mit
base_model: microsoft/speecht5_tts
tags:
- TTS,
- generated_from_trainer
datasets:
- lj_speech
model-index:
- name: SpeechT5 TTS LJ_Speech
  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 LJ_Speech

This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the lj_speech dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3659

## 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: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step  | Validation Loss |
|:-------------:|:-------:|:-----:|:---------------:|
| 0.4059        | 2.7137  | 1000  | 0.3729          |
| 0.3927        | 5.4274  | 2000  | 0.3707          |
| 0.3982        | 8.1411  | 3000  | 0.3696          |
| 0.4006        | 10.8548 | 4000  | 0.3682          |
| 0.3869        | 13.5685 | 5000  | 0.3669          |
| 0.395         | 16.2822 | 6000  | 0.3669          |
| 0.4012        | 18.9959 | 7000  | 0.3666          |
| 0.3858        | 21.7096 | 8000  | 0.3662          |
| 0.3864        | 24.4233 | 9000  | 0.3658          |
| 0.3982        | 27.1370 | 10000 | 0.3659          |


### Framework versions

- Transformers 4.41.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1