---
language:
- es
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
datasets:
- facebook/voxpopuli
model-index:
- name: speec T5 ES - Sumet
  results: []
pipeline_tag: text-to-speech
---

<!-- 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. -->

# speec T5 ES - Sumet

This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co./microsoft/speecht5_tts) on the Vox Populi ES dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.4434
- eval_runtime: 126.5506
- eval_samples_per_second: 19.802
- eval_steps_per_second: 4.955
- epoch: 3.41
- step: 2400

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- 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: 4000

### Framework versions

- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3