---
library_name: transformers
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
datasets:
- voxpopuli
model-index:
- name: speecht5_finetuned_voxpopuli_es
  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_finetuned_voxpopuli_es

This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the voxpopuli dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4743

## 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: 2
- 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: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 0.7149        | 1.1799  | 100  | 0.6094          |
| 0.6526        | 2.3599  | 200  | 0.5722          |
| 0.5987        | 3.5398  | 300  | 0.5286          |
| 0.5604        | 4.7198  | 400  | 0.5086          |
| 0.5468        | 5.8997  | 500  | 0.4940          |
| 0.5322        | 7.0796  | 600  | 0.4859          |
| 0.5272        | 8.2596  | 700  | 0.4807          |
| 0.5245        | 9.4395  | 800  | 0.4772          |
| 0.5169        | 10.6195 | 900  | 0.4765          |
| 0.5204        | 11.7994 | 1000 | 0.4743          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1