---
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
datasets:
- facebook/voxpopuli
model-index:
- name: speecht5_quick_finetuned_voxpopuli_it
  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. -->

# speecht5_quick_finetuned_voxpopuli_it

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: 0.4879

## 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: 250
- training_steps: 2500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.5535        | 1.53  | 250  | 0.5129          |
| 0.5395        | 3.07  | 500  | 0.5065          |
| 0.5393        | 4.6   | 750  | 0.4994          |
| 0.5316        | 6.13  | 1000 | 0.4956          |
| 0.5372        | 7.66  | 1250 | 0.4919          |
| 0.53          | 9.2   | 1500 | 0.4914          |
| 0.5277        | 10.73 | 1750 | 0.4888          |
| 0.5198        | 12.26 | 2000 | 0.4896          |
| 0.5236        | 13.79 | 2250 | 0.4880          |
| 0.5209        | 15.33 | 2500 | 0.4879          |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2