---
license: mit
tags:
- generated_from_trainer
datasets:
- voxpopuli
model-index:
- name: speecht5_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_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: 0.4968

## 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: 0.0005
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 25

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.6707        | 1.0   | 108  | 0.5946          |
| 0.6625        | 2.0   | 217  | 0.6029          |
| 0.708         | 3.0   | 325  | 0.6118          |
| 0.6588        | 4.0   | 434  | 0.7109          |
| 0.6614        | 5.0   | 542  | 0.5799          |
| 0.6375        | 6.0   | 651  | 0.5714          |
| 0.619         | 7.0   | 759  | 0.5699          |
| 0.5806        | 8.0   | 868  | 0.5538          |
| 0.6024        | 9.0   | 976  | 0.5856          |
| 0.5728        | 10.0  | 1085 | 0.5446          |
| 0.5624        | 11.0  | 1193 | 0.5508          |
| 0.5711        | 12.0  | 1302 | 0.5376          |
| 0.5438        | 13.0  | 1410 | 0.5300          |
| 0.5308        | 14.0  | 1519 | 0.5206          |
| 0.5536        | 15.0  | 1627 | 0.5359          |
| 0.5285        | 16.0  | 1736 | 0.5264          |
| 0.525         | 17.0  | 1844 | 0.5108          |
| 0.4961        | 18.0  | 1953 | 0.5116          |
| 0.5111        | 19.0  | 2061 | 0.5042          |
| 0.4869        | 20.0  | 2170 | 0.5050          |
| 0.4864        | 21.0  | 2278 | 0.4994          |
| 0.4794        | 22.0  | 2387 | 0.5039          |
| 0.4787        | 23.0  | 2495 | 0.4975          |
| 0.4692        | 24.0  | 2604 | 0.4961          |
| 0.4656        | 24.88 | 2700 | 0.4968          |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3