---
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
datasets:
- voxpopuli
model-index:
- name: speecht5_tts_voxpopuli_it_v2
  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_voxpopuli_it_v2

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: 0.4484

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- 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: 200
- training_steps: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.5707        | 0.2358 | 100  | 0.5183          |
| 0.5452        | 0.4717 | 200  | 0.5096          |
| 0.5313        | 0.7075 | 300  | 0.4890          |
| 0.5229        | 0.9434 | 400  | 0.4807          |
| 0.5119        | 1.1792 | 500  | 0.4802          |
| 0.5121        | 1.4151 | 600  | 0.4681          |
| 0.5037        | 1.6509 | 700  | 0.4719          |
| 0.4996        | 1.8868 | 800  | 0.4691          |
| 0.4931        | 2.1226 | 900  | 0.4621          |
| 0.4903        | 2.3585 | 1000 | 0.4620          |
| 0.4949        | 2.5943 | 1100 | 0.4573          |
| 0.4853        | 2.8302 | 1200 | 0.4579          |
| 0.4826        | 3.0660 | 1300 | 0.4547          |
| 0.4827        | 3.3019 | 1400 | 0.4535          |
| 0.4835        | 3.5377 | 1500 | 0.4523          |
| 0.4802        | 3.7736 | 1600 | 0.4514          |
| 0.4777        | 4.0094 | 1700 | 0.4503          |
| 0.4792        | 4.2453 | 1800 | 0.4499          |
| 0.4779        | 4.4811 | 1900 | 0.4491          |
| 0.4755        | 4.7170 | 2000 | 0.4484          |


### Framework versions

- Transformers 4.43.1
- Pytorch 2.2.0
- Datasets 3.0.1
- Tokenizers 0.19.1