---
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
datasets:
- voxpopuli
model-index:
- name: speecht5_finetuned_voxpopuli_fr
  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_fr

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: 0.4697

## 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: 5e-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

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.765         | 0.23  | 50   | 0.6575          |
| 0.687         | 0.47  | 100  | 0.6106          |
| 0.6423        | 0.7   | 150  | 0.5548          |
| 0.5792        | 0.94  | 200  | 0.5300          |
| 0.5658        | 1.17  | 250  | 0.5186          |
| 0.5558        | 1.41  | 300  | 0.5078          |
| 0.5484        | 1.64  | 350  | 0.5029          |
| 0.5427        | 1.87  | 400  | 0.4981          |
| 0.5349        | 2.11  | 450  | 0.4921          |
| 0.524         | 2.34  | 500  | 0.4906          |
| 0.5243        | 2.58  | 550  | 0.4857          |
| 0.5238        | 2.81  | 600  | 0.4835          |
| 0.5104        | 3.05  | 650  | 0.4796          |
| 0.516         | 3.28  | 700  | 0.4769          |
| 0.5084        | 3.51  | 750  | 0.4763          |
| 0.5029        | 3.75  | 800  | 0.4749          |
| 0.5015        | 3.98  | 850  | 0.4725          |
| 0.5045        | 4.22  | 900  | 0.4716          |
| 0.503         | 4.45  | 950  | 0.4706          |
| 0.5013        | 4.69  | 1000 | 0.4697          |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.2
- Tokenizers 0.13.3