---
license: mit
tags:
- generated_from_trainer
datasets:
- voxpopuli
pipeline_tag: text-to-speech
base_model: microsoft/speecht5_tts
model-index:
- name: speecht5_finetuned_facebook_voxpopuli_french
  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_facebook_voxpopuli_french

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: 0.4379

## 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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- 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: 100
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.4872        | 1.0   | 1584  | 0.4663          |
| 0.4656        | 2.0   | 3168  | 0.4642          |
| 0.4686        | 3.0   | 4752  | 0.4533          |
| 0.4576        | 4.0   | 6336  | 0.4479          |
| 0.4658        | 5.0   | 7920  | 0.4485          |
| 0.4536        | 6.0   | 9504  | 0.4443          |
| 0.4559        | 7.0   | 11088 | 0.4426          |
| 0.449         | 8.0   | 12672 | 0.4410          |
| 0.4469        | 9.0   | 14256 | 0.4420          |
| 0.4565        | 10.0  | 15840 | 0.4402          |
| 0.4428        | 11.0  | 17424 | 0.4470          |
| 0.4412        | 12.0  | 19008 | 0.4400          |
| 0.4437        | 13.0  | 20592 | 0.4396          |
| 0.4395        | 14.0  | 22176 | 0.4385          |
| 0.4461        | 15.0  | 23760 | 0.4407          |
| 0.4401        | 16.0  | 25344 | 0.4387          |
| 0.4407        | 17.0  | 26928 | 0.4379          |
| 0.4359        | 18.0  | 28512 | 0.4384          |
| 0.4338        | 19.0  | 30096 | 0.4387          |
| 0.4326        | 20.0  | 31680 | 0.4381          |
| 0.4406        | 21.0  | 33264 | 0.4390          |
| 0.437         | 22.0  | 34848 | 0.4387          |
| 0.4357        | 23.0  | 36432 | 0.4389          |
| 0.4309        | 24.0  | 38016 | 0.4387          |
| 0.441         | 25.0  | 39600 | 0.4379          |
| 0.4355        | 26.0  | 41184 | 0.4378          |
| 0.4312        | 27.0  | 42768 | 0.4380          |
| 0.4328        | 28.0  | 44352 | 0.4388          |
| 0.4289        | 29.0  | 45936 | 0.4380          |
| 0.4291        | 30.0  | 47520 | 0.4379          |


### Framework versions

- Transformers 4.30.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3