---
library_name: transformers
license: mit
base_model: microsoft/speecht5_tts
tags:
- Text-To-Speech
- generated_from_trainer
model-index:
- name: speecht5_ft_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_ft_french

This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6022

## 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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 0.7809        | 0.5587  | 100  | 0.7240          |
| 0.7682        | 1.1173  | 200  | 0.6956          |
| 0.7216        | 1.6760  | 300  | 0.6608          |
| 0.7083        | 2.2346  | 400  | 0.6578          |
| 0.6839        | 2.7933  | 500  | 0.6375          |
| 0.6805        | 3.3520  | 600  | 0.6369          |
| 0.6587        | 3.9106  | 700  | 0.6269          |
| 0.6786        | 4.4693  | 800  | 0.6252          |
| 0.6561        | 5.0279  | 900  | 0.6192          |
| 0.6553        | 5.5866  | 1000 | 0.6159          |
| 0.6477        | 6.1453  | 1100 | 0.6108          |
| 0.6537        | 6.7039  | 1200 | 0.6121          |
| 0.6635        | 7.2626  | 1300 | 0.6106          |
| 0.6409        | 7.8212  | 1400 | 0.6059          |
| 0.6503        | 8.3799  | 1500 | 0.6066          |
| 0.6391        | 8.9385  | 1600 | 0.6033          |
| 0.6388        | 9.4972  | 1700 | 0.6039          |
| 0.6407        | 10.0559 | 1800 | 0.6010          |
| 0.6388        | 10.6145 | 1900 | 0.6016          |
| 0.6415        | 11.1732 | 2000 | 0.6022          |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0