Instructions to use Apocalypse-19/speecht5_finetuned_french with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Apocalypse-19/speecht5_finetuned_french with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="Apocalypse-19/speecht5_finetuned_french")# Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("Apocalypse-19/speecht5_finetuned_french") model = AutoModelForTextToSpectrogram.from_pretrained("Apocalypse-19/speecht5_finetuned_french") - Notebooks
- Google Colab
- Kaggle
metadata
language:
- fr
base_model: microsoft/speecht5-tts
tags:
- text-to-speech
datasets:
- facebook/voxpopuli
model-index:
- name: speecht5-finetuned-fr
results: []
speecht5-finetuned-fr
This model is a fine-tuned version of microsoft/speecht5-tts on the facebook/voxpopuli dataset. It achieves the following results on the evaluation set:
- Loss: 0.4532
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: 8
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.5147 | 2.42 | 1000 | 0.4753 |
| 0.4932 | 4.84 | 2000 | 0.4629 |
| 0.4926 | 7.26 | 3000 | 0.4566 |
| 0.4907 | 9.69 | 4000 | 0.4542 |
| 0.4839 | 12.11 | 5000 | 0.4532 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3