Text-to-Speech TTS Model Training for German Language

Welcome to my repository where I share my German Text-to-Speech (TTS) model trained using Hugging Face Transformers.

You can find the trained model on my Hugging Face Model Hub: Salama1429/TTS_German_Speecht5_finetuned_voxpopuli_nl

Model Usage

To use the TTS model, you can follow these steps:

# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-to-speech", model="Salama1429/TTS_German_Speecht5_finetuned_voxpopuli_nl")

# Input your desired text
output_audio = pipe(desired_text)

language: nl
datasets: facebook/voxpopuli
pipeline_tag: text-to-speech

About the Model

The TTS_German_Speecht5_finetuned_voxpopuli_nl model is a fine-tuned version of the microsoft/speecht5_tts model on the facebook/voxpopuli dataset. During evaluation, the model achieved the following results:

• Loss: 0.4593

Training Procedure

Training Hyperparameters

The model was trained using the following hyperparameters:

• Learning Rate: 1e-05
• Training Batch Size: 4
• Evaluation 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
• Learning Rate Scheduler Type: Linear
• Learning Rate Scheduler Warmup Steps: 500
• Training Steps: 4000

Training Results

Training Loss	Epoch	Step	Validation Loss
0.5248	4.3	1000	0.4792
0.5019	8.61	2000	0.4663
0.4937	12.91	3000	0.4609
0.4896	17.21	4000	0.4593

Framework Versions

• Transformers 4.30.2
• PyTorch 2.0.1+cu118
• Datasets 2.13.1
• Tokenizers 0.13.3