Hugging Face's logo

ahk-d
/
speecht5_finetuned_voxpopuli_de

Text-to-Speech
Transformers
TensorBoard
Safetensors
speecht5
text-to-audio
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
speecht5_finetuned_voxpopuli_de / README.md
ahk-d's picture
ahk-d
Update README.md
b45c5b7 verified
preview code
|
raw
history blame
1.77 kB
metadata
library_name: transformers
license: mit
base_model: microsoft/speecht5_tts
tags:
  - generated_from_trainer
datasets:
  - voxpopuli
model-index:
  - name: speecht5_finetuned_voxpopuli_de
    results: []
pipeline_tag: text-to-speech

speecht5_finetuned_voxpopuli_de

This model is a fine-tuned version of microsoft/speecht5_tts on the voxpopuli dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4708

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: 4
  • eval_batch_size: 2
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 32
  • optimizer: Use 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: 500
  • training_steps: 4000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
0.5265 11.6110 1000 0.4860
0.5029 23.2221 2000 0.4740
0.4984 34.8331 3000 0.4721
0.4965 46.4441 4000 0.4708

Framework versions

  • Transformers 4.46.2
  • Pytorch 2.5.1+cu121
  • Datasets 3.1.0
  • Tokenizers 0.20.3