Text-to-Speech
Transformers
TensorBoard
Safetensors
Dutch
speecht5
text-to-audio
Generated from Trainer
# Load model directly
from transformers import AutoProcessor, AutoModelForTextToSpectrogram
processor = AutoProcessor.from_pretrained("EYEDOL/speek")
model = AutoModelForTextToSpectrogram.from_pretrained("EYEDOL/speek")Quick Links
SpeechT5 TTS Dutch
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: 0.3553
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 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 |
|---|---|---|---|
| 0.3986 | 3.0488 | 1000 | 0.3671 |
| 0.3848 | 6.0976 | 2000 | 0.3597 |
| 0.3821 | 9.1463 | 3000 | 0.3544 |
| 0.3813 | 12.1951 | 4000 | 0.3553 |
Framework versions
- Transformers 4.49.0.dev0
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.21.0
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Model tree for EYEDOL/speek
Base model
microsoft/speecht5_tts
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="EYEDOL/speek")