Text-to-Speech
Transformers
TensorBoard
Safetensors
Croatian
speecht5
text-to-audio
Generated from Trainer
# pip install -U transformers accelerate
# Load model directly
from transformers import AutoProcessor, AutoModelForTextToSpectrogram
processor = AutoProcessor.from_pretrained("derek-thomas/speecht5_finetuned_voxpopuli_hr")
model = AutoModelForTextToSpectrogram.from_pretrained("derek-thomas/speecht5_finetuned_voxpopuli_hr", device_map="auto")Quick Links
speecht5_finetuned_voxpopuli_it
This model is a fine-tuned version of microsoft/speecht5_tts on the voxpopuli/it dataset. It achieves the following results on the evaluation set:
- Loss: 0.4497
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- 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 |
|---|---|---|---|
| 0.4773 | 32.52 | 1000 | 0.4502 |
| 0.4545 | 65.04 | 2000 | 0.4462 |
| 0.4488 | 97.56 | 3000 | 0.4502 |
| 0.4517 | 130.08 | 4000 | 0.4497 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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Model tree for derek-thomas/speecht5_finetuned_voxpopuli_hr
Base model
microsoft/speecht5_tts
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="derek-thomas/speecht5_finetuned_voxpopuli_hr")