Instructions to use Birma/speecht5_finetuned_zarma with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Birma/speecht5_finetuned_zarma with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="Birma/speecht5_finetuned_zarma")# Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("Birma/speecht5_finetuned_zarma") model = AutoModelForTextToSpectrogram.from_pretrained("Birma/speecht5_finetuned_zarma") - Notebooks
- Google Colab
- Kaggle
speecht5_finetuned_zarma
This model is a fine-tuned version of microsoft/speecht5_tts on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: nan
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 OptimizerNames.ADAMW_TORCH_FUSED 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: 50
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.2591 | 16.8889 | 50 | nan |
| 1.7534 | 33.4444 | 100 | nan |
| 1.446 | 50.0 | 150 | nan |
| 1.3861 | 66.8889 | 200 | nan |
| 1.2551 | 83.4444 | 250 | nan |
| 1.1811 | 100.0 | 300 | nan |
| 1.1416 | 116.8889 | 350 | nan |
| 1.0839 | 133.4444 | 400 | nan |
| 1.0502 | 150.0 | 450 | nan |
| 1.0335 | 166.8889 | 500 | nan |
| 1.0372 | 183.4444 | 550 | nan |
| 1.0037 | 200.0 | 600 | nan |
| 0.9739 | 216.8889 | 650 | nan |
| 1.027 | 233.4444 | 700 | nan |
| 0.9747 | 250.0 | 750 | nan |
| 0.9857 | 266.8889 | 800 | nan |
| 0.9798 | 283.4444 | 850 | nan |
| 0.9619 | 300.0 | 900 | nan |
| 0.9532 | 316.8889 | 950 | nan |
| 0.9474 | 333.4444 | 1000 | nan |
Framework versions
- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
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Model tree for Birma/speecht5_finetuned_zarma
Base model
microsoft/speecht5_tts