Instructions to use drownnila/Ergonomic_TTS_ID_v4_beta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use drownnila/Ergonomic_TTS_ID_v4_beta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="drownnila/Ergonomic_TTS_ID_v4_beta")# Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("drownnila/Ergonomic_TTS_ID_v4_beta") model = AutoModelForTextToSpectrogram.from_pretrained("drownnila/Ergonomic_TTS_ID_v4_beta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Ergonomic_TTS_ID_v2-lanjutan
This model is a fine-tuned version of drownnila/Ergonomic_TTS_ID_v2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4573
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: 200
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.5001 | 1.2469 | 1000 | 0.4656 |
| 0.4976 | 2.4938 | 2000 | 0.4623 |
| 0.4939 | 3.7408 | 3000 | 0.4616 |
| 0.4931 | 4.9877 | 4000 | 0.4607 |
| 0.4926 | 6.2345 | 5000 | 0.4591 |
| 0.4841 | 7.4814 | 6000 | 0.4595 |
| 0.4838 | 8.7283 | 7000 | 0.4589 |
| 0.4874 | 9.9752 | 8000 | 0.4571 |
| 0.481 | 11.2220 | 9000 | 0.4589 |
| 0.486 | 12.4689 | 10000 | 0.4573 |
Framework versions
- Transformers 4.56.1
- Pytorch 2.8.0+cu126
- Datasets 2.15.0
- Tokenizers 0.22.0
- Downloads last month
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Model tree for drownnila/Ergonomic_TTS_ID_v4_beta
Base model
microsoft/speecht5_tts Finetuned
drownnila/Ergonomic_TTS_ID Finetuned
drownnila/Ergonomic_TTS_ID_v2