| --- |
| library_name: transformers |
| license: mit |
| base_model: microsoft/speecht5_tts |
| tags: |
| - generated_from_trainer |
| datasets: |
| - common_voice_17_0 |
| model-index: |
| - name: speecht5_finetuned_with_Uzbek_data |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # speecht5_finetuned_with_Uzbek_data |
|
|
| This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the common_voice_17_0 dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.5099 |
| |
| ## 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: 0.0002 |
| - train_batch_size: 32 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 128 |
| - 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: 200 |
| - training_steps: 1000 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:------:|:----:|:---------------:| |
| | 0.6618 | 0.7331 | 250 | 0.6034 | |
| | 0.594 | 1.4663 | 500 | 0.5597 | |
| | 0.5596 | 2.1994 | 750 | 0.5249 | |
| | 0.5437 | 2.9326 | 1000 | 0.5099 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.46.2 |
| - Pytorch 2.5.1+cu121 |
| - Datasets 3.1.0 |
| - Tokenizers 0.20.3 |
| |
