| --- |
| library_name: transformers |
| license: mit |
| base_model: microsoft/speecht5_tts |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: result |
| 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. --> |
|
|
| # result |
|
|
| This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.4306 |
|
|
| ## 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: 0.0001 |
| - train_batch_size: 4 |
| - eval_batch_size: 2 |
| - seed: 42 |
| - gradient_accumulation_steps: 8 |
| - 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: 100 |
| - training_steps: 1000 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:-------:|:----:|:---------------:| |
| | 4.3611 | 1.6949 | 100 | 0.4645 | |
| | 3.9124 | 3.3898 | 200 | 0.4499 | |
| | 3.7546 | 5.0847 | 300 | 0.4453 | |
| | 3.6216 | 6.7797 | 400 | 0.4333 | |
| | 3.5083 | 8.4746 | 500 | 0.4299 | |
| | 3.5245 | 10.1695 | 600 | 0.4295 | |
| | 3.4645 | 11.8644 | 700 | 0.4191 | |
| | 3.3739 | 13.5593 | 800 | 0.4218 | |
| | 3.3132 | 15.2542 | 900 | 0.4316 | |
| | 3.3192 | 16.9492 | 1000 | 0.4306 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.47.1 |
| - Pytorch 2.5.1+cu121 |
| - Datasets 3.2.0 |
| - Tokenizers 0.21.0 |
|
|
