| | --- |
| | license: mit |
| | base_model: microsoft/speecht5_tts |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: Finetuned_speecht5_2 |
| | 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. --> |
| |
|
| | # Finetuned_speecht5_2 |
| |
|
| | This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.4976 |
| |
|
| | ## 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: 16 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 2 |
| | - 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: 5000 |
| | - mixed_precision_training: Native AMP |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | |
| | |:-------------:|:-------:|:----:|:---------------:| |
| | | 0.5279 | 5.9172 | 500 | 0.4841 | |
| | | 0.5081 | 11.8343 | 1000 | 0.4887 | |
| | | 0.4844 | 17.7515 | 1500 | 0.4822 | |
| | | 0.4897 | 23.6686 | 2000 | 0.4829 | |
| | | 0.4708 | 29.5858 | 2500 | 0.4898 | |
| | | 0.4801 | 35.5030 | 3000 | 0.4916 | |
| | | 0.4805 | 41.4201 | 3500 | 0.4923 | |
| | | 0.4617 | 47.3373 | 4000 | 0.5006 | |
| | | 0.4761 | 53.2544 | 4500 | 0.4999 | |
| | | 0.4616 | 59.1716 | 5000 | 0.4976 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.42.3 |
| | - Pytorch 2.1.2 |
| | - Datasets 2.20.0 |
| | - Tokenizers 0.19.1 |
| |
|
